Due to extensive growth of the Internet and increasing availability of tools and methods for intruding and attacking
networks, intrusion detection has become a critical component of network security parameters. TCP/IP protocol suite is the defacto
standard for communication on the Internet. The underlying vulnerabilities in the protocols is the root cause of intrusions. Therefor
Intrusion detection system becomes an important element in network security that controls real time data and leads to huge
dimensional problem. Processing large number of packets and data in real time is very difficult and costly. Therefor data preprocessing
is necessary to remove redundant and unwanted information from packets and clean network data. Here, we are focusing on
two important aspects of intrusion detection; one is accuracy and other is performance. The layered approach of TCP/IP model can be
applied to packet pre-processing to achieve early and faster intrusion detection. Motivation for the paper comes from the large impact
data preprocessing has on the accuracy and capability of anomaly-based NIPS. In this paper it is demonstrated that high attack
detection accuracy can be achieved by using layered approach for data preprocessing in Internet. To reduce false positive rate and to
increase efficiency of detection, the paper proposed framework for preprocessing in intrusion prevention system. We experimented
with real time network traffic as well as he KDDcup99 dataset for our research.
This document discusses the Address Resolution Protocol (ARP) and its use in intrusion detection systems. It proposes a standardized 64-byte ARP protocol structure to more easily capture ARP packets from a network. The structure includes fields for frame information, destination and source addresses, ARP type details, and sender/target MAC and IP addresses. This standardized structure could be integrated into network monitoring to help detect intrusions without affecting normal data transfer processes. Overall, the document aims to optimize the ARP sequence for use in intrusion detection systems.
The nature of wireless networks itself created new vulnerabilities that in the classical wired networks do
not exist. This results in an evolutional requirement to implement new sophisticated security mechanism in
form of Intrusion Detection and Prevention Systems. This paper deals with security issues of small office
and home office wireless networks. The goal of our work is to design and evaluate wireless IDPS with use
of packet injection method. Decrease of attacker’s traffic by 95% was observed when compared to
attacker’s traffic without deployment of proposed IDPS system.
Network Attack and Intrusion Prevention System Deris Stiawan
(1) The document discusses network attack and intrusion prevention systems. It describes how intrusion prevention systems (IPS) aim to detect and block threats in online traffic in real-time, beyond just detecting threats like intrusion detection systems (IDS).
(2) Feature extraction from network traffic is important for IPS to analyze without being overwhelmed by raw data. The document examines relevant features to monitor and criteria for deciding what is important to track.
(3) Experimental testing is needed to evaluate IPS performance. The document outlines stages for training systems, testing methodsologies, and resuming test results. This helps IPS avoid unexpected outcomes and ensures continuous monitoring.
Intrusion Detection and Prevention System in an Enterprise NetworkOkehie Collins
This document describes a project on intrusion detection and prevention systems in an enterprise network. It was submitted by Okehie Collins Obinna to the Department of Computer Science at the Federal University of Technology in partial fulfillment of a Bachelor of Technology degree in Computer Science. The project analyzes intrusion detection and prevention technologies used in enterprise networks and designs a desktop application to monitor a computer network system for possible intrusions and provide an interface for a network administrator.
Team research paper and project on network vulnerabilities with multiple attacks and defesnses:
Cybersecurity
-For this project, our class was paired with teams to attempt to find vulnerabilities in other teams networks and to successfully beach their network.
-My role in this group was to help breach other team vulnerabilities through different attacks like responder attacks, honeypots, etc.
-The main challenges of this project were trying to find the vulnerabilities successfully, as the whole team had troubles with each of our different attacks and defenses.
-We learned how to use cybersecurity tools to help find vulnerabilities in networks and how to protect against them better. For example, in the honeypot we used we deployed it to port 80, when the attacker tried to access our fake server we were notified. We also deployed palto alto firewall to create our private and secure network. For an attack, we also used password crackers like john the ripper. This project taught us how to breach networks as a team.
EFFICIENT DEFENSE SYSTEM FOR IP SPOOFING IN NETWORKScscpconf
In this age of gigabit Ethernet and broadband internet, network security has been the top
priority for most of the researchers. Technology advancements have advantages as well as
disadvantages. Most of the communication of present world, the e-world, takes place online,
through the internet. Thus the context of network intrusions and attacks to hack into servers also
came into existence. A technique to perform this activity is made possible by preventing the
discovery of the sender’s identity through IP Spoofing [7]. Many popular internet sites have
been hacked and attackers try to forge or spoof the source addresses in IP packets. Using
spoofing detection technique, the user can retrieve the list of IP addresses and able to identify
the malicious IP addresses.Hence mechanisms must be designed to prevent hacking. This paper
proposes a novel technique to detect IP spoofing based on traffic verification and filtering
THREATS are possible attacks.
It includes
The spread of computer viruses
Infiltration and theft of data from external hackers
Engineered network overloads triggered by malicious mass e-mailing
Misuse of computer resources and confidential information by employees
Unauthorized financial transactions and other kinds of computer fraud conducted in the company's name
Electronic inspection of corporate computer data by outside parties
Damage from failure, fire, or natural disasters
This document discusses network security and protocols. It covers internal and external threats to networks like unauthorized access, data destruction, and hacking. It also discusses ways to protect networks from these threats, including passwords, firewalls, encryption, authentication protocols, and virtual local area networks (VLANs). The document outlines concepts like cryptography, digital signatures, and authentication protocols. It also discusses firewalls, storage technologies like RAID, NAS, and SAN for fault tolerance, and tape backups.
This document discusses the Address Resolution Protocol (ARP) and its use in intrusion detection systems. It proposes a standardized 64-byte ARP protocol structure to more easily capture ARP packets from a network. The structure includes fields for frame information, destination and source addresses, ARP type details, and sender/target MAC and IP addresses. This standardized structure could be integrated into network monitoring to help detect intrusions without affecting normal data transfer processes. Overall, the document aims to optimize the ARP sequence for use in intrusion detection systems.
The nature of wireless networks itself created new vulnerabilities that in the classical wired networks do
not exist. This results in an evolutional requirement to implement new sophisticated security mechanism in
form of Intrusion Detection and Prevention Systems. This paper deals with security issues of small office
and home office wireless networks. The goal of our work is to design and evaluate wireless IDPS with use
of packet injection method. Decrease of attacker’s traffic by 95% was observed when compared to
attacker’s traffic without deployment of proposed IDPS system.
Network Attack and Intrusion Prevention System Deris Stiawan
(1) The document discusses network attack and intrusion prevention systems. It describes how intrusion prevention systems (IPS) aim to detect and block threats in online traffic in real-time, beyond just detecting threats like intrusion detection systems (IDS).
(2) Feature extraction from network traffic is important for IPS to analyze without being overwhelmed by raw data. The document examines relevant features to monitor and criteria for deciding what is important to track.
(3) Experimental testing is needed to evaluate IPS performance. The document outlines stages for training systems, testing methodsologies, and resuming test results. This helps IPS avoid unexpected outcomes and ensures continuous monitoring.
Intrusion Detection and Prevention System in an Enterprise NetworkOkehie Collins
This document describes a project on intrusion detection and prevention systems in an enterprise network. It was submitted by Okehie Collins Obinna to the Department of Computer Science at the Federal University of Technology in partial fulfillment of a Bachelor of Technology degree in Computer Science. The project analyzes intrusion detection and prevention technologies used in enterprise networks and designs a desktop application to monitor a computer network system for possible intrusions and provide an interface for a network administrator.
Team research paper and project on network vulnerabilities with multiple attacks and defesnses:
Cybersecurity
-For this project, our class was paired with teams to attempt to find vulnerabilities in other teams networks and to successfully beach their network.
-My role in this group was to help breach other team vulnerabilities through different attacks like responder attacks, honeypots, etc.
-The main challenges of this project were trying to find the vulnerabilities successfully, as the whole team had troubles with each of our different attacks and defenses.
-We learned how to use cybersecurity tools to help find vulnerabilities in networks and how to protect against them better. For example, in the honeypot we used we deployed it to port 80, when the attacker tried to access our fake server we were notified. We also deployed palto alto firewall to create our private and secure network. For an attack, we also used password crackers like john the ripper. This project taught us how to breach networks as a team.
EFFICIENT DEFENSE SYSTEM FOR IP SPOOFING IN NETWORKScscpconf
In this age of gigabit Ethernet and broadband internet, network security has been the top
priority for most of the researchers. Technology advancements have advantages as well as
disadvantages. Most of the communication of present world, the e-world, takes place online,
through the internet. Thus the context of network intrusions and attacks to hack into servers also
came into existence. A technique to perform this activity is made possible by preventing the
discovery of the sender’s identity through IP Spoofing [7]. Many popular internet sites have
been hacked and attackers try to forge or spoof the source addresses in IP packets. Using
spoofing detection technique, the user can retrieve the list of IP addresses and able to identify
the malicious IP addresses.Hence mechanisms must be designed to prevent hacking. This paper
proposes a novel technique to detect IP spoofing based on traffic verification and filtering
THREATS are possible attacks.
It includes
The spread of computer viruses
Infiltration and theft of data from external hackers
Engineered network overloads triggered by malicious mass e-mailing
Misuse of computer resources and confidential information by employees
Unauthorized financial transactions and other kinds of computer fraud conducted in the company's name
Electronic inspection of corporate computer data by outside parties
Damage from failure, fire, or natural disasters
This document discusses network security and protocols. It covers internal and external threats to networks like unauthorized access, data destruction, and hacking. It also discusses ways to protect networks from these threats, including passwords, firewalls, encryption, authentication protocols, and virtual local area networks (VLANs). The document outlines concepts like cryptography, digital signatures, and authentication protocols. It also discusses firewalls, storage technologies like RAID, NAS, and SAN for fault tolerance, and tape backups.
This document discusses using packet filtering as a mechanism for network security. It describes how packet filters examine packet headers to make routing decisions based on rules. Factors like asymmetric access requirements and protocol characteristics can complicate rule implementation. The document provides an example set of rules to allow access between two networks in most cases, but deny it from a specific subnet due to security issues. It notes that correctly specifying complex filter rules is difficult, and reordering rules can unintentionally change the access policy that was intended. Packet filtering shows promise as a network security tool but has limitations that must be understood.
This document discusses security challenges in wireless sensor networks. It outlines key challenges like limited energy and communication capabilities as sensors are often deployed in accessible areas. It discusses approaches for secure key establishment, privacy concerns around surveillance, threats like denial of service attacks, and the need for secure routing, intrusion detection, and data aggregation given the resource constraints of sensor networks. Research is still needed to address security challenges posed by the unique aspects of sensor network environments and applications.
Next Generation Network: Security and Architectureijsrd.com
Wireless sensor networks will be widely deployed in the near future. While much research has focused on making these networks feasible and useful, security has received little attention. Wireless Sensor Networks (WSN) are a most challenging and emerging technology for the Research due to their vital scope in the field coupled with their low processing power and associated low energy. As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design staring with a brief overview of the sensor networks security, a review is made of and how to provide the security in the wireless sensor networks. This paper studies the security problems, Requirement, Architecture of WSN and different platform, characterized by severely constrained computational and energy resources, and an ad hoc operational environment.
The document discusses the history and development of virtual private networks (VPNs). It explains that early VPNs used IPSec but had problems with complexity and interoperability. This led to the development of user-space VPNs using virtual network interfaces and encapsulating IP packets in UDP for transmission over public networks like the internet. OpenVPN is highlighted as an open-source user-space VPN that follows this model and provides a more portable and easier to configure alternative to IPSec VPNs.
The document discusses data security in local networks using distributed firewalls. It describes how distributed firewalls work to overcome issues with traditional firewalls, which rely on a single entry point. Distributed firewalls are centrally managed from a network server but installed on endpoints throughout the network. This allows security policies to be defined and pushed centrally while filtering traffic both from the internet and internally. It also discusses how distributed firewalls use pull and push techniques to update endpoints with the latest security policies from the central management server.
The document discusses trends and challenges in internet of things (IoT) from an information systems perspective. It describes IoT as involving the interconnection of heterogeneous networked entities through various communication patterns like human-to-human and machine-to-machine. The document outlines security and privacy as major issues in IoT due to the heterogeneity of devices, dynamicity of networks, and need to protect data. It reviews existing research that proposes solutions for these issues but identifies drawbacks like lack of testing on real heterogeneous devices and not addressing communication between different devices.
Network security is important to protect systems from attacks. Firewalls act as the first line of defense, blocking unauthorized incoming and outgoing network traffic based on security rules. Different types of firewalls operate at different layers of the OSI model and provide varying levels of security. No single security measure can guarantee protection, so a defense-in-depth approach using firewalls along with other tools like intrusion detection systems is recommended.
The network layer is responsible for routing data across interconnected networks through logical addressing and packet encapsulation. It uses protocols like IP, ICMP, and routing protocols to determine the best path and encapsulate higher layer data into packets with a network header for transmission. Functions include routing, fragmentation and reassembly, and providing a logical addressing scheme independent of physical hardware addresses.
This document discusses wireless communication security. It begins by defining wireless communication and noting some advantages and disadvantages, including security issues. It then discusses the general characteristics of the Wireless Application Protocol (WAP) and provides an overview of wireless communication systems. The document outlines some common security threats in wireless networks like unauthorized disclosure, data modification, network disruption, and repudiation. It also describes different types of wireless attacks and security goals in wireless networks to provide authentication, confidentiality, integrity, non-repudiation, and availability. Symmetric and asymmetric encryption techniques are introduced as methods for encrypting data in wireless networks.
This document discusses network hacking techniques. It describes ARP spoofing attacks, including generating spoofed ARP replies to redirect traffic. It also discusses sniffing attacks, session hijacking, and tools used for these attacks like Ettercap and Dsniff. Detection methods are outlined, though the document notes most older operating systems lacked detection. Hypothetical detection applications are proposed to track ARP entries and identify spoofing.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document outlines objectives for day 1 of a training on network security and hacking techniques, including hardening Linux and Windows 2000 systems, analyzing software vulnerabilities and attacking techniques, and discussing elements of network security like confidentiality, integrity, availability, and models for access control. It also provides details on installation and configuration of Linux operating systems for network security.
In this research work an Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) will be implemented to detect and prevent critical networks infrastructure from cyber-attacks. To strengthen network security and improve the network's active defense intrusion detection capabilities, this project will consist of intrusion detection system using honey token based encrypted pointers and intrusion prevention system which based on the mixed interactive honeypot. The Intrusion Detection System (IDS) is based on the novel approach of Honey Token based Encrypted Pointers. This honey token inside the frame will serve as a trap for the attacker. All nodes operating within the working domain of critical infrastructure network are divided into four different pools. This division is based per their computational power and level of vulnerability. These pools are provided with different levels of security measures within the network. IDS use different number of Honey Tokens (HT) per frame for every different pool e.g. Pool-A contains 4 HT/frame, Pool-B contains 3 HT/frame, Pool-C contains 2 HT/frame and Pool-D contain 1 HT/frame. Moreover, every pool uses different types of encryption schemes (AES-128,192,256). Our critical infrastructure network of 64 nodes is under the umbrella of unified security provided by this single Network Intrusion Detection System (NIDS). After the design phase of IDS, we analyze the performance of IDS in terms of True Positives (TP) and False Negatives (FN). Finally, we test these IDS through Network Penetration Testing (NPT) phase. The detection rate depends on the number of honey tokens per frame. Our proposed IDS are a scalable solution and it can be implemented for any number of nodes in critical infrastructure network. However, in case of Intrusion Prevention System (IPS) we use Virtual honeypot technology which is the best active prevention technology among all honeypot technologies. By using the original operating system and virtual technology, the honeypot lures attackers in a pre-arranged manner, analyzes and audits various attacking behavior, tracks the attack source, obtains evidence, and finds effective solutions.
Network Security consists of the provisions and policies adopted by a network
administrator to prevent and monitor unauthorized access, misuse, modification,
or denial of a computer network and network-accessible resources. Network
security involves the authorization of access to data in a network, which is
controlled by the network administrator. Users choose or are assigned an ID and
password or other authenticating information that allows them access to
information and programs within their authority.
This document describes a distributed intrusion detection system based on honeypots. It proposes using honeypots to collect invasion characteristics on the network and genetic clustering algorithms to extract data for analysis. The system combines protocol analysis and signature detection modules to improve detection performance. An evaluation using KDDCUP 99 intrusion data showed the system can better detect intrusions and improve network security compared to traditional intrusion detection systems.
Utilizing Data Mining Approches in the Detection of Intrusion in IPv6 Network...IDES Editor
The development of Internet protocols are greatly
needed as the network security becomes one of the most
important issues. This brings the need to develop IPv4 into
IPv6 in order to proceed towards increasing the network
capacity.
Now Intruders are considered as one of the most serious
threats to the internet security. Data mining techniques have
been successfully utilized in many applications. Many
research projects have applied data mining techniques to
intrusion detection. Furthermore different types of data
mining algorithms are very much useful to intrusion detection
such as Classification, Link Analysis and Sequence Analysis.
Moreover, one of the major challenges in securing fast
networks is the online detection of suspicious anomalies in
network traffic pattern. Most of the current security solutions
failed to perform the security task in online mode because of
the time needed to capture the packets and making decision
about it.
Practically, this study provides alliterative survey for the
enhancement associated with IPv6 in terms of its security
related functions. It is worthy mentioned that this study is
concurred with the data mining approaches that have been
used to detect intrusions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this research work an Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) will be implemented to detect and prevent critical networks infrastructure from cyber-attacks. To strengthen network security and improve the network's active defense intrusion detection capabilities, this project will consist of intrusion detection system using honey token based encrypted pointers and intrusion prevention system which based on the mixed interactive honeypot. The Intrusion Detection System (IDS) is based on the novel approach of Honey Token based Encrypted Pointers.
This document proposes a novel method to defend against IP spoofing attacks using packet filtering and marking techniques. It involves a network architecture model with trusted nodes that can access each other after authentication. The proposed method uses packet tracing and cooperation between trusted adjacent nodes to detect and block spoofed packets entering the trusted network from external sources. It aims to effectively defend against distributed denial of service attacks and IP spoofing attacks.
Denial of Service Attack Defense TechniquesIRJET Journal
This document discusses denial of service (DoS) attacks and defense techniques. It begins by defining DoS attacks and describing common types like SYN floods, teardrop attacks, and ICMP floods. It then discusses various defense techniques including intrusion detection systems, intrusion prevention systems, and packet filtering firewalls. It compares the advantages and disadvantages of these different techniques. In conclusion, the document reviews that various techniques can be used to detect and prevent DoS attacks, with no single best approach, and defense requires a layered approach using multiple techniques.
This document discusses using packet filtering as a mechanism for network security. It describes how packet filters examine packet headers to make routing decisions based on rules. Factors like asymmetric access requirements and protocol characteristics can complicate rule implementation. The document provides an example set of rules to allow access between two networks in most cases, but deny it from a specific subnet due to security issues. It notes that correctly specifying complex filter rules is difficult, and reordering rules can unintentionally change the access policy that was intended. Packet filtering shows promise as a network security tool but has limitations that must be understood.
This document discusses security challenges in wireless sensor networks. It outlines key challenges like limited energy and communication capabilities as sensors are often deployed in accessible areas. It discusses approaches for secure key establishment, privacy concerns around surveillance, threats like denial of service attacks, and the need for secure routing, intrusion detection, and data aggregation given the resource constraints of sensor networks. Research is still needed to address security challenges posed by the unique aspects of sensor network environments and applications.
Next Generation Network: Security and Architectureijsrd.com
Wireless sensor networks will be widely deployed in the near future. While much research has focused on making these networks feasible and useful, security has received little attention. Wireless Sensor Networks (WSN) are a most challenging and emerging technology for the Research due to their vital scope in the field coupled with their low processing power and associated low energy. As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design staring with a brief overview of the sensor networks security, a review is made of and how to provide the security in the wireless sensor networks. This paper studies the security problems, Requirement, Architecture of WSN and different platform, characterized by severely constrained computational and energy resources, and an ad hoc operational environment.
The document discusses the history and development of virtual private networks (VPNs). It explains that early VPNs used IPSec but had problems with complexity and interoperability. This led to the development of user-space VPNs using virtual network interfaces and encapsulating IP packets in UDP for transmission over public networks like the internet. OpenVPN is highlighted as an open-source user-space VPN that follows this model and provides a more portable and easier to configure alternative to IPSec VPNs.
The document discusses data security in local networks using distributed firewalls. It describes how distributed firewalls work to overcome issues with traditional firewalls, which rely on a single entry point. Distributed firewalls are centrally managed from a network server but installed on endpoints throughout the network. This allows security policies to be defined and pushed centrally while filtering traffic both from the internet and internally. It also discusses how distributed firewalls use pull and push techniques to update endpoints with the latest security policies from the central management server.
The document discusses trends and challenges in internet of things (IoT) from an information systems perspective. It describes IoT as involving the interconnection of heterogeneous networked entities through various communication patterns like human-to-human and machine-to-machine. The document outlines security and privacy as major issues in IoT due to the heterogeneity of devices, dynamicity of networks, and need to protect data. It reviews existing research that proposes solutions for these issues but identifies drawbacks like lack of testing on real heterogeneous devices and not addressing communication between different devices.
Network security is important to protect systems from attacks. Firewalls act as the first line of defense, blocking unauthorized incoming and outgoing network traffic based on security rules. Different types of firewalls operate at different layers of the OSI model and provide varying levels of security. No single security measure can guarantee protection, so a defense-in-depth approach using firewalls along with other tools like intrusion detection systems is recommended.
The network layer is responsible for routing data across interconnected networks through logical addressing and packet encapsulation. It uses protocols like IP, ICMP, and routing protocols to determine the best path and encapsulate higher layer data into packets with a network header for transmission. Functions include routing, fragmentation and reassembly, and providing a logical addressing scheme independent of physical hardware addresses.
This document discusses wireless communication security. It begins by defining wireless communication and noting some advantages and disadvantages, including security issues. It then discusses the general characteristics of the Wireless Application Protocol (WAP) and provides an overview of wireless communication systems. The document outlines some common security threats in wireless networks like unauthorized disclosure, data modification, network disruption, and repudiation. It also describes different types of wireless attacks and security goals in wireless networks to provide authentication, confidentiality, integrity, non-repudiation, and availability. Symmetric and asymmetric encryption techniques are introduced as methods for encrypting data in wireless networks.
This document discusses network hacking techniques. It describes ARP spoofing attacks, including generating spoofed ARP replies to redirect traffic. It also discusses sniffing attacks, session hijacking, and tools used for these attacks like Ettercap and Dsniff. Detection methods are outlined, though the document notes most older operating systems lacked detection. Hypothetical detection applications are proposed to track ARP entries and identify spoofing.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
The document outlines objectives for day 1 of a training on network security and hacking techniques, including hardening Linux and Windows 2000 systems, analyzing software vulnerabilities and attacking techniques, and discussing elements of network security like confidentiality, integrity, availability, and models for access control. It also provides details on installation and configuration of Linux operating systems for network security.
In this research work an Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) will be implemented to detect and prevent critical networks infrastructure from cyber-attacks. To strengthen network security and improve the network's active defense intrusion detection capabilities, this project will consist of intrusion detection system using honey token based encrypted pointers and intrusion prevention system which based on the mixed interactive honeypot. The Intrusion Detection System (IDS) is based on the novel approach of Honey Token based Encrypted Pointers. This honey token inside the frame will serve as a trap for the attacker. All nodes operating within the working domain of critical infrastructure network are divided into four different pools. This division is based per their computational power and level of vulnerability. These pools are provided with different levels of security measures within the network. IDS use different number of Honey Tokens (HT) per frame for every different pool e.g. Pool-A contains 4 HT/frame, Pool-B contains 3 HT/frame, Pool-C contains 2 HT/frame and Pool-D contain 1 HT/frame. Moreover, every pool uses different types of encryption schemes (AES-128,192,256). Our critical infrastructure network of 64 nodes is under the umbrella of unified security provided by this single Network Intrusion Detection System (NIDS). After the design phase of IDS, we analyze the performance of IDS in terms of True Positives (TP) and False Negatives (FN). Finally, we test these IDS through Network Penetration Testing (NPT) phase. The detection rate depends on the number of honey tokens per frame. Our proposed IDS are a scalable solution and it can be implemented for any number of nodes in critical infrastructure network. However, in case of Intrusion Prevention System (IPS) we use Virtual honeypot technology which is the best active prevention technology among all honeypot technologies. By using the original operating system and virtual technology, the honeypot lures attackers in a pre-arranged manner, analyzes and audits various attacking behavior, tracks the attack source, obtains evidence, and finds effective solutions.
Network Security consists of the provisions and policies adopted by a network
administrator to prevent and monitor unauthorized access, misuse, modification,
or denial of a computer network and network-accessible resources. Network
security involves the authorization of access to data in a network, which is
controlled by the network administrator. Users choose or are assigned an ID and
password or other authenticating information that allows them access to
information and programs within their authority.
This document describes a distributed intrusion detection system based on honeypots. It proposes using honeypots to collect invasion characteristics on the network and genetic clustering algorithms to extract data for analysis. The system combines protocol analysis and signature detection modules to improve detection performance. An evaluation using KDDCUP 99 intrusion data showed the system can better detect intrusions and improve network security compared to traditional intrusion detection systems.
Utilizing Data Mining Approches in the Detection of Intrusion in IPv6 Network...IDES Editor
The development of Internet protocols are greatly
needed as the network security becomes one of the most
important issues. This brings the need to develop IPv4 into
IPv6 in order to proceed towards increasing the network
capacity.
Now Intruders are considered as one of the most serious
threats to the internet security. Data mining techniques have
been successfully utilized in many applications. Many
research projects have applied data mining techniques to
intrusion detection. Furthermore different types of data
mining algorithms are very much useful to intrusion detection
such as Classification, Link Analysis and Sequence Analysis.
Moreover, one of the major challenges in securing fast
networks is the online detection of suspicious anomalies in
network traffic pattern. Most of the current security solutions
failed to perform the security task in online mode because of
the time needed to capture the packets and making decision
about it.
Practically, this study provides alliterative survey for the
enhancement associated with IPv6 in terms of its security
related functions. It is worthy mentioned that this study is
concurred with the data mining approaches that have been
used to detect intrusions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this research work an Intrusion Detection System (IDS) and Intrusion Prevention System (IPS) will be implemented to detect and prevent critical networks infrastructure from cyber-attacks. To strengthen network security and improve the network's active defense intrusion detection capabilities, this project will consist of intrusion detection system using honey token based encrypted pointers and intrusion prevention system which based on the mixed interactive honeypot. The Intrusion Detection System (IDS) is based on the novel approach of Honey Token based Encrypted Pointers.
This document proposes a novel method to defend against IP spoofing attacks using packet filtering and marking techniques. It involves a network architecture model with trusted nodes that can access each other after authentication. The proposed method uses packet tracing and cooperation between trusted adjacent nodes to detect and block spoofed packets entering the trusted network from external sources. It aims to effectively defend against distributed denial of service attacks and IP spoofing attacks.
Denial of Service Attack Defense TechniquesIRJET Journal
This document discusses denial of service (DoS) attacks and defense techniques. It begins by defining DoS attacks and describing common types like SYN floods, teardrop attacks, and ICMP floods. It then discusses various defense techniques including intrusion detection systems, intrusion prevention systems, and packet filtering firewalls. It compares the advantages and disadvantages of these different techniques. In conclusion, the document reviews that various techniques can be used to detect and prevent DoS attacks, with no single best approach, and defense requires a layered approach using multiple techniques.
This document discusses network security and cryptography. It begins by describing modern organizational networks and their vulnerabilities. It then discusses physical networks, wired and wireless networks, and common network vulnerabilities and attacks. The document outlines goals of network security including confidentiality, integrity and availability. It describes security mechanisms at different networking layers and protocols for securing email communication, DNS, and web traffic. The key points are that network security aims to protect data in transit, vulnerabilities exist at various layers, and different security protocols operate at the application, transport and network layers to provide encryption, authentication and integrity for common network services.
Intrusion Detection Systems By Anamoly-Based Using Neural NetworkIOSR Journals
To improve network security different steps has been taken as size and importance of the network has
increases day by day. Then chances of a network attacks increases Network is mainly attacked by some
intrusions that are identified by network intrusion detection system. These intrusions are mainly present in data
packets and each packet has to scan for its detection. This paper works to develop a intrusion detection system
which utilizes the identity and signature of the intrusion for identifying different kinds of intrusions. As network
intrusion detection system need to be efficient enough that chance of false alarm generation should be less,
which means identifying as a intrusion but actually it is not an intrusion. Result obtained after analyzing this
system is quite good enough that nearly 90% of true alarms are generated. It detect intrusion for various
services like Dos, SSH, etc by neural network
As cyberattacks grow in volume and complexity, artificial intelligence (AI) is helping under-resourced security operations analysts stay ahead of threats. Curating threat intelligence from millions of research papers, blogs and news stories, AI technologies like machine learning and natural language processing provide rapid insights to cut through the noise of daily alerts, drastically reducing response
This document summarizes the key aspects of computer network security. It discusses the importance of network security due to increased interconnectivity and risk of intellectual property theft. It describes common internet attack methods like viruses, Trojans, eavesdropping and denial of service attacks. It also discusses network security technologies used to defend against attacks, such as firewalls, encryption, intrusion detection systems. The document outlines security considerations for network design like access control, authentication, integrity and non-repudiation. It examines vulnerabilities in the internet architecture and security issues in different versions of the internet protocol. Finally, it discusses future directions for network security.
Passive monitoring to build Situational AwarenessDavid Sweigert
Passive network monitoring techniques can provide valuable situational awareness for network security professionals. The document describes techniques for passively discovering information about nodes on a network, including operating systems, roles, services, and configurations. This contextual information helps analysts by reducing false positives and focusing resources. The passive approach does not disrupt networks and can operate continuously, in contrast to active scanning tools. A network monitoring prototype is being developed to test these passive discovery techniques.
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...IJCNCJournal
After tightening up network perimeter for dealing with external threats, organizations have woken up to the
threats from inside Local Area Networks (LAN) over the past several years. It is thus important to design
and implement LAN security strategies in order to secure assets on LAN by filtering traffic and thereby
protecting them from malicious access and insider attacks. Banking Financial Services and Insurance
(BFSI) industry is one such segment that faces increased risks and security challenges. The typical
architecture of this segment includes several thousands of users connecting from various branches over
Wide Area Network (WAN) links crossing national and international boundaries with varying network
speed to access data center resources. The objective of this work is to deploy LAN security solution to
protect the data center located at headquarters from the end user machines. A LAN security solution should
ideally provide Network Access Control (NAC) along with cleaning (securing) the traffic going through it.
Traffic cleaning itself includes various features like firewall, intrusion detection/prevention, traffic anomaly
detection, validation of asset ownership etc. LANenforcer (LE) is a device deployed in front of the data
center such that the traffic from end-user machines necessarily passes through it so that it can enforce
security. The goal of this system is to enhance the security features of a LANenforcer security system with
Intrusion Prevention System (IPS) to enable it to detect and prevent malicious network activities. IPS is
plugged into the packet path based on the configuration in such a way that the entire traffic passes through
the IPS on LE.
Network security involves protecting computer networks and systems from unauthorized access, theft of or damage to hardware, software or electronic data. The chapter discusses network security basics, threats like cyberattacks and phishing, vulnerabilities from weaknesses in TCP/IP protocols and buffer overflows. It also covers network security protocols like IPsec, SSL/TLS, and wireless encryption methods like WEP, WPA, and WPA2 that are used to secure wireless networks and encrypt data transmitted over them. Administrative, technical and physical controls help defend networks against various security risks and assure network integrity and safety.
This document provides summaries of 7 IEEE papers from 2012 related to software projects in various domains such as Java, J2ME, J2EE, .NET, MATLAB and NS2. The papers discuss topics such as password security, data provenance, trust-aware routing in wireless sensor networks, content distribution via network coding, detecting insider threats, secure message passing interfaces, and the security of an anonymity system with traceability.
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMSIJNSA Journal
Nowadays, corporations and a government agencies relay on computer-based information system to
manage their information, this information may be classified, so it will be dangerous if it is disclosed by
unauthorized persons. Therefore, there is urgent need for defense. In this research, defense has been
categorized into four mechanisms technical defense, operation defense, management defense, and physical
defense based on the logic of computer and network security. Also, each mechanism has been investigated
and explained in the term of computer based information systems.
Optimized Intrusion Detection System using Deep Learning Algorithmijtsrd
A method and a system for the detection of an intrusion in a computer network compare the network traffic of the computer network at multiple different points in the network. In an uncompromised network the network traffic monitored at these two different points in the network should be identical. A network intrusion detection system is mostly place at strategic points in a network, so that it can monitor the traffic traveling to or from different devices on that network. The existing Software Defined Network SDN proposes the separation of forward and control planes by introducing a new independent plane called network controller. Machine learning is an artificial intelligence approach that focuses on acquiring knowledge from raw data and, based at least in part on the identified flow, selectively causing the packet, or a packet descriptor associated with the packet. The performance is evaluated using the network analysis metrics such as key generation delay, key sharing delay and the hash code generation time for both SDN and the proposed machine learning SDN. Prof P. Damodharan | K. Veena | Dr N. Suguna "Optimized Intrusion Detection System using Deep Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21447.pdf
Paper URL: https://www.ijtsrd.com/engineering/other/21447/optimized-intrusion-detection-system-using-deep-learning-algorithm/prof-p-damodharan
International Journal of Computer Science and Security Volume (1) Issue (3)CSCJournals
The document discusses integrating VPN and IDS technologies to improve network security. It proposes configuring a VPN concentrator/firewall to encrypt traffic between remote clients and private networks. An IDS would be placed within the private network to monitor decrypted traffic. Rules would define the IDS monitoring encrypted VPN traffic and taking action on detected threats. The integration aims to address issues like switched and encrypted data evading traditional network IDS, while reducing false alarms through traffic correlation. Configuration rules specify interfaces, address pools, VPN/firewall settings, and IDS login to dynamically update firewall rules.
This document discusses network intrusion detection systems (NIDS) and their ability to handle high-speed traffic. It introduces NIDS and their role in monitoring network traffic. The document presents an experiment that tests the open-source NIDS Snort under high-volume traffic. The experiment shows that Snort drops more packets as traffic speed and volume increases, demonstrating a weakness of NIDS in high-speed environments. It suggests using a parallel NIDS technique to help NIDS better handle high-speed network traffic and reduce packet dropping.
Network security refers to protecting computer networks from unauthorized access and system threats. Effective network security implements measures like firewalls, encryption, and user authentication to restrict access and ensure confidentiality, integrity, and availability of network resources. As networks and threats evolve, network security requires an adaptive, layered approach using tools like antivirus software, intrusion detection, and biometrics alongside continued software and hardware advances.
NETWORK INTRUSION DETECTION AND COUNTERMEASURE SELECTION IN VIRTUAL NETWORK (...ijsptm
Intrusion in a network or a system is a problem today as the trend of successful network attacks continue to
rise. Intruders can explore vulnerabilities of a network system to gain access in order to deploy some virus
or malware such as Denial of Service (DOS) attack. In this work, a frequency-based Intrusion Detection
System (IDS) is proposed to detect DOS attack. The frequency data is extracted from the time-series data
created by the traffic flow using Discrete Fourier Transform (DFT). An algorithm is developed for
anomaly-based intrusion detection with fewer false alarms which further detect known and unknown attack
signature in a network. The frequency of the traffic data of the virus or malware would be inconsistent with
the frequency of the legitimate traffic data. A Centralized Traffic Analyzer Intrusion Detection System
called CTA-IDS is introduced to further detect inside attackers in a network. The strategy is effective in
detecting abnormal content in the traffic data during information passing from one node to another and
also detects known attack signature and unknown attack. This approach is tested by running the artificial
network intrusion data in simulated networks using the Network Simulator2 (NS2) software.
Network Intrusion Detection And Countermeasure Selection In Virtual Network (...ClaraZara1
Intrusion in a network or a system is a problem today as the trend of successful network attacks continue to rise. Intruders can explore vulnerabilities of a network system to gain access in order to deploy some virus or malware such as Denial of Service (DOS) attack. In this work, a frequency-based Intrusion Detection System (IDS) is proposed to detect DOS attack. The frequency data is extracted from the time-series data created by the traffic flow using Discrete Fourier Transform (DFT). An algorithm is developed for anomaly-based intrusion detection with fewer false alarms which further detect known and unknown attack signature in a network. The frequency of the traffic data of the virus or malware would be inconsistent with the frequency of the legitimate traffic data. A Centralized Traffic Analyzer Intrusion Detection System called CTA-IDS is introduced to further detect inside attackers in a network. The strategy is effective in detecting abnormal content in the traffic data during information passing from one node to another and also detects known attack signature and unknown attack. This approach is tested by running the artificial network intrusion data in simulated networks using the Network Simulator2 (NS2) software.
A honeynet framework to promote enterprise network securityIAEME Publication
This document describes a honeynet framework to promote enterprise network security. The framework consists of two high-interaction honeypot servers connected by a switch to a monitoring station. The honeypots provide real operating systems and services to attract attackers. When an attacker attempts to access a honeypot, its data is captured by a packet sniffer and stored in a database. This data is then sent securely to the monitoring station using web services. The monitoring station analyzes the data, generates an alert report, and provides a GUI to monitor extracted information. The goal is to identify attack traffic and profile attackers to improve network defense.
An enhanced ip traceback mechanism for tracking the attack source using packe...IAEME Publication
The document discusses an enhanced IP traceback mechanism (EITM) to more efficiently trace the source of distributed denial of service (DDoS) attacks. EITM aims to reduce the number of packets required for traceback by improving existing linear and remainder packet marking schemes. It analyzes challenges in tracing attackers due to the stateless nature of the internet and proposes that an effective traceback scheme minimizes required packets. The main goal is a mechanism that needs a number of packets almost equal to the number of hops to reconstruct the attack path more efficiently.
Similar to Layered Approach for Preprocessing of Data in Intrusion Prevention Systems (20)
Text Mining in Digital Libraries using OKAPI BM25 ModelEditor IJCATR
The emergence of the internet has made vast amounts of information available and easily accessible online. As a result, most libraries have digitized their content in order to remain relevant to their users and to keep pace with the advancement of the internet. However, these digital libraries have been criticized for using inefficient information retrieval models that do not perform relevance ranking to the retrieved results. This paper proposed the use of OKAPI BM25 model in text mining so as means of improving relevance ranking of digital libraries. Okapi BM25 model was selected because it is a probability-based relevance ranking algorithm. A case study research was conducted and the model design was based on information retrieval processes. The performance of Boolean, vector space, and Okapi BM25 models was compared for data retrieval. Relevant ranked documents were retrieved and displayed at the OPAC framework search page. The results revealed that Okapi BM 25 outperformed Boolean model and Vector Space model. Therefore, this paper proposes the use of Okapi BM25 model to reward terms according to their relative frequencies in a document so as to improve the performance of text mining in digital libraries.
Green Computing, eco trends, climate change, e-waste and eco-friendlyEditor IJCATR
This document discusses green computing practices and sustainable IT services. It provides an overview of factors driving adoption of green computing to reduce costs and environmental impact of data centers, such as rising energy costs and density. Green strategies discussed include improving infrastructure efficiency, power management, thermal management, efficient product design, and virtualization to optimize resource utilization. The document examines how green computing aims to lower costs and environmental footprint, and how sustainable IT services take a broader approach considering economic, environmental and social impacts.
Policies for Green Computing and E-Waste in NigeriaEditor IJCATR
Computers today are an integral part of individuals’ lives all around the world, but unfortunately these devices are toxic to the environment given the materials used, their limited battery life and technological obsolescence. Individuals are concerned about the hazardous materials ever present in computers, even if the importance of various attributes differs, and that a more environment -friendly attitude can be obtained through exposure to educational materials. In this paper, we aim to delineate the problem of e-waste in Nigeria and highlight a series of measures and the advantage they herald for our country and propose a series of action steps to develop in these areas further. It is possible for Nigeria to have an immediate economic stimulus and job creation while moving quickly to abide by the requirements of climate change legislation and energy efficiency directives. The costs of implementing energy efficiency and renewable energy measures are minimal as they are not cash expenditures but rather investments paid back by future, continuous energy savings.
Performance Evaluation of VANETs for Evaluating Node Stability in Dynamic Sce...Editor IJCATR
Vehicular ad hoc networks (VANETs) are a favorable area of exploration which empowers the interconnection amid the movable vehicles and between transportable units (vehicles) and road side units (RSU). In Vehicular Ad Hoc Networks (VANETs), mobile vehicles can be organized into assemblage to promote interconnection links. The assemblage arrangement according to dimensions and geographical extend has serious influence on attribute of interaction .Vehicular ad hoc networks (VANETs) are subclass of mobile Ad-hoc network involving more complex mobility patterns. Because of mobility the topology changes very frequently. This raises a number of technical challenges including the stability of the network .There is a need for assemblage configuration leading to more stable realistic network. The paper provides investigation of various simulation scenarios in which cluster using k-means algorithm are generated and their numbers are varied to find the more stable configuration in real scenario of road.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Analysis of Comparison of Fuzzy Knn, C4.5 Algorithm, and Naïve Bayes Classifi...Editor IJCATR
Early detection of diabetes mellitus (DM) can prevent or inhibit complication. There are several laboratory test that must be done to detect DM. The result of this laboratory test then converted into data training. Data training used in this study generated from UCI Pima Database with 6 attributes that were used to classify positive or negative diabetes. There are various classification methods that are commonly used, and in this study three of them were compared, which were fuzzy KNN, C4.5 algorithm and Naïve Bayes Classifier (NBC) with one identical case. The objective of this study was to create software to classify DM using tested methods and compared the three methods based on accuracy, precision, and recall. The results showed that the best method was Fuzzy KNN with average and maximum accuracy reached 96% and 98%, respectively. In second place, NBC method had respective average and maximum accuracy of 87.5% and 90%. Lastly, C4.5 algorithm had average and maximum accuracy of 79.5% and 86%, respectively.
Web Scraping for Estimating new Record from Source SiteEditor IJCATR
Study in the Competitive field of Intelligent, and studies in the field of Web Scraping, have a symbiotic relationship mutualism. In the information age today, the website serves as a main source. The research focus is on how to get data from websites and how to slow down the intensity of the download. The problem that arises is the website sources are autonomous so that vulnerable changes the structure of the content at any time. The next problem is the system intrusion detection snort installed on the server to detect bot crawler. So the researchers propose the use of the methods of Mining Data Records and the method of Exponential Smoothing so that adaptive to changes in the structure of the content and do a browse or fetch automatically follow the pattern of the occurrences of the news. The results of the tests, with the threshold 0.3 for MDR and similarity threshold score 0.65 for STM, using recall and precision values produce f-measure average 92.6%. While the results of the tests of the exponential estimation smoothing using ? = 0.5 produces MAE 18.2 datarecord duplicate. It slowed down to 3.6 datarecord from 21.8 datarecord results schedule download/fetch fix in an average time of occurrence news.
Evaluating Semantic Similarity between Biomedical Concepts/Classes through S...Editor IJCATR
Most of the existing semantic similarity measures that use ontology structure as their primary source can measure semantic similarity between concepts/classes using single ontology. The ontology-based semantic similarity techniques such as structure-based semantic similarity techniques (Path Length Measure, Wu and Palmer’s Measure, and Leacock and Chodorow’s measure), information content-based similarity techniques (Resnik’s measure, Lin’s measure), and biomedical domain ontology techniques (Al-Mubaid and Nguyen’s measure (SimDist)) were evaluated relative to human experts’ ratings, and compared on sets of concepts using the ICD-10 “V1.0” terminology within the UMLS. The experimental results validate the efficiency of the SemDist technique in single ontology, and demonstrate that SemDist semantic similarity techniques, compared with the existing techniques, gives the best overall results of correlation with experts’ ratings.
Semantic Similarity Measures between Terms in the Biomedical Domain within f...Editor IJCATR
The techniques and tests are tools used to define how measure the goodness of ontology or its resources. The similarity between biomedical classes/concepts is an important task for the biomedical information extraction and knowledge discovery. However, most of the semantic similarity techniques can be adopted to be used in the biomedical domain (UMLS). Many experiments have been conducted to check the applicability of these measures. In this paper, we investigate to measure semantic similarity between two terms within single ontology or multiple ontologies in ICD-10 “V1.0” as primary source, and compare my results to human experts score by correlation coefficient.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Integrated System for Vehicle Clearance and RegistrationEditor IJCATR
Efficient management and control of government's cash resources rely on government banking arrangements. Nigeria, like many low income countries, employed fragmented systems in handling government receipts and payments. Later in 2016, Nigeria implemented a unified structure as recommended by the IMF, where all government funds are collected in one account would reduce borrowing costs, extend credit and improve government's fiscal policy among other benefits to government. This situation motivated us to embark on this research to design and implement an integrated system for vehicle clearance and registration. This system complies with the new Treasury Single Account policy to enable proper interaction and collaboration among five different level agencies (NCS, FRSC, SBIR, VIO and NPF) saddled with vehicular administration and activities in Nigeria. Since the system is web based, Object Oriented Hypermedia Design Methodology (OOHDM) is used. Tools such as Php, JavaScript, css, html, AJAX and other web development technologies were used. The result is a web based system that gives proper information about a vehicle starting from the exact date of importation to registration and renewal of licensing. Vehicle owner information, custom duty information, plate number registration details, etc. will also be efficiently retrieved from the system by any of the agencies without contacting the other agency at any point in time. Also number plate will no longer be the only means of vehicle identification as it is presently the case in Nigeria, because the unified system will automatically generate and assigned a Unique Vehicle Identification Pin Number (UVIPN) on payment of duty in the system to the vehicle and the UVIPN will be linked to the various agencies in the management information system.
Assessment of the Efficiency of Customer Order Management System: A Case Stu...Editor IJCATR
The Supermarket Management System deals with the automation of buying and selling of good and services. It includes both sales and purchase of items. The project Supermarket Management System is to be developed with the objective of making the system reliable, easier, fast, and more informative.
Energy-Aware Routing in Wireless Sensor Network Using Modified Bi-Directional A*Editor IJCATR
Energy is a key component in the Wireless Sensor Network (WSN)[1]. The system will not be able to run according to its function without the availability of adequate power units. One of the characteristics of wireless sensor network is Limitation energy[2]. A lot of research has been done to develop strategies to overcome this problem. One of them is clustering technique. The popular clustering technique is Low Energy Adaptive Clustering Hierarchy (LEACH)[3]. In LEACH, clustering techniques are used to determine Cluster Head (CH), which will then be assigned to forward packets to Base Station (BS). In this research, we propose other clustering techniques, which utilize the Social Network Analysis approach theory of Betweeness Centrality (BC) which will then be implemented in the Setup phase. While in the Steady-State phase, one of the heuristic searching algorithms, Modified Bi-Directional A* (MBDA *) is implemented. The experiment was performed deploy 100 nodes statically in the 100x100 area, with one Base Station at coordinates (50,50). To find out the reliability of the system, the experiment to do in 5000 rounds. The performance of the designed routing protocol strategy will be tested based on network lifetime, throughput, and residual energy. The results show that BC-MBDA * is better than LEACH. This is influenced by the ways of working LEACH in determining the CH that is dynamic, which is always changing in every data transmission process. This will result in the use of energy, because they always doing any computation to determine CH in every transmission process. In contrast to BC-MBDA *, CH is statically determined, so it can decrease energy usage.
Security in Software Defined Networks (SDN): Challenges and Research Opportun...Editor IJCATR
In networks, the rapidly changing traffic patterns of search engines, Internet of Things (IoT) devices, Big Data and data centers has thrown up new challenges for legacy; existing networks; and prompted the need for a more intelligent and innovative way to dynamically manage traffic and allocate limited network resources. Software Defined Network (SDN) which decouples the control plane from the data plane through network vitalizations aims to address these challenges. This paper has explored the SDN architecture and its implementation with the OpenFlow protocol. It has also assessed some of its benefits over traditional network architectures, security concerns and how it can be addressed in future research and related works in emerging economies such as Nigeria.
Measure the Similarity of Complaint Document Using Cosine Similarity Based on...Editor IJCATR
Report handling on "LAPOR!" (Laporan, Aspirasi dan Pengaduan Online Rakyat) system depending on the system administrator who manually reads every incoming report [3]. Read manually can lead to errors in handling complaints [4] if the data flow is huge and grows rapidly, it needs at least three days to prepare a confirmation and it sensitive to inconsistencies [3]. In this study, the authors propose a model that can measure the identities of the Query (Incoming) with Document (Archive). The authors employed Class-Based Indexing term weighting scheme, and Cosine Similarities to analyse document similarities. CoSimTFIDF, CoSimTFICF and CoSimTFIDFICF values used in classification as feature for K-Nearest Neighbour (K-NN) classifier. The optimum result evaluation is pre-processing employ 75% of training data ratio and 25% of test data with CoSimTFIDF feature. It deliver a high accuracy 84%. The k = 5 value obtain high accuracy 84.12%
Hangul Recognition Using Support Vector MachineEditor IJCATR
The recognition of Hangul Image is more difficult compared with that of Latin. It could be recognized from the structural arrangement. Hangul is arranged from two dimensions while Latin is only from the left to the right. The current research creates a system to convert Hangul image into Latin text in order to use it as a learning material on reading Hangul. In general, image recognition system is divided into three steps. The first step is preprocessing, which includes binarization, segmentation through connected component-labeling method, and thinning with Zhang Suen to decrease some pattern information. The second is receiving the feature from every single image, whose identification process is done through chain code method. The third is recognizing the process using Support Vector Machine (SVM) with some kernels. It works through letter image and Hangul word recognition. It consists of 34 letters, each of which has 15 different patterns. The whole patterns are 510, divided into 3 data scenarios. The highest result achieved is 94,7% using SVM kernel polynomial and radial basis function. The level of recognition result is influenced by many trained data. Whilst the recognition process of Hangul word applies to the type 2 Hangul word with 6 different patterns. The difference of these patterns appears from the change of the font type. The chosen fonts for data training are such as Batang, Dotum, Gaeul, Gulim, Malgun Gothic. Arial Unicode MS is used to test the data. The lowest accuracy is achieved through the use of SVM kernel radial basis function, which is 69%. The same result, 72 %, is given by the SVM kernel linear and polynomial.
Application of 3D Printing in EducationEditor IJCATR
This paper provides a review of literature concerning the application of 3D printing in the education system. The review identifies that 3D Printing is being applied across the Educational levels [1] as well as in Libraries, Laboratories, and Distance education systems. The review also finds that 3D Printing is being used to teach both students and trainers about 3D Printing and to develop 3D Printing skills.
Survey on Energy-Efficient Routing Algorithms for Underwater Wireless Sensor ...Editor IJCATR
In underwater environment, for retrieval of information the routing mechanism is used. In routing mechanism there are three to four types of nodes are used, one is sink node which is deployed on the water surface and can collect the information, courier/super/AUV or dolphin powerful nodes are deployed in the middle of the water for forwarding the packets, ordinary nodes are also forwarder nodes which can be deployed from bottom to surface of the water and source nodes are deployed at the seabed which can extract the valuable information from the bottom of the sea. In underwater environment the battery power of the nodes is limited and that power can be enhanced through better selection of the routing algorithm. This paper focuses the energy-efficient routing algorithms for their routing mechanisms to prolong the battery power of the nodes. This paper also focuses the performance analysis of the energy-efficient algorithms under which we can examine the better performance of the route selection mechanism which can prolong the battery power of the node
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Decay Property for Solutions to Plate Type Equations with Variable CoefficientsEditor IJCATR
In this paper we consider the initial value problem for a plate type equation with variable coefficients and memory in
1 n R n ), which is of regularity-loss property. By using spectrally resolution, we study the pointwise estimates in the spectral
space of the fundamental solution to the corresponding linear problem. Appealing to this pointwise estimates, we obtain the global
existence and the decay estimates of solutions to the semilinear problem by employing the fixed point theorem
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Zilliz
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
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See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
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- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
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BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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Layered Approach for Preprocessing of Data in Intrusion Prevention Systems
1. International Journal of Computer Applications Technology and Research
Volume 3– Issue 6, 364 - 369, 2014
www.ijcat.com 364
Layered Approach for Preprocessing of Data in Intrusion
Prevention Systems
Kamini Nalavade
Department of Computer Engineering,
VJTI, Matunga, Mumbai,
India
Dr. B. B. Meshram
Department ofComputer Engineering
VJTI, Matunga, Mumbai,
India
Abstract: Due to extensive growth of the Internet and increasing availability of tools and methods for intruding and attacking
networks, intrusion detection has become a critical component of network security parameters. TCP/IP protocol suite is the defacto
standard for communication on the Internet. The underlying vulnerabilities in the protocols is the root cause of intrusions. Therefor
Intrusion detection system becomes an important element in network security that controls real time data and leads to huge
dimensional problem. Processing large number of packets and data in real time is very difficult and costly. Therefor data pre-
processing is necessary to remove redundant and unwanted information from packets and clean network data. Here, we are focusing on
two important aspects of intrusion detection; one is accuracy and other is performance. The layered approach of TCP/IP model can be
applied to packet pre-processing to achieve early and faster intrusion detection. Motivation for the paper comes from the large impact
data preprocessing has on the accuracy and capability of anomaly-based NIPS. In this paper it is demonstrated that high attack
detection accuracy can be achieved by using layered approach for data preprocessing in Internet. To reduce false positive rate and to
increase efficiency of detection, the paper proposed framework for preprocessing in intrusion prevention system. We experimented
with real time network traffic as well as he KDDcup99 dataset for our research.
Keywords: Intrusion, Security, Network, Layered approach
1. INTRODUCTION
The continuous improvements in technology have made the
use of computers easy for gathering and sharing information
using the Internet. The Transmission Control Protocol and
Internet protocol suite (TCP/IP) is the de-facto standard for
using the internet. Due to a number of reported attacks on
networks originating from the Internet, security has become a
primary concern for organizations connecting to the Internet.
The Information ow on Internet is constantly under various
attacks because of vulnerabilities lying in the structure of
networks. Therefore it is essential to provide security to the
information in transit. The secure connection itself must be
established and maintained securely. The Transmission
Control Protocol and Internet protocol (TCP/IP), which is the
protocol suite that Internet was first developed in 1979. The
primary focus was to ensure reliable communications between
groups of networks connected by computers. At that time,
security was not a primary concern as the users of the Internet
were less. The information flow on Internet is constantly
under various attacks. The root cause of these exploits is
weaknesses in the protocols of underlying TCP/IP protocol
suite.
Figure 1 TCP/IP model
The TCP/IP protocol suite suffers from a number of
vulnerabilities and security flaws inherent in the protocols.
Those vulnerabilities are often exploited by attackers for
session hijacking, sniffing, spoofing, Denial of Service (DOS)
attacks and other attacks. The key vulnerability in most of the
protocols of TCP/IP is lack of authentication mechanisms.
This is the severe flaw which enables attacker to access the
confidential information. The IP layer believes that the source
address on any IP packet it receives is the same IP address as
the system that actually sent the packet. The other
vulnerability is connectionless communication between peers.
IP layer does not ensure that a packet will reach its final
destination. Also it does not guarantee that packets forwarded
on network will arrive in the order. The following are the
major TCP security problems. A malicious host can exhaust
the server‟s buffer by sending several SYN requests to a host,
but never replying to the SYN & ACK the other host sends
back. By doing so server will stop accepting new connections,
until a partially opened connection in its queue is completed
or times out. This ability to effectively remove a server from
the network can be used as a denial-of-service attack. It can be
used to implement other attacks, like IP Spoofing,
reconnaissance.
RIP, OSPF and BGP are the widely used de facto standard of
routing protocols on the Internet. These protocols suffer from
major vulnerabilities which causes attacks on network such as
denial of service, invalid route information. Routing attacks
takes advantage of Routing Information Protocol (RIP), which
is an essential component in a TCP/IP network. RIP is used to
distribute routing information within networks and advertising
routes out from the local network. RIP has no inbuilt
authentication, and the information provided in a RIP packet
is often used without verifying it. RIP's update messages are
sent over UDP and can be modified by attackers. Attacks on
RIP change the destination where data goes to, not where it
came from. For example, an invader could forge a RIP packet,
claiming his host "B" has the fastest path out of the network.
2. International Journal of Computer Applications Technology and Research
Volume 3– Issue 6, 364 - 369, 2014
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All packets sent out from that network would then be routed
through B, where they could be modified or scanned. An
invader could also use RIP to effectively impersonate any
host, by causing all traffic sent to that host to be sent to the
attacker's machine instead. RIP, OSPF and BGP were studied
with respect to their architecture, functionality and message
types. OSPF suffers from implementation and configuration
problems. BGP have vulnerabilities related confidentiality,
integrity and authentication. This study provides immense
help in describing security architecture for routing protocols.
Security protocols are the addition to the basic protocol set of
TCP/IP suite to overcome the vulnerabilities lying in the
design of these protocols. Security Protocols such IPSec,
DNSSec, SSL, SSH, TLS are also prone to attacks such as
DOS, spoofing, flooding etc. Attack detection in security
protocols is crucial task. DNSSEC does not guard against
poor configuration or bad information in the authoritative
name server, and does not protect against buffer overruns or
DDoS attacks. Small queries can generate larger UDP packets
in response. DNSSEC has a hierarchical trust model. To
securely resolve a name in DNSSEC, a root public key must
be available at the resolver. The IPSEC protocols rely on a
number of underlying technologies to achieve encryption and
authentication. Specific SSH versions and implementations
have been vulnerable to brute force attack.
In our research work we aim to develop an Intrusion
Protection Systems which detects broad range of attacks along
with reducing false alarms and increasing attack detection
accuracy. During our research work we explored many of the
vulnerabilities of these protocols and defense mechanisms for
this. Although many defense techniques are the configuration
based. The paper is organized as below. In section II we
provide a brief overview of Intrusion Prevention Sytems. In
section III Layered approach for intrusion detection is
discussed. In Section IV Experimentation and results
generated for our system is discussed followed by conclusion.
2. INTRUSION PREVENTION SYSTEM
Intrusion detection as defined by the Sysadmin, Audit,
Networking, and Security (SANS) institute is the act of
detecting activities that attempt to negotiate the
confidentiality, integrity or availability of a resource [2].
Current network systems provide critical services for
businesses to perform optimally and are target of attacks
which aim to bring down the services provided by the
network.
An Intrusion detection system (IDS) is software designed to
detect unwanted attempts at accessing, manipulating, or
disabling of computer systems, especially through a network.
It is a specialized tool that knows how to parse and interpret
network traffic and host activities. IDS technologies are not
really effective against prediction a new attacks. There are
several limitations, such as performance, flexibility, and
scalability. The inadequacies inherent in current defenses
have driven the development of a new breed of security
products known as Intrusion Prevention Systems (IPS).
Intrusion Prevention System (IPS) is a new approach system
to defense networking systems, which combine the technique
firewall with that of the Intrusion Detection properly, which is
proactive technique, prevent the attacks from entering the
network by examining various data record and detection
demeanor of pattern recognition sensor, when an attack is
identified, intrusion prevention block and log the offending
data IPS make access control decisions based on application
content, rather than IP address or ports as traditional firewalls
had done. These systems are proactive defenses mechanisms
designed to detect malicious packets within normal network
traffic and stop intrusions dead, blocking the offending traffic
automatically before it does any damage rather than simply
raising an alert as, or after, the malicious payload has been
delivered IPS use several response techniques. The
comparison of IDS and IPS is shown in figure 2.[16]
Figure 2 Comparison of IDS and IPS
Approaches to Intrusion Prevention Systems: There are
different types of approaches is used in the IPS to secure the
network.[14]
1. Signature-Based IPS: - It is commonly used by
many IPS solutions. Signatures are added to the devices that
identify a pattern that the most common attacks present.
That‟s why it is also known as pattern matching. These
signatures can be added, tuned, and updated to deal with the
new attacks.
2. Anomaly-Based IPS: - It is also called as profile-
based. It attempts to discover activity that deviates from what
an engineer defines as normal activity. Anomaly-based
approach can be statistical anomaly detection and non-
statistical anomaly detection.
3. Policy-Based IPS: - It is more concerned with
enforcing the security policy of the organization. Alarms are
triggered if activities are detected that violate the security
policy coded by the organization. With this type approaches
security policy is written into the IPS device.
4. Protocol-Analysis-Based IPS - It is similar to signature
based approach. Most signatures examine common settings,
but the protocol-analysis-based approach can do much deeper
packet inspection and is more flexible in finding some types
of attacks.
IPS technologies: Basically IPS Host based and network-
based.
3. International Journal of Computer Applications Technology and Research
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1) Host-based IPS: Host-based IPSs [13] monitors the
characteristics of a single host and the events occurring within
that host for suspicious activity. Examples of the types of
characteristics a host-based IPS might monitor are wired and
wireless network traffic, system logs, running processes, file
access and modification, and system and application
configuration changes. Most host-based IPSs have detection
software known as agents installed on the hosts of interest.
Each agent monitors activity on a single host and also
performs prevention actions. The agents transmit data to
management servers. Each agent is typically designed to
protect a server, a desktop or laptop, or an application service.
The agents are deployed to existing hosts on the networks, the
components usually communicate over those networks instead
of using a management network. Host-based IPSs run sensors
on the hosts being monitored, they can impact host
performance because of the resources the sensors consume.
2) Network-based IPS: A network-based IPS [13] monitors
network traffic for particular network segments or devices and
analyzes network, transport, and application protocols to
identify suspicious activity. Network-based IPS components
are similar to HIPS technologies, except for the sensors. A
network-based IPS sensor monitors and analyzes network
activity on one or more network segments. Sensors are
available in two formats: appliance-based sensors, which are
comprised of specialized hardware and software optimized for
IPS sensor use, and software-only sensors, which can be
installed onto hosts that meet certain specifications.
3. LAYERED APPROACH FOR
INTRUSION DETECTION AND
PREVENTION
Preprocessing is the organization of collected data from
sensors in a particular pattern. This data is then placed in a
structured database format by means of parsing and
reconstructing. The cleansing process is protocol specific as
we need different attributes of packets for intrusion analysis.
If packet is from blacklisted source then system should
discard packet without verifying it. When the packets are
transformed and stored in the respective data stores it triggers
intrusion detection.
Layered-based intrusion detection system gets its
motivation from TCP/IP model, where a number of protocols
are assigned different task at different level. Similar to this
model, the layered intrusion detection system represents a
sequential layered approach. The goal of using a layered
model is to reduce computation and the overall time required
to detect anomalous events. The time required to detect an
intrusive event is significant and can be reduced by
eliminating the communication overhead among different
layers. This can be achieved by making the layers autonomous
and self-sufficient to block an attack without the need of a
central decision maker. Every layer in layered intrusion
detection system framework is trained separately and then
deployed sequentially. We define four layers that correspond
to the four attack groups mentioned in the dataset. They are
interface layer, network layer, transport layer and application
layer. Each layer is then separately trained with a small set of
relevant features. Feature selection or reduction is important
for layered approach and discussed in next section. In order to
make the layers independent, some features may be present in
more than one layer. The layers essentially act as filters that
block any anomalous connection, thereby eliminating the need
of further processing at subsequent layers enabling quick
response to intrusion. The effect of such a sequence of layers
is that the anomalous events are identified and blocked as
soon as they are detected [2].
Data preprocessor is responsible for collecting and
providing the audit data (in a specified form) that will be used
by the next module to make a decision. Data preprocessor is,
thus, concerned with collecting the data from the desired
source and converting it into a format that is understandable
by the intrusion detector. Data used for detecting intrusions
range from user access patterns to network packet level
features such as the source and destination IP addresses, type
of packets . We refer to this data as the audit patterns.
Figure 3 Preprocessing of Data
In the proposed model we have used four major
functionalities in preprocessing module as shown in figure 2.
Two different datasets are used for our experiments. Some
experiments are carried out on real time network audit trails
collected over high speed network. Often Intrusion Detection
Systems are loaded with huge amount of data to be processed.
Processing this enormous amount of data in real-time is major
challenge faced in this area. Reduction in input data rate will
provide additional time to detection engine for thoroughly
process data and give more detection accuracy with less false
positive. In the first round, input data cleaning by removing
unwanted parameters is performed. Removal of noise and
incomplete data makes the task of intrusion detection faster.
But it also increases overlapping behavior of normal and
intrusion data. Most modern data mining and soft computing
based Intrusion Detection Systems uses data cleaning
techniques to provide quality data to detection engine and in
turn results in improved intrusion detection rate.
Our proposed system uses feature selection and
extraction on KDD cup dataset which is freely available
intrusion dataset. This dataset contains 41 features for
System
Constraint
Check
Data
Cleaning
Feature
Selection
Feature
Extraction
Network
traffic
KDDcup
dataset
4. International Journal of Computer Applications Technology and Research
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intrusion specification. Not all the features available in raw
input dataset are useful for intrusion detection. For detecting
particular category of intrusion, we require only subset of
these features. Removal of forged and duplicate data will help
in reducing false positive rate.
Another reason for false positive is lack of knowledge about
network topology, hosts and services running on the hosts. In
proposed model third functionality is system constraint check
or configuration based processing. Configuration data about
existing network, hosts, and services are stored in a file.
Configuration parameters help in differentiating normal and
intrusion data by providing additional information. Some
portion of overlapping behavior is the challenge for Intrusion
Detection Systems. The data for which Intrusion Detection
System is not sure results in false detection, either false
negative or false positive. Such ambiguity can be reduced by
collecting information from various sources. This again helps
in reducing false positive rate in proposed system. In our
approach, we perform preprocessing based on type of packet.
For proliferation of performance and reducing time factor in
detection, we separate the packets into TCP/IP protocols,
routing protocols and security protocols. Algorithm for
preprocessing is given below
Algorithm: PreprocessPacket(p)
Input: Packet p, System Configuration Constraints List L
Begin
2. Read packet header ψ.
3. Detect Type of Protocol Δ= ψ ->Τ
4. If (ψ ->Τ=TCP/UDP/IP/ICMP/ARP/RARP) Δ = 1. //
To separate the TCP/IP , routing and security protocols.
else if (ψ ->Τ = RIP/ BGP/EGP) Δ=2.
else Δ =3.
5. CleanPacket(Packet, Type) //This method will remove
unnecessary header fields
6. If incomplete/duplicate Packet then discard packet;
7. End
We successful created data records for TCP/IP Packets and
separate log files for the routing and security protocols for our
experimentation. To collect the attack data, both, the web
requests and the data accesses were logged. For the first data
set, we generate 45 different attack sessions with 275 web
requests resulting in 54,390 data requests. Combining the two
together, the unified log has 45 unique attack sessions with
275 event vectors.
For the second dataset we used KDD dataset. Every
record in the KDD 1999 data set symbolizes 41 features
representing a variety of attacks such as the Probe, DoS, R2L
and U2R. However, using all the 41 features for detecting
attacks belonging to all these classes severely affects the
performance of the system and also generates superfluous
rules, resulting in fitting irregularities in the data which can
misguide classification. Hence, we performed feature
selection to effectively detect different classes of attacks. We
now describe our approach for selecting features for every
attack and why some features were chosen over others.
Algorithm: FeatureSelection
Input: Set of 41 features from KDD cup Data Set
Output: Reduced set of features R.
Step 1. Calculate the information gain for each attribute
AiεD using (3).
Step 2. Choose an attribute Ai from D with the maximum
information gain value.
Step 3. Split the data set D into subdatasets {D1,D2, . . .
Dn} depending on the attribute values of Ai where Cj
stands for jth attribute of class C.
Step 4. Find all the attributes whose information gain ratio
> threshold.
Step 5. Store the selected attributes in the set R and output
it.
Step6: End
We tested our algorithm for each category of attack. For every
category, we applied all relevant attributes for that category,
calculated gain for them and generated small subset which
contains most relevant attributes for that category.
4. EXPERIMENTATION & RESULTS
Data preprocessing is major component of our proposed
architecture. We have considered two datasets for our
experimentation as mentioned in previous sections. The first
data is collected over real time network using packet
generators. We have developed a Java program for data
formatting and implementing a layered approach. The
program works as given in algorithm 1. The results achieved
are logged and stored in the database. Three separate tables
for TCP/IP protocols, routing protocols and security protocols
are created. This helps in further analysis of packets. Before
storing the packet info in the database, signatures for the
attack on a specific protocol are searched. This reduces the
time complexity rapidly as there is no need to check with
signatures which are for other protocols.
The other dataset used is KDDcup1999 intrusion
dataset which contains wide variety of intrusions simulated in
network environment to acquire nine weeks of raw TCP dump
data for a local-area network. A connection is a sequence of
TCP packets starting and ending at some well-defined times,
between which data flows to and from a source IP address to a
target IP address. Each connection is labelled as either
normal, or as an attack, with exactly one specific attack type.
It is important to note that the testing data is not from the
same probability distribution as the training data. This makes
the task more realistic. The datasets contains a total of 22
training attack types. There are 41 features for each
connection record that are divided into discrete sets and
continuous sets according to the feature values. It consists of
number of total records 494021. The 22 different types of
network attacks in the KDD99 dataset fall into four main
categories: DOS (Denial of Service), Probe, R2L(Remote to
Local), U2R(user to remote). The attacks in each class are as
shown below:
5. International Journal of Computer Applications Technology and Research
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Table 1: Classes of Attacks
S.N Class Attack Types
1 DOS Back, Land, Neptune,pod, smurf, Teardrop,
2 U2R Buffer_overflow, loadmodule, perl, rootkit
3 R2L ftp_write, guess_passwd, imap, multihop,
phf, spy,warezlient, warezmaster
4 Probe IPsweep,nmap, satan,portsweep
For intrusion analysis all the 41 features are not required.
Some specific features are only contributing for a specific
attack. This reduces the amount of work for intrusion
detection and increases accuracy. The feature selecion
algorithm is given above in section III. The results we
achieved after applying the algorithm is given below.
Feature Selection from KDD dataset
1. Feature Selection for Probe Layer
Probe attacks are aimed at acquiring information about the
target network from a source that is often external to the
network. For detecting Probe attacks, basic connection level
features such as the „duration of connection‟ and „source
bytes‟ are significant. We selected only four features for
Probe layer. The features selected for detecting Probe attacks
are presented in Table B.1.
Table B.1: Features for Probe Detection
S.N. Name of Feature Feature_No
1 src_bytes 5
2 duration 1
3 protocol_type 2
4 flag 4
2. Feature Selection for DoS Attacks
DoS attacks are meant to prevent the target from providing
service(s) to its users by flooding the network with
illegitimate requests. Hence, to detect attacks at the DoS layer,
network traffic features such as the „percentage of connections
having same destination host and same service‟and packet
level features such as the „duration‟ of a connection, „protocol
type‟, „source bytes‟, „percentage of packets with errors‟ and
others are significant. To detect DoS attacks, it may not be
important to know whether a user is „logged in or not‟, or
whether or not the shell‟ is invoked or „number of files
accessed‟ and, hence, such features are not considered in the
DoS layer. From all the 41 features, we selected only nine
features for the DoS layer.
Table B.2: DoS Layer Features
S.N. Name of Feature Feature_No
1 src_bytes 5
2 duration 1
3 protocol_type 2
4 flag 4
5 count 23
6 dst host same srv rate 34
7 dst host serror rate 38
8 dst host srv serror rate 39
9 dst host rerror rate 40
The features selected for detecting DoS attacks are presented
in Table B.2.
3. Feature Selection for U2R attacks
U2R attacks involve the semantic details which are very
difficult to capture at an early stage at the network level. Such
attacks are often content based and target an application.
Hence, for detecting U2R attacks, we selected features such as
„number of file creations‟, „number of shell prompts invoked‟,
while we ignored features such as „protocol‟ and „source
bytes‟. From all the 41 features, we selected only eight
features for the U2R layer. Features selected for detecting
U2R attacks are presented in Table B.3.
Table B.3: U2R Layer Features
S.N. Name of Feature Feature_
No
1 num_compromised 13
2. root_shell 14
3 num_root 16
4. num_file_creations 17
5 num_shells 18
6 num_access_files 19
7 is_host_logins 21
4. Feature Selection for R2L Attacks
R2L attacks are one of the most difficult attacks to detect and
most of the present systems cannot detect them reliably.
However, our experimental results presented earlier show that
careful feature selection can significantly improve their
detection. We observed that effective detection of the R2L
attacks involve both, the network level and the host level
features. Hence, to detect R2L attacks, we selected both, the
network level features such as the „duration of connection‟,
„service requested‟ and the host level features such as the
„number of failed login attempts‟ among others. Detecting
R2L attacks, require a large number of features and we
selected 14 features. The features selected for detecting R2L
attacks are presented in Table B.4
Table B.4: R2L Layer Features
S.N. Name of Feature Feature_No
1 src_bytes 5
2 duration 1
3 protocol_type 2
4 flag 4
5 num_failed_logins 11
6 num_file_creations 17
7 num_shells 18
8 num_access_files 19
9 is_host_login 21
10 is_guest_login 22
Feature selection is an important task of Network Intrusion
application. Large amount of attacks are threats to network
and information security. Using Feature selection approach
kdd attacks are detected with less error rate and high accuracy.
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5. CONCLUSION
Data preprocessing is widely recognized as an important stage
in anomaly detection. Data preprocessing is found to
predominantly rely on expert domain knowledge for
identifying the most relevant parts of network traffic and for
constructing the initial candidate set of traffic features.
Motivation for the paper comes from the large impact data
preprocessing has on the accuracy and capability of anomaly-
based NIPS. The review finds that many NIPS limit their view
of network traffic to the TCP/IP packet headers. Time-based
statistics can be derived from these headers to detect network
behavior, and denial of service attacks. A number of other
NIPS perform deeper inspection of request packets to detect
attacks against network services and network applications.
On the other hand, automated methods have been widely used
for feature extraction to reduce data dimensionality, and
feature selection to find the most relevant subset of features
from this candidate set. These context sensitive features are
required to detect current attacks. In our proposed system, we
try to evaluate attack at every level of TCP/IP Model by
combining network Intrusion detection and layered approach.
Our preprocessing module has packet capture, feature
selection and storing it in databases. But along with these
basic features it also evaluates known network attacks by
protocol layer wise inbuilt detection algorithm.
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