This document summarizes a survey of distributed denial-of-service (DDoS) attacks based on vulnerabilities in the TCP/IP protocol stack. It begins by introducing DDoS attacks and their architecture, then classifies DDoS attacks according to the TCP/IP layer they target - application layer, transport layer, or internet layer. Specific attack types are described for each layer, including HTTP flooding, SYN flooding, Smurf attacks, and more. The document aims to provide understanding of existing DDoS attack tools, methods, and defense mechanisms.
Preventing Distributed Denial of Service Attacks in Cloud Environments IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of
nodes that interrelate with each other for switch over the information. This information is necessary for
that node is reserved confidentially. Attacker in the system may capture this private information and
distorted. So security is the major issue. There are several security attacks in network. One of the major
intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends
services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two
different behaviors they may happen obviously or it may due to some attackers .Various schemes are
developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
This document proposes a machine learning approach using the Naive Bayes algorithm to detect distributed denial of service (DDoS) attacks through network intrusion detection. It first discusses the issues with existing intrusion detection systems, including long training times and low accuracy. It then summarizes research on applying various machine learning techniques like neural networks, decision trees, and Naive Bayes to intrusion detection. The proposed system would build a classifier using Naive Bayes, which provides faster training than other methods, to distinguish normal and attack traffic. This approach aims to improve upon the training time and detection accuracy of existing intrusion detection systems.
The document discusses denial of service (DoS) and distributed denial of service (DDoS) attacks. It defines DoS and DDoS attacks, describes different types of DoS attacks like SYN flooding and Smurf attacks. It also explains how botnets and tools are used to launch DDoS attacks, and discusses some common DDoS countermeasures like detection, mitigation and traceback.
A ROBUST MECHANISM FOR DEFENDING DISTRIBUTED DENIAL OF SERVICE ATTACKS ON WEB...IJNSA Journal
Distributed Denial of Service (DDoS) attacks have emerged as a popular means of causing mass targeted service disruptions, often for extended periods of time. The relative ease and low costs of launching such attacks, supplemented by the current inadequate sate of any viable defense mechanism, have made them one of the top threats to the Internet community today. Since the increasing popularity of web-based applications has led to several critical services being provided over the Internet, it is imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper first presents a brief discussion on some of the important types of DDoS attacks that currently exist and some existing mechanisms to combat these attacks. It then points out the major drawbacks of the currently existing defense mechanisms and proposes a new mechanism for protecting a web-server against a DDoS attack. In the proposed mechanism, incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. While the detection process is on, the sessions from the legitimate sources are not disrupted and the load on the server is restored to the normal level by blocking the traffic from the attacking sources. To cater to different scenarios, the detection algorithm has various modules with varying level of computational and memory overheads for
their execution. While the approximate modules are fast in detection and involve less overhead, they provide lower level of detection accuracy. The accurate modules employ complex detection logic and hence involve more overhead for their execution. However, they have very high detection accuracy. Simulations carried out on the proposed mechanism have produced results that demonstrate effectiveness of the proposed defense mechanism against DDoS attacks.
The document discusses various common computer network attacks and exploits. It provides descriptions of denial of service attacks, distributed denial of service attacks, backdoors, spoofing, man-in-the-middle attacks, replay attacks, session hijacking, DNS poisoning, password guessing, software exploits, war dialing, war driving, buffer overflows, SYN floods, ICMP floods, UDP floods, smurfing, sniffing, ping of death attacks and more. It also discusses implementing network security through identifying assets, threats, risk assessment, security policies, technical implementation, auditing and continuous improvement.
DDoS attacks target companies and institutions that provide online services. They work by overloading servers with traffic from multiple compromised systems known as "bots" or "zombies". Common DDoS attack types include SMURF, TCP SYN/ACK, UDP flood, DNS amplification, and attacks using peer-to-peer networks. Defenses include configuring routers and firewalls to filter unauthorized traffic, limiting response messages, and tracking malicious activity on peer-to-peer networks. As attack methods evolve, continued development of detection and mitigation techniques is needed.
This document provides an overview of distributed denial of service (DDoS) attacks, including how they work, common techniques used, and strategies for mitigating them. It defines DDoS attacks as attempts to exhaust the resources of networks, applications, or services to deny access to legitimate users. The document discusses how botnets are commonly used to launch large-scale DDoS attacks from multiple sources simultaneously. It also outlines best practices for selecting DDoS protection devices, emphasizing the importance of up-to-date detection techniques, low latency, and customized hardware-based logic to withstand major attacks.
A Comparative Approach to Handle Ddos AttacksIOSR Journals
This document summarizes various types of distributed denial of service (DDoS) attacks and potential countermeasures. It discusses common DDoS attacks like SYN flooding, UDP flooding, ICMP flooding, teardrop attacks, land attacks, and Win Nuke attacks. For each type of attack, it provides details on how the attack works and recommends precautions like firewalls, ingress/egress filtering, updating systems, and monitoring logs files and network traffic. Recent DDoS attack statistics indicate attacks are growing in frequency and bandwidth. Experimental testbed platforms are also discussed that can be used to study DDoS attacks and countermeasures.
Preventing Distributed Denial of Service Attacks in Cloud Environments IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of
nodes that interrelate with each other for switch over the information. This information is necessary for
that node is reserved confidentially. Attacker in the system may capture this private information and
distorted. So security is the major issue. There are several security attacks in network. One of the major
intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends
services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two
different behaviors they may happen obviously or it may due to some attackers .Various schemes are
developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
This document proposes a machine learning approach using the Naive Bayes algorithm to detect distributed denial of service (DDoS) attacks through network intrusion detection. It first discusses the issues with existing intrusion detection systems, including long training times and low accuracy. It then summarizes research on applying various machine learning techniques like neural networks, decision trees, and Naive Bayes to intrusion detection. The proposed system would build a classifier using Naive Bayes, which provides faster training than other methods, to distinguish normal and attack traffic. This approach aims to improve upon the training time and detection accuracy of existing intrusion detection systems.
The document discusses denial of service (DoS) and distributed denial of service (DDoS) attacks. It defines DoS and DDoS attacks, describes different types of DoS attacks like SYN flooding and Smurf attacks. It also explains how botnets and tools are used to launch DDoS attacks, and discusses some common DDoS countermeasures like detection, mitigation and traceback.
A ROBUST MECHANISM FOR DEFENDING DISTRIBUTED DENIAL OF SERVICE ATTACKS ON WEB...IJNSA Journal
Distributed Denial of Service (DDoS) attacks have emerged as a popular means of causing mass targeted service disruptions, often for extended periods of time. The relative ease and low costs of launching such attacks, supplemented by the current inadequate sate of any viable defense mechanism, have made them one of the top threats to the Internet community today. Since the increasing popularity of web-based applications has led to several critical services being provided over the Internet, it is imperative to monitor the network traffic so as to prevent malicious attackers from depleting the resources of the network and denying services to legitimate users. This paper first presents a brief discussion on some of the important types of DDoS attacks that currently exist and some existing mechanisms to combat these attacks. It then points out the major drawbacks of the currently existing defense mechanisms and proposes a new mechanism for protecting a web-server against a DDoS attack. In the proposed mechanism, incoming traffic to the server is continuously monitored and any abnormal rise in the inbound traffic is immediately detected. The detection algorithm is based on a statistical analysis of the inbound traffic on the server and a robust hypothesis testing framework. While the detection process is on, the sessions from the legitimate sources are not disrupted and the load on the server is restored to the normal level by blocking the traffic from the attacking sources. To cater to different scenarios, the detection algorithm has various modules with varying level of computational and memory overheads for
their execution. While the approximate modules are fast in detection and involve less overhead, they provide lower level of detection accuracy. The accurate modules employ complex detection logic and hence involve more overhead for their execution. However, they have very high detection accuracy. Simulations carried out on the proposed mechanism have produced results that demonstrate effectiveness of the proposed defense mechanism against DDoS attacks.
The document discusses various common computer network attacks and exploits. It provides descriptions of denial of service attacks, distributed denial of service attacks, backdoors, spoofing, man-in-the-middle attacks, replay attacks, session hijacking, DNS poisoning, password guessing, software exploits, war dialing, war driving, buffer overflows, SYN floods, ICMP floods, UDP floods, smurfing, sniffing, ping of death attacks and more. It also discusses implementing network security through identifying assets, threats, risk assessment, security policies, technical implementation, auditing and continuous improvement.
DDoS attacks target companies and institutions that provide online services. They work by overloading servers with traffic from multiple compromised systems known as "bots" or "zombies". Common DDoS attack types include SMURF, TCP SYN/ACK, UDP flood, DNS amplification, and attacks using peer-to-peer networks. Defenses include configuring routers and firewalls to filter unauthorized traffic, limiting response messages, and tracking malicious activity on peer-to-peer networks. As attack methods evolve, continued development of detection and mitigation techniques is needed.
This document provides an overview of distributed denial of service (DDoS) attacks, including how they work, common techniques used, and strategies for mitigating them. It defines DDoS attacks as attempts to exhaust the resources of networks, applications, or services to deny access to legitimate users. The document discusses how botnets are commonly used to launch large-scale DDoS attacks from multiple sources simultaneously. It also outlines best practices for selecting DDoS protection devices, emphasizing the importance of up-to-date detection techniques, low latency, and customized hardware-based logic to withstand major attacks.
A Comparative Approach to Handle Ddos AttacksIOSR Journals
This document summarizes various types of distributed denial of service (DDoS) attacks and potential countermeasures. It discusses common DDoS attacks like SYN flooding, UDP flooding, ICMP flooding, teardrop attacks, land attacks, and Win Nuke attacks. For each type of attack, it provides details on how the attack works and recommends precautions like firewalls, ingress/egress filtering, updating systems, and monitoring logs files and network traffic. Recent DDoS attack statistics indicate attacks are growing in frequency and bandwidth. Experimental testbed platforms are also discussed that can be used to study DDoS attacks and countermeasures.
This document discusses distributed denial of service (DDoS) attacks. It begins with an introduction that defines DDoS attacks as attempts to make an online service unavailable by overwhelming it with traffic from multiple compromised sources. The document then covers the basics of DDoS attacks, common symptoms, how they work by exploiting vulnerabilities in systems to create botnets for launching attacks, and various methods like ICMP floods and SYN floods. It also discusses ways to handle DDoS attacks through defenses like firewalls, switches, and routers. The document concludes with preventative and reactive defense mechanisms to detect and respond to attacks.
IRJET- A Survey on DDOS Attack in ManetIRJET Journal
This document summarizes a survey on distributed denial of service (DDoS) attacks in mobile ad hoc networks (MANETs). It begins by introducing MANETs and some of the key security issues they face, including DDoS attacks. It then discusses different types of DDoS attacks like flooding and amplification/reflection attacks. The document proposes a new defense scheme against amplification attacks, which exploit protocols like DNS and NTP to amplify traffic. It describes using the Network Security Simulator to model and simulate DDoS attacks with master, zombie, and server entities to evaluate defense techniques and compare the impact of protocols like DNS and NTP.
IRJET- DDOS Detection System using C4.5 Decision Tree AlgorithmIRJET Journal
This document proposes a machine learning model using the C4.5 decision tree algorithm to detect DDOS attacks. It trains the model on DDOS attack samples from the CICIDS2017 dataset, dividing the samples into training and test data. The Weka data mining tool is used to build the model with attribute filtering and 10-fold cross-validation. The trained model is then validated on the test data to accurately differentiate between benign and DDOS flooding traffic. This combined signature-based and anomaly-based detection approach can effectively detect complex DDOS attacks.
The document discusses denial of service (DoS) and distributed denial of service (DDoS) attacks. It defines DoS as an attack that renders a system unable to provide normal services by flooding it with traffic. DDoS uses multiple compromised systems to launch a coordinated DoS attack against one or more targets, multiplying the attack effectiveness. Attacks are classified by the system targeted (clients, routers, firewalls, servers), part of the system (hardware, OS, TCP/IP stack), and whether they exploit bugs or just overload resources. Common DDoS tools like Trinoo and TFN are mentioned. Protection from these large-scale attacks remains a challenge.
This document discusses distributed denial of service (DDoS) attacks. It begins by defining a DDoS attack as an attempt to make an online service unavailable by overwhelming it with traffic from multiple sources. It then explains how DDoS attacks work by exploiting vulnerable systems to create large networks of compromised devices that can be directed by an attacker to target a specific system or server. Finally, it discusses different types of DDoS attacks including volumetric attacks, protocol attacks, and application layer attacks and some famous DDoS incidents like attacks on the Church of Scientology and various websites.
Denial of Service attacks – Definitions, related surveys
Traceback of DDoS Attacks – Proposed method, advantages, future work
Detection methods with Shannon and Renyi cross entropy – Previous works, proposed method, dataset and results
The added value of entropy detection methods
References
The document discusses denial of service (DoS) attacks and methods of mitigation. It describes various types of DoS attacks including flooding attacks like TCP SYN floods and UDP floods that exhaust server bandwidth or resources. Other attacks discussed include HTTP floods, SSL handshake floods, and attacks that exploit vulnerabilities or misuse features like HTTP POST floods and SSL renegotiation attacks. State-of-the-art mitigation techniques mentioned include DoS mitigation software developed by the Society for Electronic Transactions & Security that use techniques like client puzzles to protect against various application layer attacks.
The document provides information about different types of DDoS attacks including DoS, DDoS, DNS reflection, SYN reflection, SMURF, UDP flood, SNMP, NTP, HTTP GET, and HTTP POST attacks. It describes how each attack works and overloads the target system with traffic. Mitigation techniques are also outlined, such as firewalls, rate limiting, authentication, and modifying server configurations.
Enhancing the impregnability of linux serversIJNSA Journal
Worldwide IT industry is experiencing a rapid shift towards Service Oriented Architecture (SOA). As a
response to the current trend, all the IT firms are adopting business models such as cloud based services
which rely on reliable and highly available server platforms. Linux servers are known to be highly
secure. Network security thus becomes a major concern to all IT organizations offering cloud based
services. The fundamental form of attack on network security is Denial of Service. This paper focuses on
fortifying the Linux server defence mechanisms resulting in an increase in reliability and availability of
services offered by the Linux server platforms. To meet this emerging scenario, most of the organizations
are adopting business models such as cloud computing that are dependant on reliable server platforms.
Linux servers are well ahead of other server platforms in terms of security. This brings network security
to the forefront of major concerns to an organization. The most common form of attacks is a Denial of
Service attack. This paper focuses on mechanisms to detect and immunize Linux servers from DoS .
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYijasa
Denial of Service (DoS) or Distributed-Denial of Service (DDoS) is major threat to network security.
Network is collection of nodes that interconnect with each other for exchange the Information. This
information is required for that node is kept confidentially. Attacker in network computer captures this
information that is confidential and misuse the network. Hence security is one of the major issues. There
are one or many attacks in network. One of the major threats to internet service is DDoS (Distributed
denial of services) attack. DDoS attack is a malicious attempt to suspending or interrupting services to
target node. DDoS or DoS is an attempt to make network resource or the machine is unavailable to its
intended user. Many ideas are developed for avoiding the DDoS or DoS. DDoS happen in two ways
naturally or it may due to some botnets .Various schemes are developed defense against to this attack.
Main idea of this paper is present basis of DDoS attack. DDoS attack types, DDoS attack components,
survey on different mechanism to prevent DDoS
Nowadays DNS is used to load balance, failover, and geographically redirect connections. DNS has become so pervasive it is hard to identify a modern TCP/IP connection that does not use DNS in some way. Unfortunately, due to the reliability built into the fundamental RFC-based design of DNS, most IT professionals don't spend much time worrying about it. If DNS is maliciously attacked — altering the addresses it gives out or taken offline the damage will be enormous. Whether conducted for political motives, financial gain, or just the notoriety of the attacker, the damage from a DNS attack can be devastating for the target.
In this research we will review different DNS advanced attacks and analyze them. We will survey some of the most DNS vulnerabilities and ways of DNS attacks protection.
This document provides explanations for multiple choice questions related to network scanning, TCP/IP protocols, and cybersecurity concepts like social engineering and denial of service attacks. It defines technical terms like ICMP type codes, default port numbers for protocols like SNMP and LDAP, the three-way handshake process in TCP, and vulnerabilities involving alternate data streams and tailgating. The explanations emphasize accurate port scanning methods, TCP flag functions, covert channels, broadcast MAC addresses, and strategies for preventing social engineering like tailgating.
Monitoring of traffic over the victim under tcp syn flood in a laneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IP Traceback for Flooding attacks on Internet Threat Monitors (ITM ) Using Ho...IJNSA Journal
The Internet Threat Monitoring (ITM) is an efficient monitoring system used globally to measure, detect, characterize and track threats such as denial of service (DoS) and distributed Denial of Service (DDoS) attacks and worms. . To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address the flooding attack of DDoS against ITM monitors to exhaust the network resources, such as bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. One possible way to counter DDoS attacks is to trace the attack sources and punish the perpetrators. we propose a novel traceback method for DDoS using Honeypots. IP tracing through honeypot is a single packet tracing method and is more efficient than commonly used packet marking techniques.
This document summarizes a research paper that proposed and evaluated methods for mitigating denial of service (DoS) and distributed denial of service (DDoS) attacks on virtual machines. The paper implemented iptables connection limits on the host machine to prevent excessive connections from attacking IPs. It also tuned network performance by adjusting the receiving window size to maximize bandwidth utilization. The experimental results showed that the iptables security measures protected against DoS/DDoS attacks while window scaling optimization improved network performance during attacks.
This document provides information about different types of denial of service (DoS) and distributed denial of service (DDoS) attacks, including buffer overflow, ping of death, smurf attack, and TCP SYN attack. It explains that DoS attacks aim to make machines or network resources unavailable by overwhelming them with more requests than their capacity allows. DDoS attacks perform the same type of flooding from multiple sources rather than a single source. The document also discusses how buffer overflows can corrupt data and crash systems, how ping of death exploits IP fragmentation, and how smurf attacks work by amplifying traffic volume through IP broadcast replies.
THE FIGHT AGAINST IP SPOOFING ATTACKS: NETWORK INGRESS FILTERING VERSUS FIRST...ijsptm
The IP(Internet Protocol) spoofing is a technique that consists in replacing the IP address of the sender by
another sender’s address. This technique allows the attacker to send a message without being intercepted
by the firewall. The most used method to deal with such attacks is the technique called "Network Ingress
Filtering". This technique has been used, initially, forIPv4 networks, but its principles, are currently
extended toIPv6 networks.Unfortunately, it has some limitations, the main is its accuracy. To improve
safety conditions, we applied the "First-Come First-Serve (FCFS)" technique, applied for IPV6 networks,
and developed by the "Internet Engineering Task Force (IETF)" within its working group "Source Address
Validation Improvements (SAVI)", which is currently being standardization. In this paper, we remember
the course of an attack by IP Spoofing and expose the threats it entails.Then, we explain the "Network
Ingress Filtering" technique. Next, We present the FCFS SAVI method and methodology that we have
adopted for its implementation.Finally, we, followingthe results, discuss and compare the advantages,
disadvantages andlimitations of the FCFSSAVI methodto thoseknown in the "Network Ingress Filtering"
technique. FCFS SAVI method is more effective than the technique of "Network Ingress Filtering", but
requires some improvements, for dealing with limitations it presents.
This was a group project which was created by myself, Samy Izebboudjen, Daniel Phan, and Eric Hernandez in which we tested a denial of service SYN flood script against a targeted website on our own local network on a virtual machine. In this project, we also used virtual machines (via VirtualBox) in order to set up our testing environment as well as used Wireshark to analyze the network traffic during the simulation.
This project was conducted during our ISYS-575 (Information Security Management) course at San Francisco State University and the purpose of this project and write-up was to test network security and determine the overall effects a denial of service attack has against a targeted website/network.
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.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
PREVENTING DISTRIBUTED DENIAL OF SERVICE ATTACKS IN CLOUD ENVIRONMENTS IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of nodes that interrelate with each other for switch over the information. This information is necessary for that node is reserved confidentially. Attacker in the system may capture this private information and distorted. So security is the major issue. There are several security attacks in network. One of the major intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two different behaviors they may happen obviously or it may due to some attackers .Various schemes are developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
This document discusses distributed denial of service (DDoS) attacks. It begins with an introduction that defines DDoS attacks as attempts to make an online service unavailable by overwhelming it with traffic from multiple compromised sources. The document then covers the basics of DDoS attacks, common symptoms, how they work by exploiting vulnerabilities in systems to create botnets for launching attacks, and various methods like ICMP floods and SYN floods. It also discusses ways to handle DDoS attacks through defenses like firewalls, switches, and routers. The document concludes with preventative and reactive defense mechanisms to detect and respond to attacks.
IRJET- A Survey on DDOS Attack in ManetIRJET Journal
This document summarizes a survey on distributed denial of service (DDoS) attacks in mobile ad hoc networks (MANETs). It begins by introducing MANETs and some of the key security issues they face, including DDoS attacks. It then discusses different types of DDoS attacks like flooding and amplification/reflection attacks. The document proposes a new defense scheme against amplification attacks, which exploit protocols like DNS and NTP to amplify traffic. It describes using the Network Security Simulator to model and simulate DDoS attacks with master, zombie, and server entities to evaluate defense techniques and compare the impact of protocols like DNS and NTP.
IRJET- DDOS Detection System using C4.5 Decision Tree AlgorithmIRJET Journal
This document proposes a machine learning model using the C4.5 decision tree algorithm to detect DDOS attacks. It trains the model on DDOS attack samples from the CICIDS2017 dataset, dividing the samples into training and test data. The Weka data mining tool is used to build the model with attribute filtering and 10-fold cross-validation. The trained model is then validated on the test data to accurately differentiate between benign and DDOS flooding traffic. This combined signature-based and anomaly-based detection approach can effectively detect complex DDOS attacks.
The document discusses denial of service (DoS) and distributed denial of service (DDoS) attacks. It defines DoS as an attack that renders a system unable to provide normal services by flooding it with traffic. DDoS uses multiple compromised systems to launch a coordinated DoS attack against one or more targets, multiplying the attack effectiveness. Attacks are classified by the system targeted (clients, routers, firewalls, servers), part of the system (hardware, OS, TCP/IP stack), and whether they exploit bugs or just overload resources. Common DDoS tools like Trinoo and TFN are mentioned. Protection from these large-scale attacks remains a challenge.
This document discusses distributed denial of service (DDoS) attacks. It begins by defining a DDoS attack as an attempt to make an online service unavailable by overwhelming it with traffic from multiple sources. It then explains how DDoS attacks work by exploiting vulnerable systems to create large networks of compromised devices that can be directed by an attacker to target a specific system or server. Finally, it discusses different types of DDoS attacks including volumetric attacks, protocol attacks, and application layer attacks and some famous DDoS incidents like attacks on the Church of Scientology and various websites.
Denial of Service attacks – Definitions, related surveys
Traceback of DDoS Attacks – Proposed method, advantages, future work
Detection methods with Shannon and Renyi cross entropy – Previous works, proposed method, dataset and results
The added value of entropy detection methods
References
The document discusses denial of service (DoS) attacks and methods of mitigation. It describes various types of DoS attacks including flooding attacks like TCP SYN floods and UDP floods that exhaust server bandwidth or resources. Other attacks discussed include HTTP floods, SSL handshake floods, and attacks that exploit vulnerabilities or misuse features like HTTP POST floods and SSL renegotiation attacks. State-of-the-art mitigation techniques mentioned include DoS mitigation software developed by the Society for Electronic Transactions & Security that use techniques like client puzzles to protect against various application layer attacks.
The document provides information about different types of DDoS attacks including DoS, DDoS, DNS reflection, SYN reflection, SMURF, UDP flood, SNMP, NTP, HTTP GET, and HTTP POST attacks. It describes how each attack works and overloads the target system with traffic. Mitigation techniques are also outlined, such as firewalls, rate limiting, authentication, and modifying server configurations.
Enhancing the impregnability of linux serversIJNSA Journal
Worldwide IT industry is experiencing a rapid shift towards Service Oriented Architecture (SOA). As a
response to the current trend, all the IT firms are adopting business models such as cloud based services
which rely on reliable and highly available server platforms. Linux servers are known to be highly
secure. Network security thus becomes a major concern to all IT organizations offering cloud based
services. The fundamental form of attack on network security is Denial of Service. This paper focuses on
fortifying the Linux server defence mechanisms resulting in an increase in reliability and availability of
services offered by the Linux server platforms. To meet this emerging scenario, most of the organizations
are adopting business models such as cloud computing that are dependant on reliable server platforms.
Linux servers are well ahead of other server platforms in terms of security. This brings network security
to the forefront of major concerns to an organization. The most common form of attacks is a Denial of
Service attack. This paper focuses on mechanisms to detect and immunize Linux servers from DoS .
A REVIEW ON DDOS PREVENTION AND DETECTION METHODOLOGYijasa
Denial of Service (DoS) or Distributed-Denial of Service (DDoS) is major threat to network security.
Network is collection of nodes that interconnect with each other for exchange the Information. This
information is required for that node is kept confidentially. Attacker in network computer captures this
information that is confidential and misuse the network. Hence security is one of the major issues. There
are one or many attacks in network. One of the major threats to internet service is DDoS (Distributed
denial of services) attack. DDoS attack is a malicious attempt to suspending or interrupting services to
target node. DDoS or DoS is an attempt to make network resource or the machine is unavailable to its
intended user. Many ideas are developed for avoiding the DDoS or DoS. DDoS happen in two ways
naturally or it may due to some botnets .Various schemes are developed defense against to this attack.
Main idea of this paper is present basis of DDoS attack. DDoS attack types, DDoS attack components,
survey on different mechanism to prevent DDoS
Nowadays DNS is used to load balance, failover, and geographically redirect connections. DNS has become so pervasive it is hard to identify a modern TCP/IP connection that does not use DNS in some way. Unfortunately, due to the reliability built into the fundamental RFC-based design of DNS, most IT professionals don't spend much time worrying about it. If DNS is maliciously attacked — altering the addresses it gives out or taken offline the damage will be enormous. Whether conducted for political motives, financial gain, or just the notoriety of the attacker, the damage from a DNS attack can be devastating for the target.
In this research we will review different DNS advanced attacks and analyze them. We will survey some of the most DNS vulnerabilities and ways of DNS attacks protection.
This document provides explanations for multiple choice questions related to network scanning, TCP/IP protocols, and cybersecurity concepts like social engineering and denial of service attacks. It defines technical terms like ICMP type codes, default port numbers for protocols like SNMP and LDAP, the three-way handshake process in TCP, and vulnerabilities involving alternate data streams and tailgating. The explanations emphasize accurate port scanning methods, TCP flag functions, covert channels, broadcast MAC addresses, and strategies for preventing social engineering like tailgating.
Monitoring of traffic over the victim under tcp syn flood in a laneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IP Traceback for Flooding attacks on Internet Threat Monitors (ITM ) Using Ho...IJNSA Journal
The Internet Threat Monitoring (ITM) is an efficient monitoring system used globally to measure, detect, characterize and track threats such as denial of service (DoS) and distributed Denial of Service (DDoS) attacks and worms. . To block the monitoring system in the internet the attackers are targeted the ITM system. In this paper we address the flooding attack of DDoS against ITM monitors to exhaust the network resources, such as bandwidth, computing power, or operating system data structures by sending the malicious traffic. We propose an information-theoretic frame work that models the flooding attacks using Botnet on ITM. One possible way to counter DDoS attacks is to trace the attack sources and punish the perpetrators. we propose a novel traceback method for DDoS using Honeypots. IP tracing through honeypot is a single packet tracing method and is more efficient than commonly used packet marking techniques.
This document summarizes a research paper that proposed and evaluated methods for mitigating denial of service (DoS) and distributed denial of service (DDoS) attacks on virtual machines. The paper implemented iptables connection limits on the host machine to prevent excessive connections from attacking IPs. It also tuned network performance by adjusting the receiving window size to maximize bandwidth utilization. The experimental results showed that the iptables security measures protected against DoS/DDoS attacks while window scaling optimization improved network performance during attacks.
This document provides information about different types of denial of service (DoS) and distributed denial of service (DDoS) attacks, including buffer overflow, ping of death, smurf attack, and TCP SYN attack. It explains that DoS attacks aim to make machines or network resources unavailable by overwhelming them with more requests than their capacity allows. DDoS attacks perform the same type of flooding from multiple sources rather than a single source. The document also discusses how buffer overflows can corrupt data and crash systems, how ping of death exploits IP fragmentation, and how smurf attacks work by amplifying traffic volume through IP broadcast replies.
THE FIGHT AGAINST IP SPOOFING ATTACKS: NETWORK INGRESS FILTERING VERSUS FIRST...ijsptm
The IP(Internet Protocol) spoofing is a technique that consists in replacing the IP address of the sender by
another sender’s address. This technique allows the attacker to send a message without being intercepted
by the firewall. The most used method to deal with such attacks is the technique called "Network Ingress
Filtering". This technique has been used, initially, forIPv4 networks, but its principles, are currently
extended toIPv6 networks.Unfortunately, it has some limitations, the main is its accuracy. To improve
safety conditions, we applied the "First-Come First-Serve (FCFS)" technique, applied for IPV6 networks,
and developed by the "Internet Engineering Task Force (IETF)" within its working group "Source Address
Validation Improvements (SAVI)", which is currently being standardization. In this paper, we remember
the course of an attack by IP Spoofing and expose the threats it entails.Then, we explain the "Network
Ingress Filtering" technique. Next, We present the FCFS SAVI method and methodology that we have
adopted for its implementation.Finally, we, followingthe results, discuss and compare the advantages,
disadvantages andlimitations of the FCFSSAVI methodto thoseknown in the "Network Ingress Filtering"
technique. FCFS SAVI method is more effective than the technique of "Network Ingress Filtering", but
requires some improvements, for dealing with limitations it presents.
This was a group project which was created by myself, Samy Izebboudjen, Daniel Phan, and Eric Hernandez in which we tested a denial of service SYN flood script against a targeted website on our own local network on a virtual machine. In this project, we also used virtual machines (via VirtualBox) in order to set up our testing environment as well as used Wireshark to analyze the network traffic during the simulation.
This project was conducted during our ISYS-575 (Information Security Management) course at San Francisco State University and the purpose of this project and write-up was to test network security and determine the overall effects a denial of service attack has against a targeted website/network.
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.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
PREVENTING DISTRIBUTED DENIAL OF SERVICE ATTACKS IN CLOUD ENVIRONMENTS IJITCA Journal
Distributed-Denial of Service (DDoS) is a key intimidation to network security. Network is a group of nodes that interrelate with each other for switch over the information. This information is necessary for that node is reserved confidentially. Attacker in the system may capture this private information and distorted. So security is the major issue. There are several security attacks in network. One of the major intimidations to internet examine is DDoS attack. It is a malevolent effort to suspending or suspends services to destination node. DDoS or DoS is an effort to create network resource or the machine is busy to
its intentional user. Numerous thoughts are developed for avoid the DDoS or DoS. DDoS occur in two different behaviors they may happen obviously or it may due to some attackers .Various schemes are developed defense against to this attack. The Main focus of paper is present basis of DDoS attack, DDoS
attack types, and DDoS attack components, intrusion prevention system for DDoS.
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.
This document discusses a statistical approach for classifying and identifying different types of Distributed Denial of Service (DDoS) attacks using the UCLA dataset. It first introduces DDoS attacks and their increasing prevalence. It then discusses related work on DDoS attack detection. The document outlines the architecture of DDoS attacks and describes some common types like SYN flooding and ACK flooding attacks. The proposed system is described which involves collecting packets, extracting features, using a packet classification algorithm to initially classify attacks, then using a K-Nearest Neighbors classifier for more accurate results. Finally, the system aims to classify and identify specific types of DDoS attacks from the network traffic analysis.
This document discusses a statistical approach for classifying and identifying DDoS attacks using the UCLA dataset. It proposes extracting features from network traffic such as packet count, average packet size, time interval variance, and packet size variance. A packet classification algorithm first classifies packets as normal or attacks. For uncertain cases, a K-NN classifier is used. Then the types of DDoS attacks, including flooding and scanning attacks, are identified based on the feature values. The proposed approach is evaluated using the UCLA dataset and shows mathematical calculations for feature extraction. In conclusion, the statistical approach and packet classification algorithm are effective for classifying common DDoS flooding and scanning attacks.
The document discusses distributed denial of service (DDoS) attacks, including how they work, common tools and methods used, and examples of recent large-scale DDoS attacks. It provides details on how botnets are used to overwhelm websites and infrastructure with malicious traffic. Specific DDoS attack types like UDP floods, SYN floods, and reflection attacks are outlined. Recent large attacks are described, such as those targeting bitcoin exchanges, social trading platforms, and Hong Kong voting sites ahead of a civil referendum.
The document discusses distributed denial of service (DDoS) attacks and methods to detect them. It describes DDoS attacks as attempts to make network resources unavailable by flooding them with traffic. The document then reviews literature on detection methods like packet marking and cumulative sum algorithms. It presents a methodology using packet sniffing and analysis to identify attack levels based on packet counts. Specifically, it generates DDoS attacks using LOIC and analyzes TCP SYN flood and UDP flood attacks to detect the length of attacks with over 99% accuracy. In conclusion, it emphasizes the challenge of identifying DDoS attacks and discusses using packet headers and contents to identify malicious traffic based on their behaviors.
The document summarizes distributed denial of service (DDoS) attacks and defenses against them. It provides an overview of DDoS attacks, describes several common DDoS tools (Trinoo, TFN, TFN2K, Stacheldraht), and discusses challenges in defending against them. It also presents a case study of a DDoS attack against the website GRC.com and the difficulties they faced in getting help stopping the attacks. The document advocates for coordinated technical solutions and consistent incentive structures to defend against DDoS attacks.
A SYNCHRONIZED DISTRIBUTED DENIAL OF SERVICE PREVENTION SYSTEMcscpconf
DDoS attack is a distributed source but coordinated Internet security threat that attackers either degrade or disrupt a shared service to legitimate users. It uses various methods to inflict damages on limited resources. It can be broadly classified as: flood and semantic (logic) attacks. DDoS attacking mechanisms vary from time to time and simple but powerful attacking tools are freely available on the Internet. There have been many trials on defending victims from DDoS attacks. However, many of the previous attack prevention systems lack effective handling of various attacking mechanisms and protecting legitimate users from collateral damages during detection and protection. In this paper, we proposed a distributed but synchronized DDoS defense architecture by using multiple agents, which are autonomous systems that perform their assigned mission in other networks on behalf of the victim. The major assignments of defense agents are IP spoofing verification, high traffic rate limitation, anomaly packet detection, and attack source detection.These tasks are distributed through four agents that are deployed on different domain networks. The proposed solution was tested through simulation with sample attack scenarios on the model Internet topology. The experiments showed encouraging results. A more comprehensive attack protection and legitimate users prevention from collateral damages makes this system more effective than other previous works.
Study of flooding based ddos attacks and their effect using deter testbedeSAT Journals
Abstract Today, Internet is the primary medium for communication which is used by number of users across the Network. At the same time, its commercial nature is causing increase vulnerability to enhance cyber crimes and there has been an enormous increase in the number of DDOS (distributed denial of service attack) attacks on the internet over the past decade. Whose impact can be proportionally severe. With little or no advance warning, a DDoS attack can easily exhaust the computing and communication resources of its victim within a short period of time. Network resources such as network bandwidth, web servers and network switches are mostly the victims of DDoS attacks. In this paper different types of DDoS attacks has been studied, a dumb-bell topology have been created and effect of UDP flooding attacks has been analyzed on web service by using attack tools available in DETER testbed. Throughput of web server is analyzed with and without DDoS attacks.
Study of flooding based d do s attacks and their effect using deter testbedeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document is a project report submitted by two students, Ameya Vashishth and Amir Khan, for their Bachelor of Technology degree. It examines denial of service (DoS) attacks in cloud computing. The report includes an introduction to DoS attacks, descriptions of different types of attacks like ping of death, SYN flooding, and Smurf attacks. It also discusses tools used for DoS attacks, countermeasures, and the legal issues surrounding these attacks. The document contains abstract, table of contents, list of figures, and 10 chapters covering these topics in detail with examples.
This document provides an overview of distributed denial of service (DDoS) attacks. It discusses the components and architecture of DDoS attacks and classifies them into four categories: flood attacks, amplification attacks, TCP SYN attacks, and malformed packet attacks. Specific attack types like UDP floods, ICMP floods, Smurf attacks and Fraggle attacks are described. The document also covers DDoS defense problems and classifications such as intrusion prevention, detection, tolerance and response. It concludes that DDoS attacks are difficult to prevent due to readily available tools and the ability to target any internet host, and that the best defense involves vigilant system administration.
International Journal of Computational Science and Information Technology (I...ijcsity
Denial of Service (DoS) or Distributed-Denial of Service (DDoS) is major threat to network security.Network is collection of nodes that interconnect with each other for exchange the Information. This information is required for that node is kept confidentially. Attacker in network computer captures this information that is confidential and misuse the network. Hence security is one of the major issues. There are one or many attacks in network. One of the major threats to internet service is DDoS (Distributed denial of services) attack. DDoS attack is a malicious attempt to suspending or interrupting services to target node. DDoS or DoS is an attempt to make network resource or the machine is unavailable to its intended user. Many ideas are developed for avoiding the DDoS or DoS. DDoS happen in two ways
naturally or it may due to some botnets .Various schemes are developed defense against to this attack.Main idea of this paper is present basis of DDoS attack. DDoS attack types, DDoS attack components,survey on different mechanism to prevent DDoS.
This document discusses denial of service (DoS) attacks at different layers of the TCP/IP model. It begins with an introduction to DoS attacks and some common types like ping of death, smurf, buffer overflow, teardrop, and SYN attacks. It then examines DoS attacks at each layer of the TCP/IP model: physical layer attacks target devices and media; data link layer attacks include MAC spoofing and DHCP starvation; network layer attacks involve IP spoofing, RIP attacks, and ICMP flooding; transport layer attacks focus on session hijacking; and application layer attacks include HTTP flooding. The document reviews several research papers on detecting and preventing DoS attacks at different layers using methods like machine learning algorithms.
A Survey: DDOS Attack on Internet of ThingsIJERD Editor
Internet of Things refer as interconnection of smart object, included from small coffee machine to
big car, communicate with each other without human interactions also called as Device to Device
communications. In current emerging world, all of the devices become smarter and can communicate with other
devices as well. With this rapid development of Internet of Things in different area like smart home, smart
hospital etc. it also have to face some difficulty to securing overall privacy due to heterogeneity nature. There
are so many types of vulnerability but here in this paper we put concentration on Distributed Denial of Service
attack (DDoS). DoS is attack which can block the usage for authentic user and make network resource
unavailable, consume bandwidth; if similar attack is penetrated from different sources its call DDoS. To prevent
from such attack it need mechanism that can detect and prevent it from attack, but due to small devices it has
limited power capacity. So that mechanism must be implemented at network entrance. In this paper we discuss
different DDoS attack and its effect on IoT.
A Novel Method for Prevention of Bandwidth Distributed Denial of Service AttacksIJERD Editor
Distributed Denial of Service (DDoS) Attacks became a massive threat to the Internet. Traditional
Architecture of internet is vulnerable to the attacks like DDoS. Attacker primarily acquire his army of Zombies,
then that army will be instructed by the Attacker that when to start an attack and on whom the attack should be
done. In this paper, different techniques which are used to perform DDoS Attacks, Tools that were used to
perform Attacks and Countermeasures in order to detect the attackers and eliminate the Bandwidth Distributed
Denial of Service attacks (B-DDoS) are reviewed. DDoS Attacks were done by using various Flooding
techniques which are used in DDoS attack.
The main purpose of this paper is to design an architecture which can reduce the Bandwidth
Distributed Denial of service Attack and make the victim site or server available for the normal users by
eliminating the zombie machines. Our Primary focus of this paper is to dispute how normal machines are
turning into zombies (Bots), how attack is been initiated, DDoS attack procedure and how an organization can
save their server from being a DDoS victim. In order to present this we implemented a simulated environment
with Cisco switches, Routers, Firewall, some virtual machines and some Attack tools to display a real DDoS
attack. By using Time scheduling, Resource Limiting, System log, Access Control List and some Modular
policy Framework we stopped the attack and identified the Attacker (Bot) machines
Presentation of "State of the Art of IoT Honeypots" technical report developed for the Seminar in Advanced Topics in Computer Science course of the Master Degree in Engineering in Computer Science curriculum in Cyber Security at University of Rome "La Sapienza".
Link: https://www.slideshare.net/secret/EfL8YbinRZjDPS
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
This document provides a review of mobility management techniques in vehicular ad hoc networks (VANETs). It discusses three modes of communication in VANETs: vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and hybrid vehicle (HV) communication. For each communication mode, different mobility management schemes are required due to their unique characteristics. The document also discusses mobility management challenges in VANETs and outlines some open research issues in improving mobility management for seamless communication in these dynamic networks.
This document provides a review of different techniques for segmenting brain MRI images to detect tumors. It compares the K-means and Fuzzy C-means clustering algorithms. K-means is an exclusive clustering algorithm that groups data points into distinct clusters, while Fuzzy C-means is an overlapping clustering algorithm that allows data points to belong to multiple clusters. The document finds that Fuzzy C-means requires more time for brain tumor detection compared to other methods like hierarchical clustering or K-means. It also reviews related work applying these clustering algorithms to segment brain MRI images.
1) The document simulates and compares the performance of AODV and DSDV routing protocols in a mobile ad hoc network under three conditions: when users are fixed, when users move towards the base station, and when users move away from the base station.
2) The results show that both protocols have higher packet delivery and lower packet loss when users are either fixed or moving towards the base station, since signal strength is better in those scenarios. Performance degrades when users move away from the base station due to weaker signals.
3) AODV generally has better performance than DSDV, with higher throughput and packet delivery rates observed across the different user mobility conditions.
This document describes the design and implementation of 4-bit QPSK and 256-bit QAM modulation techniques using MATLAB. It compares the two techniques based on SNR, BER, and efficiency. The key steps of implementing each technique in MATLAB are outlined, including generating random bits, modulation, adding noise, and measuring BER. Simulation results show scatter plots and eye diagrams of the modulated signals. A table compares the results, showing that 256-bit QAM provides better performance than 4-bit QPSK. The document concludes that QAM modulation is more effective for digital transmission systems.
The document proposes a hybrid technique using Anisotropic Scale Invariant Feature Transform (A-SIFT) and Robust Ensemble Support Vector Machine (RESVM) to accurately identify faces in images. A-SIFT improves upon traditional SIFT by applying anisotropic scaling to extract richer directional keypoints. Keypoints are processed with RESVM and hypothesis testing to increase accuracy above 95% by repeatedly reprocessing images until the threshold is met. The technique was tested on similar and different facial images and achieved better results than SIFT in retrieval time and reduced keypoints.
This document studies the effects of dielectric superstrate thickness on microstrip patch antenna parameters. Three types of probes-fed patch antennas (rectangular, circular, and square) were designed to operate at 2.4 GHz using Arlondiclad 880 substrate. The antennas were tested with and without an Arlondiclad 880 superstrate of varying thicknesses. It was found that adding a superstrate slightly degraded performance by lowering the resonant frequency and increasing return loss and VSWR, while decreasing bandwidth and gain. Specifically, increasing the superstrate thickness or dielectric constant resulted in greater changes to the antenna parameters.
This document describes a wireless environment monitoring system that utilizes soil energy as a sustainable power source for wireless sensors. The system uses a microbial fuel cell to generate electricity from the microbial activity in soil. Two microbial fuel cells were created using different soil types and various additives to produce different current and voltage outputs. An electronic circuit was designed on a printed circuit board with components like a microcontroller and ZigBee transceiver. Sensors for temperature and humidity were connected to the circuit to monitor the environment wirelessly. The system provides a low-cost way to power remote sensors without needing battery replacement and avoids the high costs of wiring a power source.
1) The document proposes a model for a frequency tunable inverted-F antenna that uses ferrite material.
2) The resonant frequency of the antenna can be significantly shifted from 2.41GHz to 3.15GHz, a 31% shift, by increasing the static magnetic field placed on the ferrite material.
3) Altering the permeability of the ferrite allows tuning of the antenna's resonant frequency without changing the physical dimensions, providing flexibility to operate over a wide frequency range.
This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
This document reviews the design of an energy-optimized wireless sensor node that encrypts data for transmission. It discusses how sensing schemes that group nodes into clusters and transmit aggregated data can reduce energy consumption compared to individual node transmissions. The proposed node design calculates the minimum transmission power needed based on received signal strength and uses a periodic sleep/wake cycle to optimize energy when not sensing or transmitting. It aims to encrypt data at both the node and network level to further optimize energy usage for wireless communication.
This document discusses group consumption modes. It analyzes factors that impact group consumption, including external environmental factors like technological developments enabling new forms of online and offline interactions, as well as internal motivational factors at both the group and individual level. The document then proposes that group consumption modes can be divided into four types based on two dimensions: vertical (group relationship intensity) and horizontal (consumption action period). These four types are instrument-oriented, information-oriented, enjoyment-oriented, and relationship-oriented consumption modes. Finally, the document notes that consumption modes are dynamic and can evolve over time.
The document summarizes a study of different microstrip patch antenna configurations with slotted ground planes. Three antenna designs were proposed and their performance evaluated through simulation: a conventional square patch, an elliptical patch, and a star-shaped patch. All antennas were mounted on an FR4 substrate. The effects of adding different slot patterns to the ground plane on resonance frequency, bandwidth, gain and efficiency were analyzed parametrically. Key findings were that reshaping the patch and adding slots increased bandwidth and shifted resonance frequency. The elliptical and star patches in particular performed better than the conventional design. Three antenna configurations were selected for fabrication and measurement based on the simulations: a conventional patch with a slot under the patch, an elliptical patch with slots
1) The document describes a study conducted to improve call drop rates in a GSM network through RF optimization.
2) Drive testing was performed before and after optimization using TEMS software to record network parameters like RxLevel, RxQuality, and events.
3) Analysis found call drops were occurring due to issues like handover failures between sectors, interference from adjacent channels, and overshooting due to antenna tilt.
4) Corrective actions taken included defining neighbors between sectors, adjusting frequencies to reduce interference, and lowering the mechanical tilt of an antenna.
5) Post-optimization drive testing showed improvements in RxLevel, RxQuality, and a reduction in dropped calls.
This document describes the design of an intelligent autonomous wheeled robot that uses RF transmission for communication. The robot has two modes - automatic mode where it can make its own decisions, and user control mode where a user can control it remotely. It is designed using a microcontroller and can perform tasks like object recognition using computer vision and color detection in MATLAB, as well as wall painting using pneumatic systems. The robot's movement is controlled by DC motors and it uses sensors like ultrasonic sensors and gas sensors to navigate autonomously. RF transmission allows communication between the robot and a remote control unit. The overall aim is to develop a low-cost robotic system for industrial applications like material handling.
This document reviews cryptography techniques to secure the Ad-hoc On-Demand Distance Vector (AODV) routing protocol in mobile ad-hoc networks. It discusses various types of attacks on AODV like impersonation, denial of service, eavesdropping, black hole attacks, wormhole attacks, and Sybil attacks. It then proposes using the RC6 cryptography algorithm to secure AODV by encrypting data packets and detecting and removing malicious nodes launching black hole attacks. Simulation results show that after applying RC6, the packet delivery ratio and throughput of AODV increase while delay decreases, improving the security and performance of the network under attack.
The document describes a proposed modification to the conventional Booth multiplier that aims to increase its speed by applying concepts from Vedic mathematics. Specifically, it utilizes the Urdhva Tiryakbhyam formula to generate all partial products concurrently rather than sequentially. The proposed 8x8 bit multiplier was coded in VHDL, simulated, and found to have a path delay 44.35% lower than a conventional Booth multiplier, demonstrating its potential for higher speed.
This document discusses image deblurring techniques. It begins by introducing image restoration and focusing on image deblurring. It then discusses challenges with image deblurring being an ill-posed problem. It reviews existing approaches to screen image deconvolution including estimating point spread functions and iteratively estimating blur kernels and sharp images. The document also discusses handling spatially variant blur and summarizes the relationship between the proposed method and previous work for different blur types. It proposes using color filters in the aperture to exploit parallax cues for segmentation and blur estimation. Finally, it proposes moving the image sensor circularly during exposure to prevent high frequency attenuation from motion blur.
This document describes modeling an adaptive controller for an aircraft roll control system using PID, fuzzy-PID, and genetic algorithm. It begins by introducing the aircraft roll control system and motivation for developing an adaptive controller to minimize errors from noisy analog sensor signals. It then provides the mathematical model of aircraft roll dynamics and describes modeling the real-time flight control system in MATLAB/Simulink. The document evaluates PID, fuzzy-PID, and PID-GA (genetic algorithm) controllers for aircraft roll control and finds that the PID-GA controller delivers the best performance.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Fueling AI with Great Data with Airbyte WebinarZilliz
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A Comprehensive Guide to DeFi Development Services in 2024
L1803046876
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 3, Ver. IV (May-Jun. 2016), PP 68-76
www.iosrjournals.org
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 68 | Page
Survey Of DDoS Attacks Based On TCP/IP Protocol
Vulnerabilities
Saket Acharya1
, Namita Tiwari2
1
(Department Of Computer Science Engineering,MANIT Bhopal,India)
2
(Asstt. Professor,Department Of Computer Science Engineering,MANIT Bhopal,India)
Abstract: Distributed denial-of-service (DDoS) attacks are one of the key threats and perhaps the toughest
security problem for today’s Internet.Distributed Denial of Service (DDoS) attack has become a stimulating
problem to the availability of resources in computer networks.With brief or no advance warning, a DDoS attack
can easily drain the computing and communication resources of its victim within a short period of time. In this
paper, DDoS attacks based on the protocols vulnerabilities in the TCP/IP model, their impact on available
resources viz CPU,memory,buffer space is investigated. This paper aims to provide a better understanding of
the existing tools,methods and comparative analysis of them,and defense mechanisms.
Keywords: Cyber-attack, Cyber security,DDoS Attack,DDoS Attack Tools, Mitigation,Vulnerability,
I. Introduction
Distributed Denial of Service (DDoS) attacks pose a severe problem in the Internet, whose impact has
been well exhibited in the computer network literature. The main goal of a DDoS is the disruption of services by
attempting to reduce access to a machine or service instead of depraving the service itself..In DDoS attack, the
attacker feats any vulnerability in the protocols at different layers.In this way it compromises different systems.
These systems are called zombies or bots.[1]DDoS attacks are comprised of packet streams from disparate
sources.The DDoS tools do not require technical knowledge to execute them. Hence DDoS are becoming
effortless to launch and difficult to detect.DDoS traffic creates a heavy congestion in the internet and hinders all
Internet users whose packets cross congested routers.In this paper, we studied ddos attack types at various
TCP/IP protocols,application level ddos attack tools ,compare existing GUI tools so that we know the trend of
attacking method used by the attackers to launch an attack and various defense mechanisms.DDoS attacks never
try to break the victim's system, thus making any old security defense mechanism inefficient. The main goal of a
DDoS attack is to cause destruction on a victim either for personal reasons, either for material gain, or for
popularity.[2]Application level attacks overflow a computer with such a high volume of connection requests,
that all available operating system resources are disbursed, and the computer can no longer process legitimate
user requests.
II. Ddos Architecture
A Distributed Denial of Service Attack is encompassed of following terms, as shown in Fig. 1:
The attacker.
The handlers or masters, which are conceded hosts with a special program running on them, capable of
controlling multiple agents.
The attack daemon agents or zombie hosts, who are conceded hosts that are running a special program and
are responsible for generating a stream of packets towards the intended victim.
Victim.
Fig. 1: DDoS Architecture
2. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 69 | Page
Following steps take place during DDoS attack:
1. The attacker chooses the machines that have some susceptibility that the attacker can use to gain access to
them. Using these machines, the attacker performs attack.
2. The attacker exploits the vulnerabilities of the agent machines and embeds the attack code. When
participating in a DDoS attack, each agent program uses only a small amount of resources (both in memory
and bandwidth), so that the users of computers experience minimal change in performance.
3. The attacker communicates with handlers to identify which agents are running and when to schedule
attacks. In case of direct attack, the attacker directly performs the attack without handlers.
III. Ddos Attacks Classification
On the basis of TCP/IP Protocol vulnerabilities, DDoS attacks are classified as shown in Fig.2
Fig. 2: Classification of DDoS Attacks Based On TCP/IP Vulnerabilites
A. Application Layer DDoS Attacks: An application layer DDoS attack is prepared mainly for explicit
targeted purposes, including disrupting transactions and access to databases. They require a smaller amount
of resources and often supplement network layer attacks. An attack is masked to look like legitimate traffic,
except it targets particular application packets. The attack on the application layer can dislocate services
such as the retrieval of information or search function as well as web browser function, email services and
photo applications.
Following are some application layer DDoS attacks:
a) HTTP/HTTPS Flooding: HTTP flood is a type of Distributed Denial of Service (DDoS) attack in which
the attacker feats HTTP GET or POST requests which looks real to attack a web server or application.
HTTP flood attacks are volumetric attacks, frequently using a botnet ―zombie army‖—a group of Internet-
connected computers, each of which has been spitefully taken over, usually with the help of malware like
Trojan Horses. An erudite Layer 7 attack, HTTP floods do not use deformed packets, spoofing or reflection
techniques, and involve less bandwidth than other attacks to bring down the targeted site or server. This
attack is disgrading in nature.
b) FTP Flooding: In this type of attack, the attacker exploits apparently-legitimate FTP requests to outbreak a
FTP server or application. This attack is disgrading in nature.
c) Telnet DDoS: In this type of attack, the attacker distantly login into target system and the perform attack.
This attack is disgrading in nature.
d) Mail Bombs: Attacker sends a immense amount of e-mail to a specific person or system. A huge amount of
mail may solely fill up the recipient's disk space on the server. This attack is degrading in nature.
e) SQL Slammer: It is a computer worm that triggered a denial of service on some Internet hosts and
intensely slowed down general Internet traffic.
f) DNS Flood: DNS floods are endeavored to exhaust server-side assets (e.g., memory or CPU) with a flood
of UDP requests, created by scripts running on several conceded botnet machines.
B. Transport Layer DDoS Attacks: These types of attacks are usually encompassed of volumetric attacks
that aim to devastate the target machine, denying or consuming resources until the server goes offline. In
these types of DDoS attacks, malicious traffic (TCP / UDP) is used to flood the victim.The major categories
of DDoS attacks under transport layer are following:
a) SYN Flooding: It is a form of denial-of-service attack in which an attacker sends a subsequence of SYN
requests to a target's system in an attempt to ingest enough server resources to make the system
unresponsive to legitimate traffic. It is generally degrading in nature. It is shown below:
3. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 70 | Page
Fig 3: DDoS SYN Flooding
b) UDP Flooding : The attacker sends UDP packets, naturally big ones, to single destination or to random
ports.It is generally disruptive in nature.It is shown below:
Fig 4: UDP Flooding
c) TCP Null Flooding: In this type of attack the invader send packets that have the no TCP segment flags set
(six possible) which is invalid. This type of section may be used in port scanning.It is generally degrading
in nature.Following are the six TCP flags :
URG (U) – indicates that the Urgent pointer field is noteworthy
ACK (A) – indicates that the Acknowledgment field is noteworthy. All packets after the initial SYN packet
sent by the client should have this flag set.
PSH (P) – Push function. Asks to push the buffered data to the receiving application.
RST (R) – Reset the connection
SYN (S) – Synchronize sequence numbers. Only the first packet sent from each end should have this flag
set. Some other flags and fields modify meaning based on this flag, and some are only valid for when it is
set, and others when it is clear.
FIN (F) – No more data from sender.
4. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 71 | Page
C. Internet Layer DDoS Attack: These types of attacks occur due to vulnerability in internet layer protocols
of the TCP/IP model. They are following:
a) Smurf Attack :In this type of attack, large numbers of Internet Control Message Protocol (ICMP) packets
with the intended victim's spoofed source IP are broadcast to a computer network using an IP Broadcast
address. This attack is disgrading in nature. It is shown below :
Fig. 5: Smurf Attack
b) Fraggle Attack :It is similar to smurf attack but insted of ICMP packets,large numbers of UDP packets
with the intended victim's spoofed source IP are broadcast to a computer network using an IP Broadcast
address.This attack is disgrading in nature.
c) TearDrop Attack :It involves sending fragmented packets to a target machine. Since the machine
receiving such packets cannot reassemble them due to a bug in TCP/IP fragmentation reassembly, the
packets overlap one another, crashing the target network device.This attack is disgrading in nature.It is
shown below :
Fig. 6: Tear Drop Attack
In fig 6. there are three normal fragmented IP packets are having size 1500 bytes whereas the teardrop
fragmented packets have varying sizes of 1700 bytes,1699 bytes and 1900 bytes respectively.When these
teardrop fragmented packets are send to viictim machine,the machine will remain busy in assembling these
fragments and will end up in denying services to other legitimate clients.Since these packets have different
sizes,the machine is not able to reassemble these packets.
5. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 72 | Page
d) ICMP Flooding: Attacker overwhelms the victim with ICMP Echo Request (ping) packets.The attacker
hopes that the victim will respond with ICMP Echo Reply packets, thus consuming both outgoing
bandwidth as well as incoming bandwidth. If the target system is slow enough, enough CPU cycles can be
consumed and the user notices a significant slowdown.This attack is disgrading in nature.It is shown
below :
Fig.7: ICMP Flooding
D. Network Access Layer DDoS Attack: These type of attacks exploit the weakness of network layer and its
protocols.Followng are the major types of DDoS attacks falls under this category:
a) VLAN Hopping: VLAN hopping is a computer security exploit, a method of attacking networked
resources on a Virtual LAN (VLAN). This attack is disruptive in nature.As shown in fig 9. the attacker
launches VLAN hopping attack by spoffing Dynamic Trunking Protocol(DTP) messages and causes the
switch to enter trunking mode.
Fig.8: VLAN Hopping
b) MAC Flooding : MAC flooding is a method engaged to compromise the security of network switches.This
attack is disgrading in nature.
c) DHCP Attack : Attacker avert hosts from gaining access to the network by refuting them an IP address by
overwhelming all of the available IP address in the DHCP Pool.This attack is disruptive in nature.It is
shown below :
6. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 73 | Page
Fig.9: DHCP Attack
d) ARP Spoofing: ARP spoofing is a type of attack in which a malevolent actor sends falsified ARP (Address
Resolution Protocol) messages over a local area network. This attack is disgrading in nature.Fig. 10 shows
normal ARP traffic pattern. The sniffer snorts the traffic and sends malicious ARP messages to the target
computer as shown in fig.11
Fig.10 ARP Attack Normal Traffic
Fig.11: ARP Attack Malicious Traffic
7. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 74 | Page
Following are the reasons for speedy growth of Application Layer DDoS Attacks:
These attacks are some of the most difficult attacks to alleviate against because they impersonate human
behavior as they interrelate with the user interface.
Attacker requires less resources and needs only information of susceptible IP and ports.
Difficult to stop because they look authentic to classic firewalls which let them pass freely.
Defending this classification of attack is difficult because network devices like switches,routers etc have no
security at application layer.
IV. Existing Tools And Comparison
A. Low Orbit Ion Canon(LOIC): LOIC performs a denial-of-service (DoS) attack (or when used by many
individuals, a DDoS attack) on a target site by flooding the server with TCP or UDP packets with the intent
of disrupting the service of a precise host. People have used LOIC to connect intended botnets.LOIC unveil
a DDoS attack by using the various flooding method e.g. TCP, UDP and ICMP in order to harm the
resources such as CPU time, storage and bandwidth of the compromising host.[3]
B. Mstream: The purpose of the tool is to enable impostors to utilize multiple Internet connected systems to
launch packet flooding denial of service attacks against one or more target systems. The Mstream tool uses
tricking method for attacking the target host. For example using small TCP Acknowledge packets to attack
the victim site. Mstream tool uses TCP ACK floods that, as a response, can marsh the information used by
routing methods in switches.[4]
C. Switchblade: It provides three dissimilar types of denial of service situations that can be tested from a
single machine[5]
SSL Half Connect: This type of attack works by driving the server to do tasks that take up a lot of resources
over and over again until it runs out of resources to do that task with (often RAM and CPU power) and then
clatters or stops doing its envisioned function.
HTTP Post Attack: The attacker creates hundreds or even thousands of such connections, until all resources
for arriving connections on the server (the victim) are used up, hence building any further (including
legitimate) connections difficult until all data has been sent.
Slowloris: This attack works by introducing multiple connections to the targeted web server and keeping
them open as lengthy as possible. It does this by constantly sending restricted HTTP requests, none of
which are ever accomplished. The confronted servers open more and connections open, waiting for each of
the attack requests to be accomplished.
LOIC MSTREAM SWITCHBLADE
LOIC launch a DDoS attack by
using the various flooding
method e.g. TCP, UDP and
ICMP in order to damage the
resources such as CPU time,
storage and bandwidth of the
compromising host.
Mstream tool uses TCP ACK
floods that, and gains the
Information used by routing
methods in switches.
OWASP Switchblade is a
denial of service tool used for
testing the availability,
performance and capacity
planning of a web application
to be proactive about
this type of risk condition.
Types of flooding provided by
it are
TCP SYN, UDP, ICMP.
It provides TCP SYN , ICMP
and
RST
It provides UDP, TCP SYN,
ICMP
Disruptive in nature. Degrading in nature Disruptive in nature
Fig.12: Comparison of DDoS Tools
V. Defense Mechanisms
1. Ingress/Egress Filtering: Ingress filtering is an tactic to set up a router such that to prohibit incoming
packets with illegitimate source addresses into the network[6].It averts source IP address spoofing of
Internet traffic.This mechanism can considerably reduce the DoS attack by IP spoofing if all domains use it.
Sometimes legitimate traffic can be rejected by an ingress filtering using Mobile IP[7] Egress filtering [8]
is an outbound filter, which certifies that only assigned or allocated IP address space leaves the network.
Egress filters do not help to save resource wastage of the domain where the packet is originated but it
protects other domains from possible attacks.
8. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 75 | Page
Fig.13: Network Ingress/Egress Filtering
2. Route Based Distributed Packet Filtering: This methodology is capable of filtering out a huge portion of
deceived IP packets and averting attack packets from accomplishing their targets as well as to help in IP
traceback. Route-based filters use the route statistics to filter out spoofed IP packets, making this their main
modification from ingress filtering. If route-based filters are partially positioned,a synergistic sifting effect
is possible, so that spoofed IP flows are prohibited from reaching other Autonomous Systems.
3. History Based IP Filtering: According to this method the edge router disclose the incoming packets
according to a pre-built IP address database. The IP address database is based on the edge router former
connection history. This scheme is healthy, does not need the support of the whole Internet community, and
is appropriate to a wide variety of traffic types and requires little arrangement.[9]
4. Load Balancing: Load balancing[10] is a simple method that enables network providers to upsurge the
provided bandwidth on serious connections and prevent them from going down in the occurrence of an
attack. Additionally the duplication of servers can be done for guaranteed protection during a DDoS attack.
5. Intrusion Detection: Intrusion detection systems sense DDoS attacks either by using the database of well-
known signatures or by recognizing glitches in system behaviors.[11]Anomaly detection trusts on detecting
behaviors that are irregular with respect to some normal standard. Following are some anomaly detection
systems and methods have been developed to detect the weak signs of DDoS attacks:
Signature Based
Pattern Based
6. Deflection: It includes the following techniques:
Honeypots: They are the technologies that are not supposed to receive any legitimate traffic. Traffic
designed to a honeypot is possibly an ongoing attack that can be investigated to expose vulnerabilities
targeted by attackers.
Attack Study: Honeypots have special software which regularly collects data about the system performance
for forensic analysis. Honeypots are permitted to be compromised and behave as a normal machine,
noiselessly capturing valuable information about the activities of attacker.
Roaming Honeypots: Unlike classic honeypots,these can be located at service-level, where the locations of
honeypots are unexpectedly changing within a pool of back-end servers.
7. Data Logging: Vital information can be obtained from the network components (such as firewalls, packet
sniffers, log-servers) as these components registers the incident details about the attack, during forensics
analysis. If attacker has done significant financial damage,law enforcement policies can also be assissted.
8. Congestion Triggered Packet Filtering: In this technique,a subset of packets which are released due to
overcrowding is selected for statistical analysis. If any problem is shown by the statistical results, a signal is
sent to the router to filter the detrimental packets.
9. IP Traceback: IP traceback hints the attacks back towards their origin, so that the attacker can be validated
and mysterious routes can be detected, as well as path categorization. Key factor that makes IP traceback
challenging is the homeless nature of Internet routing. Other problem can be lack of source liability in the
TCP/IP protocol.[11] At a very simple level, the administrator of the network under attack places a call to
his Internet Service Provider (ISP) requesting for the direction from which the packets are coming. Since
the manual traceback is very tiresome, process computerization is needed.Probabilistic packet marking
(PPM) is used to interpret partial route path information proficiently and include the traceback data in IP
9. Survey Of DDoS Attacks Based On TCP/IP Protocol Vulnerabilities
DOI: 10.9790/0661-1803046876 www.iosrjournals.org 76 | Page
packets. This technique can be functional during or after an attack, and it does not need any supplementary
network traffic, router storage, or packet size increase. Even though it is not dreadful to reconstruct an well-
ordered network path using an unordered collection of router samples, it needs the victim to obtain a large
amount of packets.
VI. Conclusion
Internet has touched such places where people could not even think that such kind of network exists
which offer any possibly imaginable information.With the increased use of internet, a huge number of attackers
are keeping an eye to launch attacks to get entrée to critical information and even crash the complete
servers.There are systems whose vulnerabilities can be easily exploited by the attackers and they use them to
perform DDoS attacks.We provide a review on DDoS attacks classified according to vulnerabilites in the
TCP/IP protocols.We also provide a review on common DDoS attack tools and their comparison.DDoSattacks
are difficult to remove completely but they can be prevented and also a review on common DDoS defense
mechanisms is given.
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