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.
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
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 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.
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.
This document discusses distributed denial of service (DDoS) attacks and potential defenses. It describes how DDoS attacks work by flooding a victim with useless traffic from many compromised systems to overwhelm the victim's bandwidth or resources. The document outlines different types of DDoS attacks like direct and reflector attacks. It also discusses challenges with detection and prevention, such as the difficulty of filtering reflected packets or widely deploying packet filters across networks. Promising defense approaches include developing a global firewall infrastructure with distributed detection systems that can identify anomalies and coordinate response. However, effective DDoS defense remains an ongoing challenge.
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 .
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.
This document discusses various internet security threats such as viruses, worms, rootkits, scanners, IP spoofing, session hijacking, and botnet attacks. It also covers basic concepts of DNS, how TCP connections are established, and types of denial of service attacks. Specific techniques like passive and active session hijacking and how botnets use command and control infrastructures are described in more detail.
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
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 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.
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.
This document discusses distributed denial of service (DDoS) attacks and potential defenses. It describes how DDoS attacks work by flooding a victim with useless traffic from many compromised systems to overwhelm the victim's bandwidth or resources. The document outlines different types of DDoS attacks like direct and reflector attacks. It also discusses challenges with detection and prevention, such as the difficulty of filtering reflected packets or widely deploying packet filters across networks. Promising defense approaches include developing a global firewall infrastructure with distributed detection systems that can identify anomalies and coordinate response. However, effective DDoS defense remains an ongoing challenge.
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 .
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.
This document discusses various internet security threats such as viruses, worms, rootkits, scanners, IP spoofing, session hijacking, and botnet attacks. It also covers basic concepts of DNS, how TCP connections are established, and types of denial of service attacks. Specific techniques like passive and active session hijacking and how botnets use command and control infrastructures are described in more detail.
Session hijacking involves taking control of an authorized user's session by obtaining their session ID. There are several methods, including TCP session hijacking, which can be done through blind hijacking or man-in-the-middle attacks. TCP session hijacking with packet blocking modifies the route table or ARP table to intercept packets. Tools like Hunt can hijack sessions through ARP attacks. Prevention methods include encryption, as used in SSH and TLS, and storm watching to detect abnormal network traffic increases that could indicate hijacking.
This document discusses various network attacks and their mitigations. It begins with a list of common attacks like TCP SYN flood, ICMP flood, ARP spoofing, Smurf attack, IP fragmentation, TCP hijacking, and reflector attacks. It then provides descriptions and usage instructions for tools used in attacks, including hping3, Scapy, Ettercap, and Wireshark. The document proceeds to explain each attack in more detail and provides potential prevention and mitigation techniques. It focuses on techniques like firewall configuration, SYN cookies, ICMP flood protection, private VLANs, filtering, encryption, and VPNs.
A denial-of-service attack (DoS attack) or distributed denial-of-service attack (DDoS attack) is an attempt to make a computer resource unavailable to its intended users. Although the means to carry out, motives for, and targets of a DoS attack may vary, it generally consists of the concerted efforts of a person or people to prevent an Internet site or service from functioning efficiently or at all, temporarily or indefinitely. Perpetrators of DoS attacks typically target sites or services hosted on high-profile web servers such as banks, credit card payment gateways, and even root name servers. The term is generally used with regards to computer networks, but is not limited to this field, for example, it is also used in reference to CPU resource management. There are two general forms of Dos attacks: those that crash services and those that flood services.
One common method of attack involves saturating the target machine with external communications requests, such that it cannot respond to legitimate traffic, or responds so slowly as to be rendered effectively unavailable. In general terms, DoS attacks are implemented by either forcing the targeted computer to reset, or consuming its resources so that it can no longer provide its intended service or obstructing the communication media between the intended users and the victim so that they can no longer communicate adequately.
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.
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.
Time-based DDoS Detection and Mitigation for SDN ControllerLippo Group Digital
This document proposes a method to detect and mitigate distributed denial of service (DDoS) attacks on software defined networking (SDN) controllers using time-based characteristics. The method considers not only the malicious packet destination but also the time needed to achieve high traffic rates and periodic attack patterns. The proposed solution architecture monitors packet rates over time windows to detect abnormal traffic increases. Future work includes optimizing detection thresholds, deeper analysis of DDoS attack time patterns, and evaluation of the method's performance in a simulation.
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 types of network attacks, including buffer overflow attacks and TCP session hijacking. It provides details on:
- Passive attacks like traffic analysis that aim to release confidential message contents.
- Active attacks like interruption, modification, and fabrication that can disrupt network services.
- Buffer overflow occurring when a program writes more data to a fixed-length memory block, potentially corrupting data or executing malicious code.
- TCP session hijacking where an attacker gains access to an active session between two machines by predicting sequence numbers or using a man-in-the-middle attack to intercept packets.
1) The document describes a proposed SDN-based system to detect and prevent DDoS attacks. It uses entropy calculations on traffic flow statistics to detect attacks. When an attack is detected, the controller installs rules to block traffic from bot IPs and the server uses CAPTCHAs to authenticate legitimate users.
2) The system was tested using iperf and attack tools on an emulation platform. Results showed it maintained high throughput even during attacks, unlike approaches that overload the controller. It also had lower false positives than other detection algorithms.
3) Future work could include expanding the system to detect attacks targeting different SDN layers and more servers. The approach provides an effective and scalable DDoS defense for
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.
The document discusses various techniques for computer network attacks, including IP fragmentation attacks, sniffers, session hijacking, and DNS cache poisoning. IP fragmentation can be used to bypass firewalls and intrusion detection systems. Sniffers are tools that capture network traffic, which attackers use to gather passwords and escalate access. Session hijacking allows stealing interactive user sessions. DNS cache poisoning tricks DNS servers into providing incorrect IP addresses to redirect users. Defenses include encryption, authentication, firewalls, and securing DNS servers.
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 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.
Distributed reflection denial of service attacks, or DrDoS attacks, increased significantly in 2013. Uniquely, reflection attacks have two victims – the unwilling third-party server that is compelled to launch DDoS attack traffic and the attackers’ intended DDoS target. For both victims the effect is similar – slow performance or an outage that prevents legitimate users from accessing your site. This infographic from Prolexic explains why DrDoS attacks are on the rise and best practices to stop them.
Network defenses include tools like firewalls, VPNs, and intrusion detection systems that help secure networks and protect them from cyber attacks. Firewalls act as barriers that control incoming and outgoing network traffic according to security policies. VPNs extend private networks over public networks through secure tunnels. Intrusion detection systems monitor network traffic and detect suspicious activity. Denial of service attacks aim to make network services unavailable by overwhelming them with malicious traffic. Distributed denial of service attacks use multiple compromised systems to launch large-scale attacks.
A computer network plays a major part in the development of any industry. Nowadays, in this fast paced
networking world each and every industry depends on internet for their progress. As said above this is the fast
paced world, the attack to disable the progress are also fast paced. DDoS (Distributed Denial of Service) is one
among them. Though it is one of the many attacks, they temporarily disable a service provided by the company.
This paper proposes a series of steps which not only checks the possible attack but also tries its best to thwart
them. Instead of going for conventional approach of blocking the excess traffic, the proposed approach will
prolong the access to the service. In the mean time checking for the possible attack is done. Thus, not only it
thwarts the attacks but also gives them reliable user their access with a little bit of delay, resulting in high
reliability.
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.
This document summarizes a research article that presents a novel robust reversible watermarking method for copyright protection of images. The proposed method, called wavelet-domain statistical quantity histogram shifting and clustering (WSQH-SC), aims to improve upon existing reversible watermarking methods by addressing issues with reversibility, robustness, and invisibility.
WSQH-SC consists of four main modules: 1) property inspired pixel adjustment to avoid pixel overflow/underflow during embedding, 2) construction of statistical quantity histograms in the wavelet domain for embedding, 3) an enhanced pixel-wise masking technique to optimize watermark strength based on human visual perception, and 4) watermark extraction based on k-means clustering. The authors
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 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.
Session hijacking involves taking control of an authorized user's session by obtaining their session ID. There are several methods, including TCP session hijacking, which can be done through blind hijacking or man-in-the-middle attacks. TCP session hijacking with packet blocking modifies the route table or ARP table to intercept packets. Tools like Hunt can hijack sessions through ARP attacks. Prevention methods include encryption, as used in SSH and TLS, and storm watching to detect abnormal network traffic increases that could indicate hijacking.
This document discusses various network attacks and their mitigations. It begins with a list of common attacks like TCP SYN flood, ICMP flood, ARP spoofing, Smurf attack, IP fragmentation, TCP hijacking, and reflector attacks. It then provides descriptions and usage instructions for tools used in attacks, including hping3, Scapy, Ettercap, and Wireshark. The document proceeds to explain each attack in more detail and provides potential prevention and mitigation techniques. It focuses on techniques like firewall configuration, SYN cookies, ICMP flood protection, private VLANs, filtering, encryption, and VPNs.
A denial-of-service attack (DoS attack) or distributed denial-of-service attack (DDoS attack) is an attempt to make a computer resource unavailable to its intended users. Although the means to carry out, motives for, and targets of a DoS attack may vary, it generally consists of the concerted efforts of a person or people to prevent an Internet site or service from functioning efficiently or at all, temporarily or indefinitely. Perpetrators of DoS attacks typically target sites or services hosted on high-profile web servers such as banks, credit card payment gateways, and even root name servers. The term is generally used with regards to computer networks, but is not limited to this field, for example, it is also used in reference to CPU resource management. There are two general forms of Dos attacks: those that crash services and those that flood services.
One common method of attack involves saturating the target machine with external communications requests, such that it cannot respond to legitimate traffic, or responds so slowly as to be rendered effectively unavailable. In general terms, DoS attacks are implemented by either forcing the targeted computer to reset, or consuming its resources so that it can no longer provide its intended service or obstructing the communication media between the intended users and the victim so that they can no longer communicate adequately.
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.
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.
Time-based DDoS Detection and Mitigation for SDN ControllerLippo Group Digital
This document proposes a method to detect and mitigate distributed denial of service (DDoS) attacks on software defined networking (SDN) controllers using time-based characteristics. The method considers not only the malicious packet destination but also the time needed to achieve high traffic rates and periodic attack patterns. The proposed solution architecture monitors packet rates over time windows to detect abnormal traffic increases. Future work includes optimizing detection thresholds, deeper analysis of DDoS attack time patterns, and evaluation of the method's performance in a simulation.
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 types of network attacks, including buffer overflow attacks and TCP session hijacking. It provides details on:
- Passive attacks like traffic analysis that aim to release confidential message contents.
- Active attacks like interruption, modification, and fabrication that can disrupt network services.
- Buffer overflow occurring when a program writes more data to a fixed-length memory block, potentially corrupting data or executing malicious code.
- TCP session hijacking where an attacker gains access to an active session between two machines by predicting sequence numbers or using a man-in-the-middle attack to intercept packets.
1) The document describes a proposed SDN-based system to detect and prevent DDoS attacks. It uses entropy calculations on traffic flow statistics to detect attacks. When an attack is detected, the controller installs rules to block traffic from bot IPs and the server uses CAPTCHAs to authenticate legitimate users.
2) The system was tested using iperf and attack tools on an emulation platform. Results showed it maintained high throughput even during attacks, unlike approaches that overload the controller. It also had lower false positives than other detection algorithms.
3) Future work could include expanding the system to detect attacks targeting different SDN layers and more servers. The approach provides an effective and scalable DDoS defense for
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.
The document discusses various techniques for computer network attacks, including IP fragmentation attacks, sniffers, session hijacking, and DNS cache poisoning. IP fragmentation can be used to bypass firewalls and intrusion detection systems. Sniffers are tools that capture network traffic, which attackers use to gather passwords and escalate access. Session hijacking allows stealing interactive user sessions. DNS cache poisoning tricks DNS servers into providing incorrect IP addresses to redirect users. Defenses include encryption, authentication, firewalls, and securing DNS servers.
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 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.
Distributed reflection denial of service attacks, or DrDoS attacks, increased significantly in 2013. Uniquely, reflection attacks have two victims – the unwilling third-party server that is compelled to launch DDoS attack traffic and the attackers’ intended DDoS target. For both victims the effect is similar – slow performance or an outage that prevents legitimate users from accessing your site. This infographic from Prolexic explains why DrDoS attacks are on the rise and best practices to stop them.
Network defenses include tools like firewalls, VPNs, and intrusion detection systems that help secure networks and protect them from cyber attacks. Firewalls act as barriers that control incoming and outgoing network traffic according to security policies. VPNs extend private networks over public networks through secure tunnels. Intrusion detection systems monitor network traffic and detect suspicious activity. Denial of service attacks aim to make network services unavailable by overwhelming them with malicious traffic. Distributed denial of service attacks use multiple compromised systems to launch large-scale attacks.
A computer network plays a major part in the development of any industry. Nowadays, in this fast paced
networking world each and every industry depends on internet for their progress. As said above this is the fast
paced world, the attack to disable the progress are also fast paced. DDoS (Distributed Denial of Service) is one
among them. Though it is one of the many attacks, they temporarily disable a service provided by the company.
This paper proposes a series of steps which not only checks the possible attack but also tries its best to thwart
them. Instead of going for conventional approach of blocking the excess traffic, the proposed approach will
prolong the access to the service. In the mean time checking for the possible attack is done. Thus, not only it
thwarts the attacks but also gives them reliable user their access with a little bit of delay, resulting in high
reliability.
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.
This document summarizes a research article that presents a novel robust reversible watermarking method for copyright protection of images. The proposed method, called wavelet-domain statistical quantity histogram shifting and clustering (WSQH-SC), aims to improve upon existing reversible watermarking methods by addressing issues with reversibility, robustness, and invisibility.
WSQH-SC consists of four main modules: 1) property inspired pixel adjustment to avoid pixel overflow/underflow during embedding, 2) construction of statistical quantity histograms in the wavelet domain for embedding, 3) an enhanced pixel-wise masking technique to optimize watermark strength based on human visual perception, and 4) watermark extraction based on k-means clustering. The authors
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 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 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 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 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 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 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 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 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.
Simulasi perhitungan PPh 21 untuk pegawai PT Candra Kirana bernama Budi Karyanto dengan gaji Rp3 juta per bulan, status menikah tanpa anak, dan memiliki iuran pensiun dan asuransi dari perusahaan dan pribadi. Hasil perhitungan menunjukkan pajak yang harus dipotong per bulan sebesar Rp28.452."
Teks tersebut memberikan penjelasan tentang berbagai jenis shalat sunnah yang dianjurkan untuk dikerjakan, baik secara berjamaah maupun sendiri. Jenis-jenis shalat sunnah yang disebutkan antara lain shalat Idul Fitri, Idul Adha, gerhana matahari, gerhana bulan, dan memohon hujan. Tata cara pelaksanaan masing-masing jenis shalat sunnah pun dijelaskan secara singkat.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
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 study analyzed the fuzzy reliability of serum prolactin response to TRH during antithyroid treatment in hyperthyroid patients based on a fuzzy gamma distribution. The α-cut sets of the fuzzy reliability function were determined using incomplete gamma functions. Testing 10 patients before and after treatment, the study found increases in maximum prolactin response to TRH in 9 patients after treatment. This suggests changes from normal thyroid hormone levels are associated with changes in prolactin response, based on the fuzzy probability curve of the α-cut reliability analysis.
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 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 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.
DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACKS DETECTION MECHANISMijcseit
Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the router’s resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a
promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the
puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host.
DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACKS DETECTION MECHANISM ijcseit
Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS
attacks are treated as a congestion-control problem, but because most such congestion is caused by
malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the
routers. Functionality is added to each router to detect and preferentially drop packets that probably
belong to an attack. Upstream routers are also notified to drop such packets in order that the router’s
resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a
promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim
server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is
assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the
puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving
technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the
destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid
scheme called Router based Pushback technique, which involves both the techniques to solve the problem
of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core
routers rather than having at the victim. The router based client puzzle mechanism checks the host system
whether it is legitimate or not by providing a puzzle to be solved by the suspected host.
This document discusses various internet security threats such as viruses, worms, rootkits, scanners, IP spoofing, session hijacking, and botnet attacks. It also covers basic concepts of DNS, how TCP connections are established, and definitions of denial of service attacks. Specific techniques like passive and active session hijacking and how botnets function through command and control centers are described in more detail.
This document discusses various types of denial of service (DoS) and distributed denial of service (DDoS) attacks, including their characteristics and techniques. It provides examples of specific DoS attacks like Smurf, Teardrop, Ping of Death and SYN attacks. The document also covers buffer overflow vulnerabilities and SQL injection attacks. It discusses countermeasures to mitigate these threats.
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
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 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.
what is transport layer what are the typical attacks in transport l.pdfbrijeshagarwa329898l
what is transport layer? what are the typical attacks in transport layer? what are the controls that
are employed in the layer to minimize the attack or vulnerability that leads to the attack? cite
references
Solution
Transport Layer:-
In computer networking, the transport layer is a conceptual division of methods in the layered
architecture of protocols in the network stack in the Internet Protocol Suite and the Open
Systems Interconnection (OSI). The protocols of the layerprovide host-to-host communication
services for applications.
Typical attacks in transport layer:-
1. SESSION HIJACKING: Session Hijacking is commonly known as TCP session Hijacking is a
way of taking over a secure/ unsecure web user session by secretly obtaining user’s session ID
and pretending to be the authorized user for accessing the data. How it works and types: Session
hijacking works by taking advantage of the fact that most communications are protected (by
providing credentials) at session setup, but not thereafter. These attacks generally fall into three
categories: Man-in-the-middle (MITM), Blind Hijack, and Session Theft. In MITM attacks, an
attacker intercepts all communications between two hosts. With communications between a
client and server now flowing through the attacker, he or she is free to modify their content.
Protocols that rely on the exchange of public keys to protect communications are often the target
of these types of attacks. In blind hijacking, an attacker injects data such as malicious commands
into intercepted communications between two hosts commands like “net.exe local group
administrators /add Evil Attacker”. This is called blind hijacking because the attacker can only
inject data into the communications stream; he or she cannot see the response to that data (such
as “The command completed successfully.”) Essentially, the blind hijack attacker is shooting
data in the dark, but as you will see shortly, this method of hijacking is still very effective. In a
session theft attack, the attacker neither intercepts nor injects data into existing communications
between two hosts. Instead, the attacker creates new sessions or uses old ones. This type of
session hijacking is most common at the application level, especially Web applications. Main
features are: -URL (Uniform resource locator) -Cookies -Session ID The cookies stores the
previous records of the users and the URL logs can give the current visited site, a hacker take
benefits from it and hacks user’s session ID through it, after doing that it pretends to be the
authorized user and accesses the data. A cookie usually is a piece of text sent by a server to the
web client and sent back unchanged by the client, each time it access the data. 1.1 Methods used
to perform session hijacking: 1.1.1IP Spoofing: It basically means taking identity of someone
else to perform some task, in this the attacker pretends to be the authorized user and access some
confidential information, not only this, the.
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.
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.
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.
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 .
Detection of application layer ddos attack using hidden semi markov model (20...Mumbai Academisc
This document discusses a proposed scheme to detect application layer distributed denial of service (App-DDoS) attacks using hidden semi-Markov models. It begins by describing how current techniques have difficulty distinguishing App-DDoS attacks from normal flash crowds based on traffic characteristics alone. The proposed scheme aims to capture spatial-temporal patterns during normal flash crowds using an Access Matrix, and then uses a hidden semi-Markov model to analyze dynamics of the Access Matrix and detect anomalies indicating potential App-DDoS attacks. It argues this approach can more effectively identify if traffic surges are caused by attackers or normal users compared to existing detection systems.
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.
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.
Avoiding Man in the Middle Attack Based on ARP Spoofing in the LANEditor IJCATR
As technology is running on its wheels, networking has turned into one of our basic aspects. In this world along with
networking inimical vulnerabilities are also advancing in a drastic manner, resulting in perilous security threats. This calls for the great
need of network security. ARP spoofing is one of the most common MITM attacks in the LAN. This attack can show critical
implications for internet users especially in stealing sensitive information’s such as passwords. Beyond this it can facilitate other
attacks like denial of service(DOS), session hijacking etc..,. In this paper we are proposing a new method by encrypting MAC address
to shield from ARP cache poisoning
Security involves ensuring data integrity, availability, and confidentiality against threats. It can be computer or network security. Data integrity means data cannot be modified without authorization. Availability means information systems and data are accessible when needed. An information security management system (ISMS) follows the PDCA cycle of plan, do, check, act to manage security risks and ensure business continuity. ISO/IEC 27000 standards provide guidance for implementing an ISMS.
Malware Hunter: Building an Intrusion Detection System (IDS) to Neutralize Bo...Editor IJCATR
Among the various forms of malware attacks such as Denial of service, Sniffer, Buffer overflows are the most dreaded threats to computer networks. These attacks are known as botnet attacks and self-propagating in nature and act as an agent or user interface to control the computers which they attack. In the process of controlling a malware, Bot header(s) use a program to control remote systems through internet with the help of zombie systems. Botnets are collection of compromised computers (Bots) which are remotely controlled by its originator (Bot-Master) under a common Command-and-Control (C&C) structure. A server commands to the bot and botnet and receives the reports from the bot. The bots use Trojan horses and subsequently communicate with a central server using IRC. Botnet employs different techniques like Honeypot, communication protocols (e.g. HTTP and DNS) to intrude in new systems in different stages of their lifecycle. Therefore, identifying the botnets has become very challenging; because the botnets are upgrading their methods periodically for affecting the networks. Here, the focus on addressing the botnet detection problem in an Enterprise Network
This research introduces novel Solution to mitigate the malicious activities of Botnet attacks through the Principle of component analysis of each traffic data, measurement and countermeasure selection mechanism called Malware Hunter. This system is built on attack graph-based analytical models based on classification process and reconfigurable through update solutions to virtual network-based countermeasures.
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GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
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Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
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Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
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One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
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• Phases in Communication Mining
• Demo on Platform overview
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Essentials of Automations: The Art of Triggers and Actions in FME
Aw36294299
1. Prof Tushar D. Kolhe et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.294-299
RESEARCH ARTICLE
www.ijera.com
OPEN ACCESS
Distributed Denial Of Service Attack Techniques: Analysis,
Implementation And Comparison
Prof Tushar D. Kolhe, Prof. Minal T. Kolhe
Assistant Professor Department of Computer Engineering K.C.E.S’S C.O.E.I.T. Jalgaon (MH)
Assistant Professor Department of Computer Engineering K.C.E.S’S C.O.E.I.T. Jalgaon (MH)
Abstract
A denial of service attack (DOS) is any type of attack on a networking structure to disable a server from
servicing its clients. Attacks range from sending millions of requests to a server in an attempt to slow it down,
flooding a server with large packets of invalid data, to sending requests with an invalid or spoofed IP address. In
this paper we show the comparative analysis of various types of attacks: namely Ping of Death, Connection
Flood, TCP SYN Flood, Distributed DOS and others. This paper will demonstrate the potential damage from
DOS attacks and analyze the ramifications of the damage. The paper concludes with suggested mitigation
methods for some of the discussed attacks.
Keywords- DDOS attack, Spoof attack, TCP-SYN, Flooding, PUSH-ACK.
systems and network port openings to gain access.
The more ports that are open, the more points of
I. INTRODUCTION
Denial of services attacks (DOS) is a constant
danger to modern day Servers. DOS has received
vulnerability To determine which ports are open on a
increased attention as it can lead to a severe lost of
given system, a program called port scanner is
revenue if sites are taken offline for a substantial
used[2]. A port scanner runs through a series of ports
amount of time. In a denial-of-service (DoS) attack,
to see which ones are open. Usually a machine in
an attacker attempts to prevent legitimate users from
TCP/IP stack has 65,535 TCP ports and 65,535 UDP
accessing information or services[1][2]. By targeting
ports. The number of ports combined has a potential
computers and its network connection, or the
doorway into the system. Normally, major services
computers and network of the sites, an attacker may
listen on fixed port number with the list of open ports
be able to block accessing of emails, websites, online
on a target system. Using this information, the
accounts (banking, etc.), or other services that rely on
attacker can get an idea of which services are in use
the affected computer. In a distributed denial-ofby checking RFC 1700, “Assigned numbers”. In the
service (DDoS) attack, an attacker may use a
Windows environment, one good scanner is called
particular computer to attack another computer. By
Scan port. This is a fairly basic port scanner but it
taking advantage of security vulnerabilities or
enables the attacker to specify both the range of
weaknesses, an attacker could take control of that
addresses and range of ports to scan. On the Unix
particular computer. He or she could then force that
side, the best scanner is Nmap. This program scans
computer to send huge amounts of data to a website
for open ports by sending packets to the target system
or send spam to particular email addresses. The
to interact with each port. What type of packets is
attack is "distributed" because the attacker is using
sent and how does interaction happen depend on type
multiple computers, to launch the denial-of-service
of scan being conducted. Some of the types of scan
attack. Many types of DDOS attacks are prevalent.
are as follows.
The paper discusses the methodologies, signs and
possible preventions of the existing known attacks.
TCP Connect: Completes the three-way
handshake with each scanned port.
II. DDOS ATTACK MECHANISM
TCP Syn: Only sends the initial SYN and awaits
The DDoS attack operates through a client
SYN-ACK response to determine if the port is
machine by hacking into weakly secured computers.
open.
This is done by searching and finding well-known
UDP scan: Sends a UDP packet to target ports to
defects in standard network service programs and
determine if a UDP service is listening.
commonly weak configurations in known operating
systems. But before that attacker can start, the
Ping: Sends ICMP Echo request to every
attacker scans these systems looking for
machine on the target network, for
vulnerabilities. Unfortunately, this phase very much
locating live hosts. After the vulnerability scan is
favours the attackers. The attacker uses computer
done on the target system, a list of vulnerabilities
is given to the attacker could exploit. The reason
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behind the scan is to automate the process of
connecting to a target system and checking to see
if the vulnerabilities are present. Another scan
tool called Nessus scans random IP addresses to
find a known vulnerability. After the scan, a list
of victim systems is created that shares the same
common vulnerability.
After the scan, the attacker chooses a number of
machines to be involved in the attack. These systems
are also known as handlers or masters[2]. Now the
attacker can find a way to gain access and have
significant control over these machines.
Most
common method is using Stack Based buffer
overflow attack. Any application or operating system
component that is poorly written could have this
problem. A buffer overflow attack happens when an
attacker tries to store too much information in an
undersized receptacle. Buffer overflow takes
advantage of the way in which data is stored by
computer programs. When a program calls a
subroutine, the function variable and the subroutine
returns address pointers stored in a logical data
structure known as stack. A stack is a portion of
memory, which stores information about the current
program needs and contains the address where the
program returns after the subroutine has completed
execution.
When the buffer is overflowed, the data placed there
goes into neighboring variable space and eventually
into the pointers space. To cause the attacker’s code
to be executed, the attacker precisely tunes the
amount and content of data to cause buffer overflow
and stack to crash. The data the attacker sends
usually consists of machine specific byte code to
execute a command plus a new address for return
pointer. This address points back into the address
space of stack, causing the program to run the
attacker’s instruction when it returns from the
subroutine. To help improve the odds that the return
pointer will jump to a good place to begin executing
the attacker’s code, attackers will often prepend a
series of NOP (no processing) instruction to their
machine level code. A key point is that attacker code
will run at whatever privileges the software that is
exploited is running at. In most cases, attacker tries
to exploit program running as root or administrator
privilege. So attacker can easily install backdoor on
a system in this way. The captured machines are now
instructed to control another set of captured machines.
These are called the agents or daemons. By doing this,
it ensures a measure of cautiousness on the part of the
attacker. Now it is very difficult and impossible to
track and find the actual attacker on the Internet. The
attacker comprises more systems until the risk of
being captured is almost impossible. At the end, the
attacker knows the addresses of all the nodes and
stores them in a file on his control system. This is
later used to attack the victim.
After the attacker breaks into the system, they
want to be able to get back into victim’s system
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whenever they want. They could achieve this by
installing a backdoor entry as in step 2 or by
installing a rootkit (very common in Unix operating
system). A rootkit is like a trojan key system files on
an operating system. The attacker can replace the
login program by overwriting it, but it would be
obvious someone messed up the system so a
legitimate user could not gain access. To avoid this,
the attacker could add some feature into existing
login program like allowing someone to have root
access without prompting for a password; it would be
hard for the administrator to detect their system has
been comprised. In general, rootkit provide false
information or lie to the administrator to hide what
the attacker is doing. The rootkit masks attack
activity going on the background.
So finally the actual attack takes place. The
attacker on his computer using client software sends
instructions to the handlers or nodes to launch a
particular attack. These attacks come from variety of
different flooding attacks against specific victim.
III.
EXISTING ATTACK MECHANISMS
A.1 SYN Flood
A SYN flood is a form of denial-of-service attack
in which an attacker sends a succession of SYN
requests to a target's system in an attempt to consume
enough server resources to make the system
unresponsive to legitimate traffic[3]. Normally when a
client attempts to start a TCP connection to a server,
the client and server exchange a series of messages
which normally runs like this:
The client requests a connection by sending a SYN
(synchronize) message to the server.
The server acknowledges this request by sending
SYN-ACK back to the client.
The client responds with an ACK, and the
connection is established.
This is called the TCP three-way handshake, and is
the foundation for every connection established using
the TCP protocol. A SYN flood attack works by not
responding to the server with the expected ACK code.
The malicious client can either simply not send the
expected ACK, or by spoofing the source IP address
in the SYN, causing the server to send the SYN-ACK
to a falsified IP address - which will not send an ACK
because it "knows" that it never sent a SYN. The
server will wait for the acknowledgement for some
time, as simple network congestion could also be the
cause of the missing ACK, but in an attack
increasingly large numbers of half-open connections
will bind resources on the server until no new
connections can be made, resulting in a denial of
service to legitimate traffic. Some systems may also
malfunction badly or even crash if other operating
system functions are starved of resources in this way.
A.2 ICMP flood, ping flood, smurf attack
In a smurfing attack, a network amplifier is used
create a flood of traffic to target a victim system. The
attack begins with a ping packet sent to some system,
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which supports direct broadcast messages known as a
network amplifier[4]. A network amplifier is usually
a system on the Internet with an incorrect configured
network. The source address of the packet is spoofed
to be that of the victim system. Spoofing is a way for
the attacker to send messages to IP address, which
says that the message was from a trusted host. By
doing this, all the ping responses are sent to the victim
system. Using the network amplifier with 50 hosts, 50
packets can be sent to the victim by just sending one
packet. Network amplifier will receive packet by
packet until the maximum amount of traffic is sent.
This is because the network amplifier itself has a fixed
bandwidth connection to the Internet. At the end, the
attack will be traced back to the network amplifier and
not the attacker.
Smurf attacks rely on a directed broadcast to create
a flood of traffic for a victim on a particular IP
address. An IP address is made of host address and
network address. If the host part of address is all 1’s
then the packet is destined for broadcast address of the
network. For example, if the network IP address of the
network were 10.1.0.0 with net mask of 255.255.0.0,
the broadcast IP address for the network would be
10.1.255.255. Using 255 consecutively means there is
a message for network IP address because host
contains 16 consecutive 1s. This in turn will cause
every machine on destination LAN to read the packet
and send a response.
The packets sent by the attacker are ICMP ECHO
REQUESTS. Normally if the packet’s destination
network router allows direct broadcasts, all
destination LANs will receive the packet. Once
received, these machines will then send a ping
response. By sending 1 packet, thousands of response
packets can be sent. If the first ping response were
from spoofed address then all ping responses from the
network would be sent to the spoofed address. The
number of response packets will increase with more
machines on the network that allow direct
broadcasting. Using this idea an attacker can conduct
a smurfing attack.
A similar attack to smurfing is the fraggle attack.
Fraggle is similar that the attacker sends packets
through network amplifier but differ by using UDP
ECHO packets rather than ICMP ECHO packets. The
attack begins with packets sent to IP broadcast
address. The destination is UDP port set to a service,
which can send the response. The service that receives
the packet just sends the packet back exactly as
received. By doing this, all machines will echo UDP
traffic back causing a flood of the victim’s system
expresses the probability of X item sets and Y item
sets appear in D affair at the same time.
A.3 UDP Flooding:
User Datagram Protocol (UDP) is a
connectionless protocol. When sending data packets
through UDP, no handshake is required between the
sender and receiver. The receiving party will receive
packets to process. If a large number of UDP packets
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are sent, this could cause the victim system to be
saturated. This in turn would reduce the bandwidth
amount available for legitimate users on the
system[5].
When the attacker uses UDP flood attack, UDP
packets are sent to either random or specified ports on
a victim system. Most of the time they are sent to
random ports. When the packets are sent, it causes the
victim system to process the incoming data. The
system then has to determine which application sent
the request. If no applications were running on
targeted port, the victim system would send out ICMP
packet indicating the destination port is unreachable.
As with smurfing, UDP flooding uses spoofed IP
address when sending the attacking packet. By doing
this, the return packets are sent to another system with
spoofed address and not sent back to zombie systems.
Another side effect of UDP flood attacks is that these
attacks can fill the bandwidth connection around the
victim system causing those systems to experience
problems with their connectivity.
A.4 Push –Ack Attack
In the TCP protocol, packets that are sent to a
destination are buffered within the TCP stack and
when the stack is full, the packets get sent on to the
receiving system. However, the sender can request
the receiving system to unload the contents of the
buffer before the buffer becomes full by sending a
packet with the PUSH bit set to one. PUSH is a onebit flag within the TCP header. TCP stores incoming
data in large blocks for passage on to the receiving
system in order to minimize the processing overhead
required by the receiving system each time it must
unload a non-empty buffer. The PUSH + ACK attack
is similar to a TCP SYN attack in that its goal is to
deplete the resources of the victim system. The
attacking agents send TCP packets with the PUSH
and ACK bits set to one. These packets instruct the
victim system to unload all data in the TCP buffer
(regardless of whether or not the buffer is full) and
send an acknowledgement when complete. If this
process is repeated with multiple agents, the receiving
system cannot process the large volume of incoming
packets and it will crash.
A.5 Low-bandwidth HTTP denial of service
attacks
An undefended modern web server is a surprisingly
vulnerable target for very simple HTTP attacks such
as the Slowloris script. Slowloris works by opening
connections to a web server and then sending just
enough data in an HTTP header (typically 5 bytes or
so) every 299 seconds to keep the connections open,
eventually filling up the web server’s connection
table. Because of its slow approach, it can be a
devious attack, remaining under the radar of many
traffic-spike attack detection mechanisms[6]. Against
a single, typical web server running Apache 2,
Slowloris achieves denial-of-service with just 394
open connections2. Like Slowloris, the Slowpost
attack client uses a slow, low-bandwidth approach.
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Instead of sending an HTTP header, it begins an
HTTP POST command and then feeds in the payload
of the POST data very, very slowly. Because the
attack is so simple, it could infect an online Javabased game, for instance, with millions of user, then
becoming unwitting participants in an effective,
difficult-to-trace, low bandwidth DDoS attack.
A third low-bandwidth attack is the HashDos
attack. In 2011, this extremely powerful DoS
technique was shown to be effective against all major
web server platforms, including ASP.NET, Apache,
Ruby, PHP, Java, and Python3. The attack works by
computing form variable names that will hash to the
same value and then posting a request containing
thousands of the colliding names. The web server’s
hash table becomes overwhelmed, and its CPU spends
all its time managing the collisions. The security
professionals exploring this attack demonstrated that a
single client with a 30 Kbps connection could tie up
an Intel i7 core for an hour. They extrapolated that a
group of attackers with only a 1 Gbps connection
could tie up 10,000 i7 cores indefinitely. If a web
server is terminating SSL connections, it can be
vulnerable to the SSL renegotiation attack. This attack
capitalizes on the SSL protocol’s asymmetry between
the client and server. Since the server must do an
order of magnitude more cryptographic computation
than the client to establish the session, a single SSL
client can attack and overwhelm a web server with a
CPU of the same class. Rounding out the category of
low-bandwidth attacks are simple HTTP requests that
retrieve expensive URLs. For example, an attacker
can use automated reconnaissance to retrieve metrics
on download times and determine which URLs take
the most time to fetch. These URLs can be then be
distributed to a small number of attacking clients.
Such attacks are very difficult to detect and
mitigate, turning any weak points in an application
into a new attack vector
IV.
DDOS DETECTION AND POSSIBLE
MITIGATION METHODS
Distributed denial-of-service (DDoS) attack types
have moved up the OSI network model over time,
climbing from network attacks in the 1990s to session
attacks and application layer attacks today. Network
attacks include DDoS variants such as SYN floods,
connection floods, or ICMP fragmentation. Session
attacks, which target layers 5 and 6, include DNS and
SSL attacks. Application attacks at layer 7 represent
approximately half of all attacks today. Finally,
though layer 7 tops the OSI model, attacks are now
moving into business logic, which often exists as a
layer above the OSI model. But even with these
changes in the current threat spectrum, organizations
must continue to defend against network and session
attacks, too.
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Fig 1. DDoS attacks target many layers of the OSI
network model.
Fig 2. Network attacks target layers 2 through 4.
The most basic network attacks attempt to
overwhelm a defensive device with sheer volumes of
traffic. Sometimes these volumetric attacks are
designed to overload the connections-per-second
(CPS) capacity (e.g., the ramp-up rate). Another,
slightly more sophisticated attack method is to
establish many legitimate connections (a connection
flood) to overwhelm the memory of any stateful
defensive devices so they lose the ability to accept
legitimate connections. Listed below are some of the
methodologies which can be instrumental in detecting
and mitigating a suspected DDOS attack
A.1 Counter measure against SYN Flood:
One of the more well-known countermeasures
against a SYN flood is the use of "SYN cookies",
typically used in DDoS engines and load balancers to
create another level of protocol security for Denial of
Service attacks. A SYN cookie is a specific choice of
initial TCP sequence number by TCP software and is
used as a defence against SYN Flood attacks.[7]
In normal operation, a Client sends a SYN and the
Server responds with a SYN+ACK message, the
server will then hold state information in the TCP
stack while waiting for Client ACK message. A
simple SYN flood (using suitable software) will
generate SYN packets which would consume all
available TCP memory as the server must maintain
state for all half-open connections. And since this
state table is finite the server will no longer accept
new TCP connections and thus fail or deny service to
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the user. This is highly leveraged attack since a very
small amount of bandwidth and CPU can exhaust the
resources on a large number of servers. The TCP
sequence number at the commencement of a TCP
sequence is normally a randomised choice. The TCP
sequence is what NMAP uses to identify the OS since
it ‘knows’ the some OS’s do not have high quality
randomisation and NMAP uses algorithms to analyse
the ISN to ‘guess’ the OS. This is part of the functions
of a PIX/ASA firewall, it will improve the
randomness of the ISN to ensure If the ACK response
is not correct the TCP session is not created. The
effect is that SYN floods will no longer consume
resources on servers or load balancers/ This is
especially true in high bandwidth environments such
as Data Centres.
By specifically calculating the TCP sequence
number with a specific, secret math function in the
SYN-ACK response, the server does not need to
maintain this state table. On receipt of the ACK from
the Client, the TCP sequence number is checked
against the function to determine if this is a legitimate
reply. If the check is successful, then the server will
create the TCP session and the user connection will
proceed as normal
A.2 Countermeasures against HTTP/UDP Flood
An effective defense against an HTTP flood can
be the deployment of a reverse proxy[8]. In particular
a collection of reverse proxies spread across multiple
hosting locations, deciding which packets are allowed
to where the real web server is. By deploying many
proxies, the crush of incoming traffic is split into
fractions, lessening the possibility of the network
becoming overwhelmed. Deploying this type of
architecture can be done in the scramble after an
attack has begun, or baked into the network
architecture of a web site as a preventative defense.
The key to fast denial of UDP floods historically has
been the default-deny security posture. Any packets
that do not match a defined virtual server are dropped
as quickly as possible, thus mitigating UDP floods.
No UDP packets ever reach HTTP-based applications.
A.3 Countermeasures against PUSH –ACK Attack
Solutions built atop a full-proxy architecture can be
active security agents because their architecture
makes them part of the flow of traffic, not simply
devices sampling that traffic. Products that are full
proxies provide inherently better security because
they actively terminate the flow of data, essentially
creating an “air gap” security model inside the
product, thereby preventing attacks like PUSH-ACK
attacks. With full proxies, traffic coming from the
client can be examined before it is sent on its way to
the application tier, ensuring that malicious traffic
never passes the proxy barrier. Traffic returning from
the server can be fully examined before it is deemed
acceptable to pass back to the client, thereby ensuring
that sensitive data such as credit card or Social
Security numbers are never passed across the proxy
barrier. A full-proxy can mitigate PUSH and ACK
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floods. Because it will be a part of every conversation
between every client and every server, it can
recognize packets that do not belong to any valid
flow, such as typical PUSH and ACK flood packets.
These are dropped quickly and never pass beyond the
ADC.
A.4 Countermeasures against Smurf and Tear Drop
attacks
One of the few layer 3 attacks still in use today is
the ICMP flood. Often these floods are triggered by
amplifying ICMP echo replies from a separate
network to a target host. This can be mitigated by
limiting the rates of all ICMP traffic and then
dropping all ICMP packets beyond the limit. The limit
is adjustable by the operator. [9][10][11]
A teardrop attack exploits an overlapping IP
fragment problem in some common operating
systems. It causes the TCP reassembly code to
improperly handle overlapping IP fragments. It can be
handled by correctly checking frame alignment and
discarding improperly aligned fragments. Teardrop
packets then are dropped and the attacks are mitigated
before the packets can pass into the data center.
V. CONCLUSION
In this review research, we have given a comparative
analysis of various DDOS attack mechanisms. We
have also discussed possible methods of detection
and also some possible methods of mitigation of
some of these attacks. However, these attacks are
becoming sophisticated by the day and low
bandwidth attacks like Slowloris and Pyloris are
becoming a serious threat to systems all over the
world. Advanced and Strong architectures need to be
built in servers with strict protocol validation rules to
make sure the modern day systems are protected.
.
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