Relevant bibliographies by topics / Syn flooding attack

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Syn flooding attack'

Author: Grafiati
Published: 3 June 2025
Last updated: 7 July 2025

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Journal articles on the topic "Syn flooding attack"

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Ramanauskaitė, Simona, and Antanas Čenys. "STOCHASTIC MODEL OF TCP SYN ATTACKS / STOCHASTINIS TCP SYN ATAKŲ MODELIS." Mokslas - Lietuvos ateitis 3, no. 1 (2011): 20–24. http://dx.doi.org/10.3846/mla.2011.004.

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A great proportion of essential services are moving into internet space making the threat of DoS attacks even more actual. To estimate the real risk of some kind of denial of service (DoS) attack in real world is difficult, but mathematical and software models make this task easier. In this paper we overview the ways of implementing DoS attack models and offer a stochastic model of SYN flooding attack. It allows evaluating the potential threat of SYN flooding attacks, taking into account both the legitimate system flow as well as the possible attack power. At the same time we can assess the effect of such parameters as buffer capacity, open connection storage in the buffer or filte­ring efficiency on the success of different SYN flooding attacks. This model can be used for other type of memory depletion denial of service attacks.
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Ali, Hamid M., Ibraheem K. Ibraheem, and Sarah W. A. Ahmad. "Enhancement of the Detection of the TCP SYN Flooding (DDoS) Attack." Journal of Engineering 19, no. 6 (2023): 786–94. http://dx.doi.org/10.31026/j.eng.2013.06.10.

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The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mechanism is proposed to protect the server from TCP SYN flooding. The results show that the defense against SYN flood DDoS attack is enhanced, since the availability of legitimate packets is increased and the time of SYN Cookie activity is delayed.
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Sun, Fei Xian, and Zhi Gang Wu. "Immune Danger Theory Based Model for SYN Flooding Attack Situation Awareness." Advanced Materials Research 181-182 (January 2011): 66–71. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.66.

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This paper explores a novel danger theory based model to aware the situation for TCP SYN flooding attacks. Within in the presented model, the TCP SYN flooding attacks are looked as dangerous exogenous patterns, and induce danger signals to aware the situation of host computers, which is realized by hosted-based artificial immune detectors. After summarizing the danger theory, the model framework, correlative concepts, TCP SYN flooding attack detection, danger signal computation and attack situation awareness methods are described. Following that, the interrelated techniques are compared. Theoretical analysis results show that the proposed model is valid. Thus, it provides a good solution to computer network security.
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Mohd Fuzi, Mohd Faris, Nur Fatin Mohammad Ashraf, and Muhammad Nabil Fikri Jamaluddin. "Integrated Network Monitoring using Zabbix with Push Notification via Telegram." Journal of Computing Research and Innovation 7, no. 1 (2022): 147–55. http://dx.doi.org/10.24191/jcrinn.v7i1.282.

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The world is becoming increasingly dependent on online services. To offer a service, a network must be in good health and free of any attacks. An attack happens when the confidentiality, integrity, or availability of a service is compromised. Network monitoring is a solution capable of maintaining these network devices from their usage up to detecting attacks. A denial of service (DoS) attack on a network can affect the network performance and can cause serious damage. Zabbix is an open-source network monitoring tool that is versatile and can be used to monitor hosts on a network. The purpose of this project is to detect possible ping and SYN flooding attempts on a server and send alerts to the administrator via Telegram. This project uses Zabbix to monitor a server for potential ping and SYN flooding attacks. Tcpdump is used to log the pings received by the server. When the server continuously receives 10 or more pings per second, an alert will be automatically generated and sent to the administrator via Telegram. Similarly, a SYN flood attack is detected by using netstat’s SYN_RECV flags. When the server continuously receives more than 10 SYN packets without an ACK packet, Zabbix will generate alerts that are sent via Telegram and update the dashboard to show a problem. Zabbix was able to accurately detect all ping flooding attempts on the server. However, SYN flooding attacks were not as accurately detected. The use of Zabbix can be implemented in small businesses or networks for an automated monitoring system. Future work can include more DDoS attacks and adding countermeasure actions when detecting attacks by blocking the IP or port associated with the attack. SYN flooding detection needs to be improved because only two out of three attacks were able to be caught.
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Yang, Chun-Hao, Jhen-Ping Wu, Fang-Yi Lee, Ting-Yu Lin, and Meng-Hsun Tsai. "Detection and Mitigation of SYN Flooding Attacks through SYN/ACK Packets and Black/White Lists." Sensors 23, no. 8 (2023): 3817. http://dx.doi.org/10.3390/s23083817.

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Software-defined networking (SDN) is a new network architecture that provides programmable networks, more efficient network management, and centralized control than traditional networks. The TCP SYN flooding attack is one of the most aggressive network attacks that can seriously degrade network performance. This paper proposes detection and mitigation modules against SYN flooding attacks in SDN. We combine those modules, which have evolved from the cuckoo hashing method and innovative whitelist, to get better performance compared to current methods Our approach reduces the traffic through the switch and improves detection accuracy, also the required register size is reduced by half for the same accuracy.
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Lee, Se-Yul, and Yong-Soo Kim. "Design and Analysis of Probe Detection Systems for TCP Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 4 (2004): 369–72. http://dx.doi.org/10.20965/jaciii.2004.p0369.

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Advanced computer network technology enables the connectivity of computers in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and cannot detect new hacking patterns, making it vulnerable to previously unidentified attack patterns and variations in attack and increasing false negatives. Intrusion detection and prevention technologies are thus required. We propose a network-based intrusion detection model using fuzzy cognitive maps (FCM) that detects intrusion by Denial of Service (DoS) attack detection using packet analysis. A DoS attack typically appears as a Probe and Syn Flooding attack. Syn Flooding Preventer using Fuzzy cognitive maps (SPuF) model captures and analyzes packet information to detect Syn flooding attacks. Using the result of decision module analysis, which used FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulation using the "KDD’99 Competition Data Set" for the SPuF model shows that Probe detection exceeded 97%.
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Manna, Mehdi Ebady. "Review Of Syn-Flooding Attack Detection Mechanism." International Journal of Distributed and Parallel systems 3, no. 1 (2012): 99–117. http://dx.doi.org/10.5121/ijdps.2012.3108.

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Jose, Ancy Sherin, Latha R. Nair, and Varghese Paul. "Towards Detecting Flooding DDOS Attacks Over Software Defined Networks Using Machine Learning Techniques." Revista Gestão Inovação e Tecnologias 11, no. 4 (2021): 3837–65. http://dx.doi.org/10.47059/revistageintec.v11i4.2411.

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Distributed Denial of Service Attack (DDoS) has emerged as a major threat to cyber space. A DDoS attack aims at exhausting the resources of the victim causing financial and reputational damages to it. The availability of free software make launching of DDoS attacks easy. The difficulty in differentiating a DDoS traffic from a legitimate traffic burst such as a flash crowd makes DDoS difficult to be identified. A wide range of techniques have been used in conventional networks to detect and mitigate DDoS attacks. Though the advent of Software Defined Networking (SDN) makes a network easy to be managed even SDN is vulnerable to DDoS attacks. In this case, the controller of the SDN gets overloaded with the incoming packets from the switches. In fact, a solution based on security analytics can be put in place to ward off this threat as a proactive security measure using the flow level statistics available from the SDN. Compared to the packet analysis used in traditional networks which is resource expensive the flow level statistics is relatively inexpensive. This paper focuses on the design and implementation of an attack detection system for detecting the flooding DDoS attacks TCP SYN flooding attacks, HTTP request flooding attacks, UDP flooding attacks and ICMP flooding attacks over SDN network traffic. The system uses various classification algorithms to classify a traffic into normal or attack. The feature sets for classification were arrived at using a feature selection module with ANOVA (Analysis of Variance) F-Test statistical method. Performance evaluation of each of the classifiers was carried out for the three feature sets obtained from the feature selection module using various performance measures and the results have been tabulated. The feature set which gives the best performance in detecting malicious traffic has been identified.
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Azis, Muhammad Misbahul, Yufiz Azhar, and Syaifuddin Syaifuddin. "Analisa Sistem Identifikasi DDoS Menggunakan KNN Pada Jaringan Software Defined Network(SDN)." Jurnal Repositor 2, no. 7 (2020): 915. http://dx.doi.org/10.22219/repositor.v2i7.762.

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AbstrakAbstrak - Kebutuhan pada jaringan mengutamakan performa untuk mendukung sebuah efisiensi jaringan merupakan hal penting untuk saat ini. Penentuan konfigurasi yang semakin banyak dan kompleks serta kontrol jaringan yang semakin rumit, membuat jaringan semakin tidak fleksibel dan susah untuk diterapkan pada sebuah topologi jaringan yang besar. Software Defined Network (SDN) muncul dengan mekanisme yang dapat menyelesaikan masalah tersebut. Pada dasarnya konsep dari Software Defined Network (SDN) adalah memisahkan kontroller dan data/forwarding plane, sehingga mampu untuk me-menejemen jaringan yang begitu banyak dalam sebuah kontroller. Namun pada kontroller belum memiliki keamanan yang cukup untuk melindungi dari serangan jaringan seperti DDoS, SYN Flooding Attack sehingga kontroller akan menjadi target dari attacker. Sehingga penelitian ini mengusulkan penambahan aplikasi machine learning pada kontroller untuk menangani serangan seperti DDoS dan SYN Flooding Attack. Dalam penelitian ini kontroller yang digunakan adalah ryu controller yang menggunakan bahasa pemrograman python. Dalam penelitian ini menggunakan topologi linear pada mininet dan membuat paket dalam format .pcap untuk pengujian serangan yang dilakukan. Sehingga dapat mengetahui rata-rata jumlah paket yang masuk dan keluar dan keberhasilan dalam melakukan mitigasi terhadap paket yang dianggap DDoS.Abstract The need for the network to prioritize performance to support a network efficiency is important for now. Determination of configurations that are more and more complex and increasingly complicated network control, makes the network more inflexible and difficult to apply to a large network topology. Software Defined Network (SDN) appears with a mechanism that can solve the problem. Basically the concept of Software Defined Network (SDN) is to separate the controller and the data / forwarding plane, so that it is able to manage so many networks in a controller. But the controller does not have enough security to protect against network attacks such as DDoS, SYN Flooding Attack so the controller will be the target of the attacker. So this study proposes adding machine learning applications to controllers to handle attacks such as DDoS and SYN Flooding Attack. In this study the controller used is the Ryu controller that uses the Python programming language. In this study using a linear topology on Mininet and create a package in. Pcap format for testing attacks carried out. So as to know the average number of incoming and outgoing packages and success in mitigating packages that are considered DDoS.
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Bellaïche, Martine, and Jean-Charles Grégoire. "SYN flooding attack detection by TCP handshake anomalies." Security and Communication Networks 5, no. 7 (2011): 709–24. http://dx.doi.org/10.1002/sec.365.

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Dissertations / Theses on the topic "Syn flooding attack"

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Dudek, Jindřich. "Detekce síťových útoků pomocí nástroje Tshark." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385934.

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This diploma thesis deals with the design and implementation of a tool for network attack detection from a captured network communication. It utilises the tshark packet analyser, the meaning of which is to convert the input file with the captured communications to the PDML format. The objective of this conversion being, increasing the flexibility of input data processing. When designing the tool, emphasis has been placed on the ability to expand it to detect new network attacks and on integrating these additions with ease. For this reason, the thesis also includes the design of a complex declarative descriptions for network attacks in the YAML serialization format. This allows us to specify the key properties of the network attacks and the conditions for their detection. The resulting tool acts as an interpreter of proposed declarative descriptions allowing it to be expanded with new types of attacks.
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Sun, Jia-Rong, and 孫加榮. "The Study on Investigation Procedure of Cybercrime for SYN Flooding Attack." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/58659357419922884220.

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博士<br>亞洲大學<br>資訊工程學系<br>103<br>The cybercrime with the development of networks, it has many crime types, include network attack, mail fraud, intimidation, copyright infringement, and so on. For network attack, many approaches have been proposed to detect and defense. However, after confirm the network attack or others crime exist, it still needs to execute the investigation procedure by the investigators, collect the evidences related to the crime, find the perpetrators, and prosecute them. This study aims to propose a new cybercrime investigation approach, which is used to find the criminal (attacker) and direct digital evidences after the Distributed Denial of Service (DDoS) attack happened. We improve the conventional investigation procedure, and collect the digital evidences and compare repeatedly, finding the high possible suspects. After this, we collect the digital evidences and others crime information from victims and ISP, and use to prove the suspects ever commit the crime fact. At the same time, we will prove the probative force of the collected digital evidences, which will be same with the evidences from search and seize. Therefore, by using our investigation procedure, we wish it will help the investigators to find the suspects and strong evidences without search and seize, saving the judicial resources. Furthermore, we collect the court judgments of cybercrime in recent years, and describe the recent status of cybercrime and cybercrime judgments. And then, we will propose the detection approaches for detect SYN flooding attack. In the detection approaches, they include two detection approaches, MISO (Multi-input Single-output) policy and MIMO (Multi-input Multi-output) policy. These two detection approach improve the problems of detection approach based on Entropy, and make them can be used to the wider connection environment. In the future, the types, methods, and targets of cybercrime will be changed continues, every types of computer, network equipment, and smart phone will be the target of attack. It focuses on how the current cybercrime investigation methods combined with digital evidence collection. And even set up a defense method in the investigation process, to achieve an effective network for crime prevention, detection and investigation purposes.
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Wei, Hung-Chuan, and 魏鴻娟. "Counteracting UDP Flooding Attacks in SDN." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/56753540948380371723.

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碩士<br>元智大學<br>資訊工程學系<br>104<br>Software-defined networking (SDN) is a new network architecture with the central control. The purpose is to allow network to become more flexible and easier to manage. Besides, the need for the resources and services of applications can have better also management. SDN architecture is to separate the control plane and data plane. Control plane uses a controller to centrally manage SDN switch, while the data plane handles only data transmission, which can reduce the difficulty of management. SDN using OPENFLOW protocol to connect the control plane and data plane, so that when the packet enters first into the flow table, the matching flows can be forwarded directly. SDN has been proven successful in improving not only network performance but also network security. However, the centralized control in SDN architecture incurs new security vulnerabilities. Because all of the management functionality are in the controller, the UDP flooding attack can be easily launched and causes serious packet transmission delay, performance loss on the controller and therefore even network shutdown. Therefore, in this thesis, for UDP flood attack, we will carry out a simulation to prove flooding attack can harm the controller. After that, the defense presented a lightweight method is presented. Via the experiments, we demonstrate the performance and safety of our proposed defense mechanism. The advantage of our defense is that it will not incur too much computation and communication burden if no attack is launched. The controller itself has no need to be modified with our defense mechanism. In particular, our defense can always monitor the status of the controller. If necessary, add flow table rules to ensure normal operation of the controller and the network.
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Chen, Fu-ping, and 陳復平. "A Novel TCP Implementation for Defending Against TCP SYN Flooding Attacks." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/45765546490259627806.

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碩士<br>義守大學<br>資訊工程學系碩士班<br>93<br>With the rapid growth and increasing popularity of the Internet and E-Commerce, Denial of Service (DoS) attacks have become one of new criminal actions. More are TCP SYN Flood attacks, since the attackers can easily take advantage of the TCP specification to generate traffic making the services of public servers unavailable. Each time a client attempts to create a connection with a server, some connection state information is stored on the server. Since the connection state information stored requires memory and operating system resources, only a limited number of in progress connections are allowed. The TCP SYN attack sends a constant stream of TCP connection requests to overwhelm the server, forcing the server to allocate resources for each new connection until all resources are exhausted. As a result, the server is unable to respond to legitimate connections. Therefore, the thesis proposes a stateless connection mechanism to defend the TCP SYN Flooding attacks. Instead of storing state information in server’s memory, the new mechanism stores the state information in the sequence number of a SYN/ACK packet. The mechanism determines the accuracy of an ACK packet by checking the received sequence number in the ACK packet. The thesis presents three sequence number generating methods, from the simplest one to a more complicated means, for enhancing the security of a server. For demonstrating the correctness of the proposed mechanism, furthermore, the thesis implements it by modifying the kernel program of FreeBSD. Experimental results show that our proposed mechanism can defend servers from SYN Flooding attacks, improve the security of a server, and provide normal services to legitimate users.
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Tzeng-Yu, Chen. "An Effective Intrusion Prevention System to Protect Multi-Services against TCP SYN Flooding DDoS Attacks." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0016-1303200709313176.

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Chen, Tzeng-Yu, and 陳宗右. "An Effective Intrusion Prevention System to Protect Multi-Services against TCP SYN Flooding DDoS Attacks." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/36453050738828817765.

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碩士<br>國立清華大學<br>資訊工程學系<br>94<br>In recent years, DDoS attacks occur frequently and cause a great deal of damage to enterprises that provide network services. With the growth of the network, almost every enterprise provides more and more services on the network, like Web service, Mail service, Ftp service, and so on. If these services suffer the DDoS attack, it will cause great losses to the enterprise. The famous type of the DDoS attack is TCP SYN flooding attack and it is based on the vulnerability of the TCP three-way handshake. The firewall and intrusion detection system are not effectively to defend this type of attack. There is still not a completed solution to defend this attack. In this thesis, we collect the legitimate IP addresses in the databases for each service and protect these services according to these databases. We also create a backlog queue for each service that we can detect the attack by checking it. When attack is detected, the packet filtering mechanism will be activated to protect the victim services. There are five characteristics in our system: (1) Protecting multi-service without knowing any information about these services. (2) Detecting the attack and activate the packet filter instantly. (3) The complexity of IP searching algorithm is only O (n), where n is the number of the under-attack service. It will reduce the delay of the legitimate users. (4) We can instantly find that the attacker uses the legitimate IP address to do the attack and then we filter out this IP address. (5) The system can be built in edge router, NAT server or the protected server. With our proposed mechanism, we can effectively defend the TCP SYN flooding attack and successfully provide the service for legitimate users. Finally, we will do the experiment to evaluate this mechanism and analyze the system performance, effectiveness and influence of the legitimate users. We will show that this mechanism is effectively to protect multi-service against TCP SYN flooding attack.
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Rasool, Raihan Ur. "CyberPulse: A Security Framework for Software-Defined Networks." Thesis, 2020. https://vuir.vu.edu.au/42172/.

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Software-Defined Networking (SDN) technology provides a new perspective in traditional network management by separating infrastructure plane from the control plane which facilitates a higher level of programmability and management. While centralized control provides lucrative benefits, the control channel becomes a bottleneck and home to numerous attacks. We conduct a detailed study and find that crossfire Link Flooding Attacks (LFA) are one of the most lethal attacks for SDN due to the utilization of low-rate traffic and persistent attacking nature. LFAs can be launched by the malicious adversaries to congest the control plane with low-rate traffic which can obstruct the flow rule installation and can ultimately bring down the whole network. Similarly, the adversary can employ bots to generate low-rate traffic to congest the control channel, and ultimately bring down the control plane and data plane connection causing service disruption. We present a systematic and comparative study on the vulnerabilities of LFAs on all the SDN planes, elaborate in detail the LFA types, techniques, and their behavior in all the variant of SDN. We then illustrate the importance of a defense mechanism employing a distributed strategy against LFAs and propose a Machine Learning (ML) based framework namely CyberPulse. Its detailed design, components, and their interaction, working principles, implementation, and in-depth evaluation are presented subsequently. This research presents a novel approach to write anomaly patterns and makes a significant contribution by developing a pattern-matching engine as the first line of defense against known attacks at a line-speed. The second important contribution is the effective detection and mitigation of LFAs in SDN through deep learning techniques. We perform twofold experiments to classify and mitigate LFAs. In the initial experimental setup, we utilize Artificial Neural Networks backward propagation technique to effectively classify the incoming traffic. In the second set of experiments, we employ a holistic approach in which CyberPulse demonstrates algorithm agnostic behavior and employs a pre-trained ML repository for precise classification. As an important scientific contribution, CyberPulse framework has been developed ground up using modern software engineering principles and hence provides very limited bandwidth and computational overhead. It has several useful features such as large-scale network-level monitoring, real-time network status information, and support for a wide variety of ML algorithms. An extensive evaluation is performed using Floodlight open-source controller which shows that CyberPulse offers limited bandwidth and computational overhead and proactively detect and defend against LFA in real-time. This thesis contributes to the state-of-the-art by presenting a novel framework for the defense, detection, and mitigation of LFA in SDN by utilizing ML-based classification techniques. Existing solutions in the area mandate complex hardware for detection and defense, but our presented solution offers a unique advantage in the sense that it operates on real-time traffic scenario as well as it utilizes multiple ML classification algorithms for LFA traffic classification without necessitating complex and expensive hardware. In the future, we plan to implement it on a large testbed and extend it by training on multiple datasets for multiple types of attacks.
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Book chapters on the topic "Syn flooding attack"

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Shin, Seung-won, Ki-young Kim, and Jong-soo Jang. "LSAD: Lightweight SYN Flooding Attack Detector." In Distributed Computing and Internet Technology. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30555-2_45.

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Nalayini, C. M., and Jeevaa Katiravan. "Block Link Flooding Algorithm for TCP SYN Flooding Attack." In International Conference on Computer Networks and Communication Technologies. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8681-6_83.

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Liu, Xinyu, Beumjin Cho, and Jong Kim. "SD-OVS: SYN Flooding Attack Defending Open vSwitch for SDN." In Information Security Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56549-1_3.

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Alipour, H., M. Kashefi Kia, and M. Esmaeili. "Supporting Security against SYN Flooding Attack in Distributed DoS Via Measuring IPFIX-Based Traffic." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69403-8_16.

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Mkuzangwe, Nenekazi Nokuthala Penelope, and Fulufhelo Vincent Nelwamondo. "A Fuzzy Logic Based Network Intrusion Detection System for Predicting the TCP SYN Flooding Attack." In Intelligent Information and Database Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54430-4_2.

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He, Yanxiang, Wei Chen, and Bin Xiao. "Detecting SYN Flooding Attacks Near Innocent Side." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11599463_44.

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Sakthivel, E., R. Anitha, S. Arunachalam, and M. Hindumathy. "Detracting TCP-Syn Flooding Attacks in Software Defined Networking Environment." In Emerging Trends in Computing and Expert Technology. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32150-5_89.

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Xie, Lixia, Ying Ding, and Hongyu Yang. "Mitigating Link-Flooding Attack with Segment Rerouting in SDN." In Cyberspace Safety and Security. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37337-5_6.

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Chahal, Jasmeen Kaur, Abhinav Bhandari, and Sunny Behal. "Analysis of the Impacts of Flooding-Based DDoS Attacks on SDN-Enabled Cloud." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64064-3_14.

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Vetrivelan, P., M. Jagannath, and T. S. Pradeep Kumar. "Network Intrusion Detection and Prevention Systems on Flooding and Worm Attacks." In Advances in Digital Crime, Forensics, and Cyber Terrorism. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0193-0.ch012.

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The Internet has transformed greatly the improved way of business, this vast network and its associated technologies have opened the doors to an increasing number of security threats which are dangerous to networks. The first part of this chapter presents a new dimension of denial of service attacks called TCP SYN Flood attack has been witnessed for severity of damage and second part on worms which is the major threat to the internet. The TCP SYN Flood attack by means of anomaly detection and traces back the real source of the attack using Modified Efficient Packet Marking algorithm (EPM). The mechanism for detecting the smart natured camouflaging worms which is sensed by means of a technique called Modified Controlled Packet Transmission (MCPT) technique. Finally the network which is affected by these types of worms are detected and recovered by means of Modified Centralized Worm Detector (MCWD) mechanism. The Network Intrusion Detection and Prevention Systems (NIDPS) on Flooding and Worm Attacks were analyzed and presented.
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Conference papers on the topic "Syn flooding attack"

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Bosi, Lucas Leal, André Chaves Mendes, Raphael Melo Guedes, and Ronaldo Moreira Salles. "Traffic Classification in Software-Defined Networking (SDN): Application of Machine Learning Models for Flooding DDoS Attack Detection." In 2024 IEEE 3rd Industrial Electronics Society Annual On-Line Conference (ONCON). IEEE, 2024. https://doi.org/10.1109/oncon62778.2024.10931262.

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"SYN Flooding Attack Detection and Mitigation in SDN." In 2019 the 9th International Workshop on Computer Science and Engineering. WCSE, 2019. http://dx.doi.org/10.18178/wcse.2019.03.022.

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Kim, DongHyuk, Phuc Trinh Dinh, Sichul Noh, Junmin Yi, and Minho Park. "An Effective Defense Against SYN Flooding Attack in SDN." In 2019 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2019. http://dx.doi.org/10.1109/ictc46691.2019.8939937.

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Geetha, K., and N. Sreenath. "SYN flooding attack — Identification and analysis." In 2014 International Conference on Information Communication and Embedded Systems (ICICES). IEEE, 2014. http://dx.doi.org/10.1109/icices.2014.7033828.

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Oo, Nan Haymarn, and Aung Htein Maw. "Effective Detection and Mitigation of SYN Flooding Attack in SDN." In 2019 19th International Symposium on Communications and Information Technologies (ISCIT). IEEE, 2019. http://dx.doi.org/10.1109/iscit.2019.8905209.

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Bellaiche, Martine, and Jean-Charles Gregoire. "SYN Flooding Attack Detection Based on Entropy Computing." In GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference. IEEE, 2009. http://dx.doi.org/10.1109/glocom.2009.5425454.

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Kukreti, Sambhavi, Sumit Kumar Modgil, Neha Gehlot, and Vinod Kumar. "DDoS Attack using SYN Flooding: A Case Study." In 2022 9th International Conference on Computing for Sustainable Global Development (INDIACom). IEEE, 2022. http://dx.doi.org/10.23919/indiacom54597.2022.9763108.

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Lin, Ting-Yu, Jhen-Ping Wu, Pei-Hsuan Hung, et al. "Mitigating SYN flooding Attack and ARP Spoofing in SDN Data Plane." In 2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2020. http://dx.doi.org/10.23919/apnoms50412.2020.9236951.

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Qibo, Sun, Wang Shangguang, Yan Danfeng, and Yang Fangchun. "ARM-CPD: Detecting SYN flooding attack by traffic prediction." In Multimedia Technology (IC-BNMT). IEEE, 2009. http://dx.doi.org/10.1109/icbnmt.2009.5348532.

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Sahu, Rakesh Kumar, and Narendra S. Chaudhari. "A performance analysis of network under SYN-flooding attack." In 2012 Ninth International Conference on Wireless and Optical Communications Networks - (WOCN). IEEE, 2012. http://dx.doi.org/10.1109/wocn.2012.6335561.

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Reports on the topic "Syn flooding attack"

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Eddy, W. TCP SYN Flooding Attacks and Common Mitigations. RFC Editor, 2007. http://dx.doi.org/10.17487/rfc4987.

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