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Adaptive distributed mechanism against flooding network attacks based on machine learning

Josep L. Berral, Nicolas Poggi, Javier Alonso, Ricard Gavaldà, Jordi Torres, Manish Parashar
2008 Proceedings of the 1st ACM workshop on Workshop on AISec - AISec '08  
Adaptive techniques based on machine learning and data mining are gaining relevance in selfmanagement and self-defense for networks and distributed systems.  ...  In this paper, we focus on early detection and stopping of distributed flooding attacks and network abuses.  ...  Conclusions and Future Work In order to avoid distributed denial of service attacks and flooding attacks or abuses, we have presented a mechanism based on sharing information and machine learning, which  ... 
doi:10.1145/1456377.1456389 dblp:conf/ccs/BerralPAGTP08 fatcat:mfzxcklxfbg4lapx7y7hsdcswy

Detecting Distributed Denial of Service (DDoS) Attacks through Inductive Learning [chapter]

Sanguk Noh, Cheolho Lee, Kyunghee Choi, Gihyun Jung
2003 Lecture Notes in Computer Science  
The agents can then detect network flooding attacks against a Web server. We validate our framework with experimental results in a simulated TCP-based network setting.  ...  As the complexity of Internet is scaled up, it is likely for the Internet resources to be exposed to Distributed Denial of Service (DDoS) flooding attacks on TCP-based Web servers.  ...  On the other hand, our approach is more general so that our mechanism can be applicable to all types of DDoS attacks, i.e., SYN Flooding attacks, UDP Flooding attacks, ICMP Flooding attacks, and so on.  ... 
doi:10.1007/978-3-540-45080-1_38 fatcat:bwg7fbg62zct5ejao24omlusrm

A Comparative Study of Defense Mechanisms against SYN Flooding Attack

Prathibha R.C, Rejimol Robinson R R
2014 International Journal of Computer Applications  
Distributed Denial-of-Service (DDoS) flooding attacks are a serious threat to the security of the internet. A DDoS attack makes a machine or network resources not usable by the legitimate clients.  ...  A SYN flood is a form of denial-of-service attack.  ...  Adaptive Distributed Mechanism Based on Machine Learning The adaptive distributed mechanism [8] can be used for the detecting and stopping distributed flooding attacks and network abuses early.  ... 
doi:10.5120/17282-7414 fatcat:3watu25dpjeflo3but5lywayhu

Security Framework for IoT Devices against Cyber-Attacks [article]

Aliya Tabassum, Wadha Lebda
2019 arXiv   pre-print
This article explores popular attacks against IoT architecture and its relevant defence mechanisms to identify an appropriate protective measure for different networking practices and attack categories  ...  Various conventional security controls are insufficient to prevent numerous attacks against these information-rich devices.  ...  This model is based on Machine learning techniques which uses learned signature patters of known attacks.  ... 
arXiv:1912.01712v1 fatcat:mqwzm4f5rrhnvaagwmpz62efpm

DDoS detection and prevention based on artificial intelligence techniques

Dragoș Glăvan
2019 Scientific Bulletin of Naval Academy  
Some artificial intelligence techniques like machine learning algorithms have been used to classify DDoS attack traffic and detect DDoS attacks, such as Naive Bayes and Random forest tree.  ...  In the paper, we survey on the latest progress on the DDoS attack detection using artificial intelligence techniques and give recommendations on artificial intelligence techniques to be used in DDoS attack  ...  based on machine learning.  ... 
doi:10.21279/1454-864x-19-i1-018 doaj:7e6681b8d1b44e39afc8005271345ea5 fatcat:hhqrydf2a5e3dg3zw4r7o5gdpq

Design of an Adaptive Distributed Critical-Care Extensive Response Network (AD-CERN) Using Cooperative Overlay Network

V. Akilandeswari, S. Mercy Shalinie
2014 International Journal of Distributed Sensor Networks  
In this network, each node will be trained independently based on Naïve Bayes classification algorithm to react against any critical services in the network.  ...  It controls the flow of high rate critical services such as Distributed Denial of Services (DDoS) flooding attacks and blocks the unwarranted services without any interruption to legitimate users.  ...  Further, they would like to place on record their sincere thanks and gratitude to Tata Consultancy Services, Chennai, for their generous financial assistance to their study.  ... 
doi:10.1155/2014/754898 fatcat:vjmhsyrdofad5myb262ozgwdga

Application Layer DDoS Attack Defense Methods and A new Defense Mechanism against Flooding

2020 International journal of recent technology and engineering  
This paper here follows, we analyze the different defense mechanisms for application-layer DDoS attacks and proposes a new approach to defend using machine learning.  ...  In a network environment, Distributed Denial of Service (DDoS) attacks eemploys a network or server is unavailable to its normal users.  ...  Adaptive Selective Verification (ASV) mechanism used to countermeasure DDoS Attack to Network Layer into Application Layer also by stimulating possible attacks such as HTTP PRAGMA ATTACK, GET FLOOD ATTACK  ... 
doi:10.35940/ijrte.f6986.038620 fatcat:yh3hzcqhcbhrxnzbzquuyvxble


Mujahid shah
Distinguishing between attack traffic and normal traffic is difficult, especially in the case of a application layer attack such as a botnet performing a HTTP Flood attack against a victim's server.  ...  In a DoS attack, its one system that is sending the malicious data or requests; a DDoS attack comes from multiple systems. Generally, these attacks work by drowning a system with requests for data.  ...  Then, based on traffic a Modified Multi-chart adaptive and protocol g attacks.  ... 
doi:10.26782/jmcms.2019.12.00075 fatcat:nmydxblxijasrlh3oj24nhdwna

DoS/DDoS Detection for E-Healthcare in Internet of Things

Iftikhar ul, Maaz Bin, Muhammad Asif, Rafi Ullah
2018 International Journal of Advanced Computer Science and Applications  
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks on E-Health servers in IoT would endanger real-time monitoring of patients and also overall reliability of the E-Health services  ...  In this paper, existing solutions to DoS/DDoS attacks in IoT have been reviewed and a reliable solution is presented for securing the servers against these attacks.  ...  Some researchers have also tried machine learning approaches to learn the different models for detection of attack which reflects that the use of conventional network analysis techniques alone are not  ... 
doi:10.14569/ijacsa.2018.090140 fatcat:2qxvf7txinao5cr7o2wiiyz5ha

Intrusion Detection System in Wireless Sensor Networks: A Review

Anush Ananthakumar, Tanmay Ganediwal, Dr. Ashwini
2015 International Journal of Advanced Computer Science and Applications  
The intrusion detection system is used to detect various attacks occurring on sensor nodes of Wireless Sensor Networks that are placed in various hostile environments.  ...  This paper reviews various intrusion detection systems which can be broadly classified based on certain traditional techniques, namely signature based, anomaly based and hybrid based.  ...  One such model based on protection against sync flood attacks has been proposed by [30] .  ... 
doi:10.14569/ijacsa.2015.061218 fatcat:2izp2confbennkaa2vmdwpbvti

Survey of Countering DoS/DDoS Attacks on SIP Based VoIP Networks

Waleed Nazih, Wail S. Elkilani, Habib Dhahri, Tamer Abdelkader
2020 Electronics  
Most VoIP networks depend on the Session Initiation Protocol (SIP) to handle signaling functions. The SIP is a text-based protocol that is vulnerable to many attacks.  ...  In this paper, we present recently introduced approaches to detect DoS and DDoS attacks, and classify them based on various factors.  ...  The existing approaches can be categorized into four types: finite state machine (FSM) approaches, rules-based approaches, statistically based approaches, and machine learning approaches.  ... 
doi:10.3390/electronics9111827 fatcat:siv75rz52nbwnmdplfzy75mghe

A learning-based hybrid framework for detection and defence of DDoS attacks

T. Subbulakshmi
2017 International Journal of Internet Protocol Technology  
An integrated detection and defensive mechanism is proposed in this paper to generate and detect DDoS attacks using machine learning algorithms such as back propagation neural network (BPNN), self-organising  ...  map (SOM) and enhanced support vector machine (ESVM) and to identify the real IP address of the spoofed attack source using the entropy-based defensive mechanism.  ...  Related work The existing mechanism available to detect and mitigate the application and network layer attacks such as statistical detection, threshold-based detection and machine learning-based detection  ... 
doi:10.1504/ijipt.2017.083036 fatcat:ad4xvhp2erez3aq6g2vxtrbauy

Detecting cyber-attacks using a CRPS-based monitoring approach

Fouzi Harrou, Benamar Bouyeddou, Ying Sun, Benamar Kadri
2018 2018 IEEE Symposium Series on Computational Intelligence (SSCI)  
To accurately detect TCP SYN flood attacks, two statistical schemes based on the continuous ranked probability score (CRPS) metric have been designed in this paper.  ...  Cyber-attacks can seriously affect the security of computers and network systems. Thus, developing an efficient anomaly detection mechanism is crucial for information protection and cyber security.  ...  In [10] , an adaptive threshold-based approach and CUSUM algorithm were used to detect SYN Flooding Attacks based on SYN segments.  ... 
doi:10.1109/ssci.2018.8628797 dblp:conf/ssci/HarrouB0K18 fatcat:izi5ow6o3za2rfmmnbdoqgirhe

Efficient Distributed Denial-of-Service Attack Defense in SDN-based Cloud

Trung V. Phan, Minho Park
2019 IEEE Access  
INDEX TERMS Distributed denial-of-service attacks, machine learning, software defined networks, network function virtualization.  ...  We first introduce a new hybrid machine learning model based on support vector machine and selforganizing map algorithms to improve the traffic classification.  ...  , SOM classifier and eHIPF mechanism to defend against DDoS attacks in the SDN-based cloud environment.  ... 
doi:10.1109/access.2019.2896783 fatcat:bwwjirtfcfhjjg7mgrf6aiuzve

A DDoS Attack Mitigation Scheme in ISP Networks Using Machine Learning Based on SDN

Nguyen Ngoc Tuan, Pham Huy Hung, Nguyen Danh Nghia, Nguyen Tho, Trung Phan, Nguyen Thanh
2020 Electronics  
In this paper, we propose a novel DDoS attack mitigation in SDN-based Internet Service Provider (ISP) networks for TCP-SYN and ICMP flood attacks utilizing machine learning approach, i.e., K-Nearest-Neighbor  ...  Among other critical threats, distributed denial-of-service (DDoS) becomes one of the most widespread attacks in the Internet, which is very challenging to mitigate appropriately as DDoS attacks cause  ...  Conclusion This article presents a solution for mitigating DDoS attack, especially TCP-SYN flood attack and ICMP flood attack using machine learning in SDN-based ISP networks.  ... 
doi:10.3390/electronics9030413 fatcat:gh7vgwx6breunhfxjn4qbvmzfa
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