Proceedings ArticleDOI
A system approach to network modeling for DDoS detection using a Naìve Bayesian classifier
R. Vijayasarathy,S. V. Raghavan,Balaraman Ravindran +2 more
- pp 1-10
TLDR
The approach to a carefully engineered, practically realised system to detect DoS attacks using a Naìve Bayesian(NB) classifier is described, which includes network modeling for two protocols - TCP and UDP.Abstract:
Denial of Service(DoS) attacks pose a big threat to any electronic society. DoS and DDoS attacks are catastrophic particularly when applied to highly sensitive targets like Critical Information Infrastructure. While research literature has focussed on using various fundamental classifier models for detecting attacks, the common trend observed in literature is to classify DoS attacks into the broad class of intrusions, which makes proposed solutions to this class of attacks unrealistic in practical terms. In this work, the approach to a carefully engineered, practically realised system to detect DoS attacks using a Naive Bayesian(NB) classifier is described. The work includes network modeling for two protocols - TCP and UDP.read more
Citations
More filters
Journal ArticleDOI
Botnet in DDoS Attacks: Trends and Challenges
TL;DR: This survey presents a comprehensive overview of DDoS attacks, their causes, types with a taxonomy, and technical details of various attack launching tools.
Journal ArticleDOI
A Survey of Distance and Similarity Measures Used Within Network Intrusion Anomaly Detection
TL;DR: An overview of the use of similarity and distance measures within NIAD research is presented and a theoretical background in distance measures is provided and a discussion of various types of distance measures and their uses are discussed.
Journal ArticleDOI
Towards an Energy-Efficient Anomaly-Based Intrusion Detection Engine for Embedded Systems
Eduardo Viegas,Altair Olivo Santin,André Luiz Pereira de França,Ricardo P. Jasinski,Volnei A. Pedroni,Luiz S. Oliveira +5 more
TL;DR: It is demonstrated that a hardware (HW) implementation of network security algorithms can significantly reduce their energy consumption compared to an equivalent software (SW) version.
Journal ArticleDOI
Comprehensive Review of Artificial Intelligence and Statistical Approaches in Distributed Denial of Service Attack and Defense Methods
Bashar Ahmed Khalaf,Salama A. Mostafa,Aida Mustapha,Mazin Abed Mohammed,Wafaa Mustafa Abduallah +4 more
TL;DR: This review paper focuses on the most common defense methods against DDoS attacks that adopt artificial intelligence and statistical approaches and classifies and illustrates the attack types, the testing properties, the evaluation methods and the testing datasets that are utilized in the methodology of the proposed defense methods.
Journal ArticleDOI
Security Data Collection and Data Analytics in the Internet: A Survey
TL;DR: This paper surveys existing studies about security-related data collection and analytics for the purpose of measuring the Internet security and proposes several additional requirements for security- related data analytics in order to make the analytics flexible and scalable.
References
More filters
Proceedings ArticleDOI
DDoS detection based on feature space modeling
Shuyuan Jin,D.S. Yeung +1 more
TL;DR: This work tries to use a feature space modeling methodology to identify DDoS attacks by using a subset in KDD Cup 1999 data and gets a high detection rate under this feature space by using the proposed classification algorithm, which shows the discriminative abilities of the feature space.
Journal ArticleDOI
A Novel Distributed Detection Scheme against DDoS Attack
TL;DR: A novel detection scheme against DDoS attack is proposed from a distributed perspective and has better performance than CUSUM and time similarity algorithm individually deployed and can be applied to resolve the communication problem in other distributed application system.
Journal Article
Detecting DDoS Attacks Based on Multi-stream Fused HMM in Source-End Network
Jian Kang,Yuan Zhang,Jiu-Bin Ju +2 more
TL;DR: Wang et al. as discussed by the authors proposed a novel approach using Multi-stream Fused Hidden Markov Model (MF-HMM) on source-end DDoS detection for integrating multi-features simultaneously.
Book ChapterDOI
Detecting DDoS attacks based on multi-stream fused HMM in source-end network
Jian Kang,Yuan Zhang,Jiu-Bin Ju +2 more
TL;DR: This paper proposes a novel approach using Multi-stream Fused Hidden Markov Model (MF-HMM) on source-end DDoS detection for integrating multi- features simultaneously, and presents that this approach effectively reduces false-positive rate and false-negative rate, and improves the precision of detection.