The Strength of Weak Learnability
Machine Learning
Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
IEEE/ACM Transactions on Networking (TON)
Working Group Report on Web Infrastructure for Collaborative Applications
WET-ICE '96 Proceedings of the 5th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE'96)
IEEE Security and Privacy
DDoS attacks and defense mechanisms: classification and state-of-the-art
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Defense System against DDoS Attacks by Large-Scale IP Traceback
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
Collaborative Change Detection of DDoS Attacks on Community and ISP Networks
CTS '06 Proceedings of the International Symposium on Collaborative Technologies and Systems
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
Feature Extraction: Foundations and Applications (Studies in Fuzziness and Soft Computing)
A practical and robust inter-domain marking scheme for IP traceback
Computer Networks: The International Journal of Computer and Telecommunications Networking
On deterministic packet marking
Computer Networks: The International Journal of Computer and Telecommunications Networking
A router-based technique to mitigate reduction of quality (RoQ) attacks
Computer Networks: The International Journal of Computer and Telecommunications Networking
An Enhanced Swarm Intelligence Clustering-Based RBF Neural Network Detection Classifier
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
NPC '08 Proceedings of the IFIP International Conference on Network and Parallel Computing
Intrusion Detection Method Based on Wavelet Neural Network
WKDD '09 Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining
Reduction of Quality (RoQ) attacks on structured peer-to-peer networks
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Is it congestion or a DDoS attack?
IEEE Communications Letters
Defending DDoS attacks using hidden Markov models and cooperative reinforcement learning
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
CISC'05 Proceedings of the First SKLOIS conference on Information Security and Cryptology
ISPEC'05 Proceedings of the First international conference on Information Security Practice and Experience
Data Fusion and Cost Minimization for Intrusion Detection
IEEE Transactions on Information Forensics and Security
IEEE Communications Magazine
Tracing cyber attacks from the practical perspective
IEEE Communications Magazine
Review and functional classification of collaborative systems
International Journal of Information Management: The Journal for Information Professionals
Bayesian Neural Networks for Internet Traffic Classification
IEEE Transactions on Neural Networks
Automatic network intrusion detection: Current techniques and open issues
Computers and Electrical Engineering
A DDoS attack detection mechanism based on protocol specific traffic features
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Detecting latent attack behavior from aggregated Web traffic
Computer Communications
A survey of multiple classifier systems as hybrid systems
Information Fusion
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The vulnerabilities in the Communication (TCP/IP) protocol stack and the availability of more sophisticated attack tools breed in more and more network hackers to attack the network intentionally or unintentionally, leading to Distributed Denial of Service (DDoS) attack. The DDoS attacks could be detected using the existing machine learning techniques such as neural classifiers. These classifiers lack generalization capabilities which result in less performance leading to high false positives. This paper evaluates the performance of a comprehensive set of machine learning algorithms for selecting the base classifier using the publicly available KDD Cup dataset. Based on the outcome of the experiments, Resilient Back Propagation (RBP) was chosen as base classifier for our research. The improvement in performance of the RBP classifier is the focus of this paper. Our proposed classification algorithm, RBPBoost, is achieved by combining ensemble of classifier outputs and Neyman Pearson cost minimization strategy, for final classification decision. Publicly available datasets such as KDD Cup, DARPA 1999, DARPA 2000, and CONFICKER were used for the simulation experiments. RBPBoost was trained and tested with DARPA, CONFICKER, and our own lab datasets. Detection accuracy and Cost per sample were the two metrics evaluated to analyze the performance of the RBPBoost classification algorithm. From the simulation results, it is evident that RBPBoost algorithm achieves high detection accuracy (99.4%) with fewer false alarms and outperforms the existing ensemble algorithms. RBPBoost algorithm outperforms the existing algorithms with maximum gain of 6.6% and minimum gain of 0.8%.