A Sense of Self for Unix Processes
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
An immunological model of distributed detection and its application to computer security
An immunological model of distributed detection and its application to computer security
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
Is negative selection appropriate for anomaly detection?
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Articulation and clarification of the dendritic cell algorithm
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Introducing dendritic cells as a novel immune-inspired algorithm for anomaly detection
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Sensing danger: Innate immunology for intrusion detection
Information Security Tech. Report
Attack analysis & bio-inspired security framework for IPMultimedia subsystem
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Improving accuracy of immune-inspired malware detectors by using intelligent features
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Attack analysis & bio-inspired security framework for IP multimedia subsystem
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Further Exploration of the Dendritic Cell Algorithm: Antigen Multiplier and Time Windows
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Integrating real-time analysis with the dendritic cell algorithm through segmentation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A Sense of `Danger' for Windows Processes
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Review: The use of computational intelligence in intrusion detection systems: A review
Applied Soft Computing
Review Article: Recent Advances in Artificial Immune Systems: Models and Applications
Applied Soft Computing
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Systematic construction of anomaly detection benchmarks from real data
Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description
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Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and key to the activation of the human immune system, behaviour which has been abstracted to form the Dendritic Cell Algorithm (DCA). In algorithmic terms, individual DCs perform multi-sensor data fusion, asynchronously correlating the fused data signals with a secondary data stream. Aggregate output of a population of cells is analysed and forms the basis of an anomaly detection system. In this paper the DCA is applied to the detection of outgoing port scans using TCP SYN packets. Results show that detection can be achieved with the DCA, yet some false positives can be encountered when simultaneously scanning and using other network services. Suggestions are made for using adaptive signals to alleviate this uncovered problem.