Print Email Facebook Twitter Anomaly detection through information sharing under different topologies Title Anomaly detection through information sharing under different topologies Author Gallos, Lazaros K. (Rutgers University) Korczynski, M.T. (TU Delft Organisation & Governance) Fefferman, Nina H. (Rutgers University) Date 2017 Abstract Early detection of traffic anomalies in networks increases the probability of effective intervention/mitigation actions, thereby improving the stability of system function. Centralized methods of anomaly detection are subject to inherent constraints: (1) they create a communication burden on the system, (2) they impose a delay in detection while information is being gathered, and (3) they require some trust and/or sharing of traffic information patterns. On the other hand, truly parallel, distributed methods are fast and private but can observe only local information. These methods can easily fail to see the “big picture” as they focus on only one thread in a tapestry. A recently proposed algorithm, Distributed Intrusion/Anomaly Monitoring for Nonparametric Detection (DIAMoND), addressed these problems by using parallel surveillance that included dynamic detection thresholds. These thresholds were functions of nonparametric information shared among network neighbors. Here, we explore the influence of network topology and patterns in normal traffic flow on the performance of the DIAMoND algorithm. We contrast performance to a truly parallel, independent surveillance system. We show that incorporation of nonparametric data improves anomaly detection capabilities in most cases, without incurring the practical problems of fully parallel network surveillance. Subject Anomaly detectionDDoS attackInformation sharingSimulation To reference this document use: http://resolver.tudelft.nl/uuid:1b4b5527-4634-4c25-9eee-fc6874fe7cba DOI https://doi.org/10.1186/s13635-017-0056-5 ISSN 1687-4161 Source Eurasip Journal on Information Security, 2017 (1) Part of collection Institutional Repository Document type journal article Rights © 2017 Lazaros K. Gallos, M.T. Korczynski, Nina H. Fefferman Files PDF art_10.1186_s13635_017_0056_5.pdf 2.96 MB Close viewer /islandora/object/uuid%3A1b4b5527-4634-4c25-9eee-fc6874fe7cba/datastream/OBJ/view