Thesis Intrusion Detection System

Thesis Intrusion Detection System-9
This master thesis presents a SCADA Intrusion Detection System Test Framework that can be used to simulate SCADA traffic and detect malicious network activity.The framework uses a signature-based approach and utilize two different IDS engines, Suricata and Snort.

This master thesis presents a SCADA Intrusion Detection System Test Framework that can be used to simulate SCADA traffic and detect malicious network activity.

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95-022, COAST Laboratory, Department of Computer Sciences, Purdue University, March 1994.

Mark Crosbie, Gene Spafford, Defending a Computer System using Autonomous Agents, Technical report No.

The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection in particular Anomaly Detection, to examine their conceptual foundations, to taxonomize the Intrusion Detection System (IDS) and to develop a morphological framework for IDS for easy understanding.

In this study a detailed survey of IDS from the initial days, the development of IDS, architectures, components are presented. P., Computer Security Threat Monitoring and Surveillance, Technical report, James P.

Supervisory control and data acquisition (SCADA) systems play an important role in our critical infrastructure (CI).

Several of the protocols used in SCADA communication are old and lack of security mechanisms.

In Advanced Computing and Intelligent Technologies (ICACIE), 2016 First International Conference on.

A Novel algorithm for Network Anomaly Detection using Adaptive Machine Learning. (2010) Data Clustering Using K-Mean Algorithm For Network Intrusion Detection, Thesis, Lovely Professional University, Jalandhar.

Yadav, “Taxonomy of Anomaly Based Intrusion Detection System: A Review”, International Journal of Scientific and Research Publications, Vol 2(12), 2012 Martin Elich, “Flow-based Network Anomaly Detection in the context of IPv6”, Thesis Report, FAKULTA INFORMATIKY, MASARYKOVA UNIVERZITA, 2012.

Narayana; Prasad; Srividhya; Reddy, “Data Mining Machine Learning Techniques – A Study on Abnormal Anomaly Detection System”, International Journal of Computer Science and Telecommunications, Vol. 2011 Yevgeniy Bodyanskiy, Sergiy Popov, Neural Network Approach to Forecasting of Quasiperiodic Financial Time Series, European Journal of Operational Research Vol.

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