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Architecture For An Artificial Immune System S. A. Hofmeyr and S. Forrest
What Do They Do? Mimic Immunse System functionality and method Apply method to Intrusion Detection
How Do They Do It? They detail the ARTIS system Adapt and apply it, to create LISYS
ARTIS Detector –Detector Trainer –Activation Threshold –Lifespan Memory Detector Costimulation
Why Is It Good? Robust –Diverse, Distributed, Dynamic Adaptable Autonomous
LISYS Detector –Datapath triple (src_ip,dest_ip,port) Detection Nodes on each internal machine
LISYS in action
Does It Work? Claimed: –Robust –Controlled (Tunable) –Scalable –Accurate –Adaptable –Lightweight
What Doesn’t It Do? Pass around memory detectors Respond to a detected “nonself”
How Can We Apply It To A.C.? Architecture? Methods? Inspiration?
Immunity by Design: An Artificial Immune System Paper: Steven A. Hofmeyr, Stephanie Forrest Presentation: Joseph Niehaus.
Distributed Network Intrusion Detection An Immunological Approach Steven Hofmeyr Stephanie Forrest Patrik D’haeseleer Dept. of Computer Science University.
Computation in the Wild Staphanie Forrest Justin Balthrop Matthew Glickman David Ackley Presented by Montana Low.
1 Principles of a Computer Immune System Anil Somayaji, Steven Hofmeyr, & Stephanie Forrest Presented by: Jesus Morales.
V-Detector: A Negative Selection Algorithm Zhou Ji, advised by Prof. Dasgupta Computer Science Research Day The University of Memphis March 25, 2005.
Rogério de LemosDEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems Rogério de Lemos University of Kent at Canterbury Brian.
` Question: How do immune systems achieve such remarkable scalability? Approach: Simulate lymphoid compartments, fixed circulatory networks, cytokine communication.
Sensor B Sensor A Sensor C Sensor D Sensor E Lightweight Mining Techniques Time Frame: 10 Time Threshold: 20.
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Anomaly Detection in Data Docent Xiao-Zhi Gao
A. How does life arise from the nonliving? 1.Generate a molecular proto-organism in vitro. 2.Achieve the transition to life in an artificial chemistry.
Artificial Immune Systems Andrew Watkins. Why the Immune System? Recognition –Anomaly detection –Noise tolerance Robustness Feature extraction Diversity.
Immune System Metaphors Applied to Intrusion Detection and Related Problems by Ian Nunn, SCS, Carleton University
Artificial Immune Systems Our body’s immune system is a perfect example of a learning system. It is able to distinguish between good cells and potentially.
Presentation By SANJOG BHATTA Student ID : July 1’ 2009.
Artificial Immune System-Based Mobile Node Movement Peter Matthews.
Click to edit master text Click to edit Master text styles Second level Third level Fourth level Fifth level Artificial Immune Systems Dr Uwe Aickelin.
Nasraoui, Gonzalez, Cardona, Dasgupta: Scalable Artificial Immune System Based Data Mining NSF-NGDM, Nov. 1-3, 2002, Baltimore, MD Artificial Immune Systems.
Surface Defect Inspection: an Artificial Immune Approach Dr. Hong Zheng and Dr. Saeid Nahavandi School of Engineering and Technology.
` Research 2: Information Diversity through Information Flow Subgoal: Systematically and precisely measure program diversity by measuring the information.
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