Rogério de LemosDEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems...

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Rogério de Lemos DEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems Rogério de Lemos University of Kent at Canterbury Brian Bell (BAE Systems - Sowerby, UK) Rogério de Lemos, Jon Timmis (University of Kent at Canterbury, UK) Mark Neal (University of Wales, Aberystwyth, UK) Andy Tyrrell (University of York, UK)

Transcript of Rogério de LemosDEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems...

Page 1: Rogério de LemosDEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems Rogério de Lemos University of Kent at Canterbury  Brian.

Rogério de Lemos DEFINE – Pisa, November 2002 – 1

Proactive Computing: Artificial Immune Systems

Rogério de LemosUniversity of Kent at Canterbury

Brian Bell (BAE Systems - Sowerby, UK) Rogério de Lemos, Jon Timmis (University of Kent at

Canterbury, UK) Mark Neal (University of Wales, Aberystwyth, UK) Andy Tyrrell (University of York, UK)

Page 2: Rogério de LemosDEFINE – Pisa, November 2002 – 1 Proactive Computing: Artificial Immune Systems Rogério de Lemos University of Kent at Canterbury  Brian.

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Biological Inspired Computing

Autonomic computing (IBM) nervous system which regulates the basic functions of the

body;

Planetary computing (HP)

Self-healing systems (Software Engineering Community)

Homeostasis (Mary Shaw) a system acts to maintain a stable internal environment

despite external variations; react to change rather than desired states;

Artificial immune systems fault-tolerance, intrusion & virus detection;

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Motivation

Provision of means for a system to cope with changes: design time (evolution):

building new systems from existing ones;

run time (adaptability); adapting to changes that occur in the operating environment;

Some approaches rely on learning capabilities/emergent behaviours:

adjust behaviour/structure to new needs without human intervention;

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Artificial Immune Systems (AIS)

AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models, which are applied to complex problem domains;

What does the immune system offer? pattern recognition; robust and distributed; adaptive and diverse; learning and memory;

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Proactive Computing

Fault tolerance Learning capabilities may enable the system to react to

unexpected circumstances: it removes the predictability aspect;

System evaluation how much can these learning capabilities be trusted? how to protect the system from undesirable decisions?

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Themes

Artificial Immune Systems applied to Fault and Intrusion Tolerance

e.g., evolution of error detectors;

Biologically Inspired Engineering embryonics, evolvable hardware, immunotronics, etc.

Biologically Inspired Techniques for Autonomous Dependable Systems

exploitation of homeostasis

Swarm Techniques applied to Intrusion Tolerance in Mobile Systems

coordination of countermeasures to attacks;