1. Rogério de LemosDEFINE – 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)

2. Rogério de LemosDEFINE – Pisa, November 2002 – 2 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;

3. Rogério de LemosDEFINE – Pisa, November 2002 – 3 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;

4. Rogério de LemosDEFINE – Pisa, November 2002 – 4 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;

5. Rogério de LemosDEFINE – Pisa, November 2002 – 5 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?

6. Rogério de LemosDEFINE – Pisa, November 2002 – 6 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;