A Software Agent Framework to Overcome Malicious Host Threats and Uncontrolled Agent Clones

نویسنده

  • Annie Sujitha
چکیده

An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors. Enormous number of researches is going on by comparing the functional similarities of the Human Immune System for making the agents more adaptable in regard with security. In this research work, the functional similarities of Human Nervous system are given to the agents by proposing an agent-based framework where the agents can adapt themselves from one of the threats, the malicious host attack. The agents become aware of the malicious hosts’ attack by learning and coordination is maintained by a Co-Agent to make this system work successfully. The concept of learning and coordination are taken from the Human Nervous system functionality. This system has shown a better functioning in maintaining the system performance by making the agents aware of malicious hosts and by producing limited number of clones.

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تاریخ انتشار 2012