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• W2187029556 abstract "Computer worms present a grave concern to the common man, and a challenging problem to the computer security community. Worms' abilities have precluded human intervention. East worms can be too fast to respond to. Slow worms can be too slow to be noticed. Zero-day and polymorphic worms can look like ordinary traffic to evoke any suspicion until they cause large scale destruction. This demands not just automated response but automated and intelligent response. This dissertation presents such an automated and intelligent means of detecting and responding to zero-day worms that could possibly be polymorphic in a signature independent fashion. Worms are detected cooperatively using a novel distributed application of the long-established Sequential Hypothesis Testing technique. The technique developed here builds a distributed worm detector of any desirable fidelity from unreliable anomaly detection systems. Tracking anomalies instead of signatures enables detection of zero-day and polymorphic worms. Cost-effective responses in the face of uncertainty about worms are selected automatically using Dynamic Programming. Responses are selected based on the likelihood of a current worm attack, and the relative costs of infection and responses, while minimizing the operating cost over a period of time. This technique uses information about anomalous events, potentially due to a worm, observed by cooperating peers to choose optimal actions for local implementation. In addition to developing the above techniques, this dissertation also presents a generic testing framework based on the Emulab network testbed to evaluate these and other such worm defense models, and provides a detailed survey of the research done so far in worm defense." @default.
• W2187029556 created "2016-06-24" @default.
• W2187029556 creator A5009965537 @default.
• W2187029556 creator A5015692814 @default.
• W2187029556 date "2007-01-01" @default.
• W2187029556 modified "2023-09-27" @default.
• W2187029556 title "Collaborative defense against zero-day and polymorphic worms: detection, response and an evaluation framework" @default.
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