UMBC ebiquity
Arya Renjan: Multi-observable Session Reputation Scoring System

Arya Renjan: Multi-observable Session Reputation Scoring System

Tim Finin, 12:19pm 22 October 2017

Multi-observable Session Reputation Scoring System

Arya Renjan

11:00-12:00 Monday, 23 October 2017, ITE 346

With increasing adoption of Cloud Computing, cyber attacks have become one of the most effective means for adversaries to inflict damage. To overcome limitations of existing blacklists and whitelists, our research focuses to develop a dynamic reputation scoring model for sessions based on a variety of observable and derived attributes of network traffic. Here we propose a technique to greylist sessions using observables like IP, Domain, URL and File Hash by scoring them numerically based on the events in the session. This enables automatic labeling of possible malicious hosts or users that can help in enriching the existing whitelists or blacklists.


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