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Between Ratings and Security

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If you have a question about this talk, please contact Dr Garfield Benjamin.

Some malware is not detected by tools. When users encounter such malware, they can report it, to help prevent others from getting the malware. But attackers may send fake reports, lowering (or even nullifying) the effectiveness of the system. Intuitively, sufficiently many honest users can counteract the attackers. In a security setting, however, intuition is insufficient. Instead, we mathematically analyse what we need from ratings (reports), to obtain hard guarantees.

The main part of the talk concerns work done at the NTU in Singapore: we quantify the amount of information in a rating, using Shannon entropy. The crucial notion is that we make no assumptions about the behaviour of attackers. Current work in Oxford focusses on how to use the information to make decisions that are provably highly probably correct. In particular, this means false malware reports will be provably improbable to have an adverse effect.

This talk is part of the Computer Security Seminars series.

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