Anup K Ghosh

One of the hardest challenges for companies and their officers is determining how much to spend on cybersecurity and the appropriate allocation of those resources. Security “investments” are a cost on the ledger, and as such, companies do not want to spend more on security than they have to. The question most boards have is “how much security is enough?” and “how good is our security program?” Most CISOs and SOC teams have a hard time answering these questions for a lack of data and framework to measure risk and compare with other similar sized companies. This paper presents a data-driven practical approach to assessing and scoring cybersecurity risk that can be used to allocate resources efficiently a nd mitigate cybersecurity risk in areas that need it the most. We combine both static and dynamic measures of risk to give a composite score more indicative of cybersecurity risk over static measures alone.

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DARWIN: Survival of the Fittest Fuzzing Mutators

Patrick Jauernig (Technical University of Darmstadt), Domagoj Jakobovic (University of Zagreb, Croatia), Stjepan Picek (Radboud University and TU Delft), Emmanuel Stapf (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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CableAuth: A Biometric Second Factor Authentication Scheme for Electric...

Jack Sturgess, Sebastian Köhler, Simon Birnbach, Ivan Martinovic (University of Oxford)

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Understanding the Ethical Frameworks of Internet Measurement Studies

Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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