Titlebook: Computer Security – ESORICS 2020; 25th European Sympos Liqun Chen,Ninghui Li,Steve Schneider Conference proceedings 2020 Springer Nature Sw

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Efficient Quantification of Profile Matching Risk in Social Networks Using Belief Propagationymous way to protect their privacy. However, anonymous data sharing has been becoming more challenging in today’s interconnected digital world, especially for individuals that have both anonymous and identified online activities. The most prominent example of such data sharing platforms today are on

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Designing Reverse Firewalls for the Real Worlderts the implementation of a provably-secure cryptographic primitive to make it insecure. This concept was applied by Dodis . in the context of secure key exchange (handshake phase), where the adversary wants to exfiltrate sensitive information by using a subverted client implementation. RFs are use

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Dynamic and Secure Memory Transformation in Userspaceexploiting the runtime stack even when performing integrity checks or code re-randomization protections. Additionally, existing re-randomization frameworks do not achieve strong isolation, transparency and efficiency when securing the vulnerable application. In this paper we present Chameleon, a use

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Understanding the Security Risks of Docker Hubt popular Docker image repositories. Millions of images have been downloaded from Docker Hub billions of times. However, in the past several years, a number of high-profile attacks that exploit this key channel of image distribution have been reported. It is still unclear what security risks the new

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