Computer Security – ESORICS 2023

Table of Contents

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   Book Overview
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   Chapter 1 Layered Symbolic Security Analysis in  $$\textsf {DY}^\star $$ DY ⋆
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   Chapter 2 Indirect Meltdown: Building Novel Side-Channel Attacks from Transient-Execution Attacks
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   Chapter 3 Accessorize in the Dark: A Security Analysis of Near-Infrared Face Recognition
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   Chapter 4 A Rowhammer Reproduction Study Using the Blacksmith Fuzzer
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   Chapter 5 Reviving Meltdown 3a
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   Chapter 6 Tamarin-Based Analysis of Bluetooth Uncovers Two Practical Pairing Confusion Attacks
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   Chapter 7 MARF: A Memory-Aware CLFLUSH-Based Intra- and Inter-CPU Side-Channel Attack
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   Chapter 8 You Reset I Attack! A Master Password Guessing Attack Against Honey Password Vaults
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    Chapter 9 Attacking Logo-Based Phishing Website Detectors with Adversarial Perturbations
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    Chapter 10 Hiding Your Signals: A Security Analysis of PPG-Based Biometric Authentication
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    Chapter 11 Exploring Genomic Sequence Alignment for Improving Side-Channel Analysis
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    Chapter 12 The Grant Negotiation and Authorization Protocol: Attacking, Fixing, and Verifying an Emerging Standard
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    Chapter 13 Everlasting ROBOT: The Marvin Attack
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    Chapter 14 JWTKey: Automatic Cryptographic Vulnerability Detection in JWT Applications
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    Chapter 15 When is Slower Block Propagation More Profitable for Large Miners?
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    Chapter 16 Bijack: Breaking Bitcoin Network with TCP Vulnerabilities
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    Chapter 17 Syntax-Aware Mutation for Testing the Solidity Compiler
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    Chapter 18 Efficient Transparent Polynomial Commitments for zk-SNARKs
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    Chapter 19 n -MVTL Attack: Optimal Transaction Reordering Attack on DeFi
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    Chapter 20 stoRNA: Stateless Transparent Proofs of Storage-time
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    Chapter 21 Secure Approximate Nearest Neighbor Search with Locality-Sensitive Hashing
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    Chapter 22 ConGISATA: A Framework for Continuous Gamified Information Security Awareness Training and Assessment
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    Chapter 23 Tactics for Account Access Graphs
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    Chapter 24 Machine-Checked Proofs of Accountability: How to sElect Who is to Blame