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Computer Security – ESORICS 2022

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Table of Contents

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    Book Overview
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    Chapter 1 A Formal Analysis of the FIDO2 Protocols
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    Chapter 2 A Composable Security Treatment of ECVRF and Batch Verifications
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    Chapter 3 Efficient Proofs of Knowledge for Threshold Relations
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    Chapter 4 A Tale of Two Models: Formal Verification of  KEMTLS via Tamarin
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    Chapter 5 Browser-Based CPU Fingerprinting
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    Chapter 6 Polymorphic Protocols at the Example of Mitigating Web Bots
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    Chapter 7 Unlinkable Delegation of WebAuthn Credentials
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    Chapter 8 Large Scale Analysis of DoH Deployment on the Internet
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    Chapter 9 Equivocal URLs: Understanding the Fragmented Space of URL Parser Implementations
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    Chapter 10 Exploring the Characteristics and Security Risks of Emerging Emoji Domain Names
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    Chapter 11 CPU Port Contention Without SMT
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    Chapter 12 Protocols for a Two-Tiered Trusted Computing Base
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    Chapter 13 Using Memristor Arrays as Physical Unclonable Functions
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    Chapter 14 SecureBiNN: 3-Party Secure Computation for Binarized Neural Network Inference
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    Chapter 15 Mixed-Technique Multi-Party Computations Composed of Two-Party Computations
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    Chapter 16 PEA: Practical Private Epistasis Analysis Using MPC
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    Chapter 17 Hide and Seek: On the Stealthiness of Attacks Against Deep Learning Systems
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    Chapter 18 Precise Extraction of Deep Learning Models via Side-Channel Attacks on Edge/Endpoint Devices
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    Chapter 19 Real-Time Adversarial Perturbations Against Deep Reinforcement Learning Policies: Attacks and Defenses
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    Chapter 20 FLMJR: Improving Robustness of Federated Learning via Model Stability
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    Chapter 21 MaleficNet: Hiding Malware into Deep Neural Networks Using Spread-Spectrum Channel Coding
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    Chapter 22 Long-Short History of Gradients Is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning
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    Chapter 23 MLFM : Machine Learning Meets Formal Method for Faster Identification of Security Breaches in Network Functions Virtualization (NFV)
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    Chapter 24 Perspectives from a Comprehensive Evaluation of Reconstruction-based Anomaly Detection in Industrial Control Systems
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    Chapter 25 A Novel High-Performance Implementation of CRYSTALS-Kyber with AI Accelerator
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    Chapter 26 From Click to Sink: Utilizing AIS for Command and Control in Maritime Cyber Attacks
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    Chapter 27 Efficient Hash-Based Redactable Signature for Smart Grid Applications
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    Chapter 28 Can Industrial Intrusion Detection Be SIMPLE?
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    Chapter 29 For Your Voice Only: Exploiting Side Channels in Voice Messaging for Environment Detection
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    Chapter 30 Towards Efficient Auditing for Real-Time Systems
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    Chapter 31 Towards a Systematic and Automatic Use of State Machine Inference to Uncover Security Flaws and Fingerprint TLS Stacks
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    Chapter 32 PanoptiCANs - Adversary-Resilient Architectures for Controller Area Networks
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    Chapter 33 Detecting Cross-language Memory Management Issues in Rust
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    Chapter 34 Reach Me if You Can: On Native Vulnerability Reachability in Android Apps
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    Chapter 35 Extensible Virtual Call Integrity
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    Chapter 36 Is Your Password Sexist? a Gamification-Based Analysis of the Cultural Context of Leaked Passwords
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    Chapter 37 A Fast, Practical and Simple Shortest Path Protocol for Multiparty Computation
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    Chapter 38 Audio Spoofing Detection Using Constant-Q Spectral Sketches and Parallel-Attention SE-ResNet
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    Chapter 39 MixCT: Mixing Confidential Transactions from Homomorphic Commitment
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    Chapter 40 Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python
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    Chapter 41 The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models
Attention for Chapter 21: MaleficNet: Hiding Malware into Deep Neural Networks Using Spread-Spectrum Channel Coding
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Chapter title
MaleficNet: Hiding Malware into Deep Neural Networks Using Spread-Spectrum Channel Coding
Chapter number 21
Book title
Computer Security – ESORICS 2022
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-17143-7_21
Book ISBNs
978-3-03-117142-0, 978-3-03-117143-7
Authors

Hitaj, Dorjan, Pagnotta, Giulio, Hitaj, Briland, Mancini, Luigi V., Perez-Cruz, Fernando

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Unknown 3 75%
Readers by discipline Count As %
Unspecified 1 25%
Unknown 3 75%