
Computer Security - ESORICS 2021
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The 71 full papers presented in this book were carefully reviewed and selected from 351 submissions. They were organized in topical sections as follows:
Part I: network security; attacks; fuzzing; malware; user behavior and underground economy; blockchain; machine learning; automotive; anomaly detection;
Part II: encryption; cryptography; privacy; differential privacy; zero knowledge; key exchange; multi-party computation.
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Content
- Intro
- Preface
- Organization
- Contents - Part II
- Contents - Part I
- Encryption
- Bestie: Very Practical Searchable Encryption with Forward and Backward Security
- 1 Introduction
- 2 Background
- 3 Construction of Bestie
- 3.1 Our Construction
- 3.2 An Example of Bestie
- 4 Evaluation
- 4.1 Implementation
- 4.2 Data Description
- 4.3 Experimental Results
- 5 Other Related Works
- 6 Conclusion
- A Proof of Theorem 1
- References
- Geo-DRS: Geometric Dynamic Range Search on Spatial Data with Backward and Content Privacy
- 1 Introduction
- 1.1 Our Contributions
- 1.2 Motivation and Related Works
- 2 Building Blocks
- 2.1 Notation
- 2.2 R-Tree and R+tree
- 2.3 Secure Bitwise Comparison
- 3 Definitions, Security Notions and Model
- 3.1 Syntax of Our Geometric Dynamic Range Search (Geo-DRS+)
- 3.2 Generic Dynamic SSE Leakage Functions
- 3.3 Range Search Leakage Functions
- 3.4 Security Notions and Definitions
- 3.5 Security Model
- 4 Dynamic Secure Range Search on Encrypted Spatial Data
- 4.1 Geo-DRS Scheme
- 4.2 Geo-DRS+: Optimised Geometric Dynamic Range Search
- 5 Evaluation
- 6 Conclusion
- A Security analysis
- References
- Efficient Multi-client Order-Revealing Encryption and Its Applications
- 1 Introduction
- 1.1 Related Work
- 2 Preliminaries
- 2.1 Notation
- 2.2 Bilinear Maps
- 2.3 Complexity Assumption
- 3 Property-Preserving Hash
- 3.1 PPH from Bilinear Maps
- 3.2 Security Analysis
- 4 Multi-client Order-Revealing Encryption (m-ORE)
- 4.1 Definition of m-ORE
- 4.2 m-ORE Scheme from PPH
- 4.3 Security Analysis
- 5 Multi-client Range Query from m-ORE
- 5.1 The Proposed Construction
- 6 Experimental Evaluation
- 6.1 Setup
- 6.2 Evaluation
- 7 Conclusion
- A Security Analysis of Range Query Scheme
- References
- Versatile and Sustainable Timed-Release Encryption and Sequential Time-Lock Puzzles (Extended Abstract)
- 1 Introduction
- 2 Technical Overview and Contributions
- 3 Definitions and Constructions of Time Lock-Puzzles
- 4 Sequential Time-Lock Puzzles
- 5 (Sequential) Timed-Release Encryption
- 5.1 Basic TRE Construction
- 5.2 Sequential TRE
- 5.3 Integrating Timed-Release Features into Functional Encryption
- A Concurrent and Independent Work
- B Applications: Simpler and More Efficient Instantiations
- C On the Necessity of the Gap Sequential Squaring Assumption
- References
- Multipath TLS 1.3
- 1 Introduction
- 1.1 Multipath Key Exchange
- 1.2 Our Contribution
- 2 Preliminaries
- 2.1 Multipath TCP
- 2.2 Transport Layer Security
- 3 Security Model
- 3.1 Overview
- 3.2 Security of Multi-path Key Exchange
- 4 Multipath Extension for TLS 1.3
- 4.1 Protocol
- 4.2 Security Assumptions
- 4.3 Security
- 4.4 Sub Flow Resumption
- 4.5 Practical Considerations
- 5 Conclusions
- A Transport Layer Security
- References
- SyLPEnIoT: Symmetric Lightweight Predicate Encryption for Data Privacy Applications in IoT Environments
- 1 Introduction
- 1.1 Overview of SyLPEnIoT
- 1.2 Our Contributions
- 2 Related Work
- 3 Background and Assumptions
- 3.1 SyLPEnIoT's Model and Threat Model
- 3.2 Definitions
- 4 Main Constructions in SyLPEnIoT
- 4.1 Pseudo-Random Function
- 4.2 Symmetric-Key Encryption
- 4.3 Construction
- 5 Evaluation
- 5.1 Microbenchmarks
- 5.2 SyLPEnIoT Construction
- 5.3 SyLPEnIoT on Ultra Low-Power Devices
- A Security Proof
- References
- Security Analysis of SFrame
- 1 Introduction
- 1.1 Our Contributions
- 2 SFrame
- 2.1 Specification
- 2.2 Available Implementations
- 3 Adversary Models and Security Goals
- 3.1 Adversary Models
- 3.2 Security Goals of E2EE
- 3.3 Security Goals of AEAD for E2EE
- 3.4 Security Goals of Hash Functions
- 4 Security Analysis
- 4.1 Security of AEAD Under SFrame
- 4.2 Impersonation Against AES-CM-HMAC with Short Tags
- 4.3 Security of AES-CM-HMAC with Long Tags
- 4.4 Impersonation Against AES-GCM with Any Long Tags
- 4.5 Considerations on Authentication Key Recovery
- 4.6 Recommendations
- 5 Conclusions
- References
- Attribute-Based Conditional Proxy Re-encryption in the Standard Model Under LWE
- 1 Introduction
- 1.1 Contribution
- 1.2 Related Work
- 1.3 Organization
- 2 Preliminaries
- 2.1 Lattice Background
- 2.2 Trapdoor and Sampling
- 2.3 Key Homomorphism and Vector Decomposition
- 3 Model of Attribute-Based CPRE
- 3.1 Multi-hop AB-CPRE
- 3.2 Single-Hop AB-CPRE
- 3.3 Security Notation
- 4 Single-Hop AB-CPRE Scheme
- 4.1 Technique Review
- 4.2 Construction
- 4.3 Correctness
- 4.4 Security Proof
- 5 Extension: Multi-hop AB-CPRE Scheme
- 5.1 Construction
- 5.2 Correctness and Security Proof
- 6 Conclusion
- A Proof for Single-hop AB-CPRE
- B Correctness for Multi-hop AB-CPRE
- C Simulator Algorithms for Multi-hop AB-CPRE
- References
- Lattice-Based HRA-secure Attribute-Based Proxy Re-Encryption in Standard Model
- 1 Introduction
- 1.1 Motivation and Related Works
- 1.2 Our Contributions and Future Direction
- 1.3 Technical Overview
- 2 Preliminaries
- 3 Key-Policy Attribute-Based Proxy Re-Encryption
- 3.1 Re-Encryption Simulatability
- 4 Construction of HRA-secure KP-ABPRE
- 4.1 Correctness and Security
- References
- Server-Aided Revocable Attribute-Based Encryption Revised: Multi-User Setting and Fully Secure
- 1 Introduction
- 1.1 Motivation
- 1.2 Our Approach
- 1.3 Our Contributions
- 2 Preliminaries
- 2.1 Composite Order Bilinear Groups
- 2.2 Access Structures and Linear Secret Sharing
- 2.3 Binary Tree
- 3 Framework and Security Model
- 3.1 Security Model
- 4 Construction
- 5 Security Analysis
- 6 Conclusion
- A Proof of Lemma 2
- B Proof of Lemma 4
- C Proof of Lemma 5
- References
- Cryptography
- Precomputation for Rainbow Tables has Never Been so Fast
- 1 Introduction
- 2 Background
- 2.1 Rainbow Tables
- 2.2 Clean Rainbow Tables
- 2.3 Maximum Rainbow Tables
- 3 Filtering Chains
- 3.1 Preliminary Result on Quantifying Precomputation
- 3.2 Intermediary Filtration
- 3.3 Filtration in Each Column
- 3.4 Filtration in Chosen Columns
- 4 Distributing Precomputation
- 4.1 Distribution and Filtration
- 4.2 Distributed Architecture
- 4.3 Estimation of the Precomputation Time
- 4.4 Optimal Configuration
- 5 Experiments
- 5.1 Computing Environments
- 5.2 Filtration Implementation
- 5.3 Positions of the Filters
- 5.4 Considered Parameters
- 5.5 Results
- 6 Conclusion
- A Proof of Theorem 3
- B Online Phase Improvements and Their Impact on Precomputation
- C Intermediary Filtration
- D Notation Through this Paper
- References
- Cache-Side-Channel Quantification and Mitigation for Quantum Cryptography
- 1 Introduction
- 2 Basic Notions and Notation
- 2.1 Cache-Side-Channel Quantification
- 2.2 Quantum Key Distribution
- 3 Analysis for Cache-Side-Channel Quantification
- 3.1 Execution Model
- 3.2 Abstract Reachability Analysis
- 3.3 Automation Through Tool Support
- 4 Practical Evaluation
- 5 Vulnerability in the QKD Implementation
- 6 Security of the Hardened Implementation
- 7 Combining Rewriting and Privacy Amplification
- 8 Related Work
- 9 Conclusion
- References
- Genetic Algorithm Assisted State-Recovery Attack on Round-Reduced Xoodyak
- 1 Introduction
- 2 Preliminaries
- 2.1 Notations
- 2.2 Xoodoo
- 2.3 Xoodyak
- 3 Related Works
- 4 Remodel Xoodoo
- 4.1 Remodel Linear Layer
- 4.2 Remodel Non-linear Layer
- 4.3 Assemble into Xoodoo'
- 5 State-Recovery Attack on Round-Reduced Xoodyak
- 5.1 4/5-Round Attack Against Xoodyak
- 5.2 Extended to 5/6-Round
- 5.3 Attack Against Xoodyak Under the Nonce-Reuse Setting
- 6 Conclusion
- References
- Moving the Bar on Computationally Sound Exclusive-Or
- 1 Introduction
- 2 Background and Related Work
- 3 Symbolic Preliminaries
- 4 Symbolic and Computational Models
- 4.1 The Computational Model
- 4.2 Relationship Between Computational and Symbolic Models
- 4.3 MOO Cryptosystems and Symbolic Histories
- 5 MOO Games and Security Proofs
- 5.1 MOO Games Grstr and Grsymb
- 5.2 Conditions Implying IND$-CPA Security
- 6 Using Our Results to Analyze Modes
- 7 Conclusion and Open Problems
- References
- Optimal Verifiable Data Streaming Protocol with Data Auditing
- 1 Introduction
- 1.1 Our Contribution
- 1.2 Related Work
- 1.3 Organization
- 2 Preliminaries
- 2.1 Notations
- 2.2 Bilinear Groups and CDH Assumption
- 2.3 Groups of Unknown Order and RSA Accumulator
- 2.4 Hashing to Primes
- 3 Verifiable and Auditable Data Streaming Protocol
- 4 The Construction of VADS
- 4.1 Overview
- 4.2 The Construction
- 5 Performance Analysis
- 6 Conclusion
- References
- One-More Unforgeability of Blind ECDSA
- 1 Introduction
- 1.1 ECDSA-ROS Attack on Blind ECDSA
- 1.2 Generic Construction
- 1.3 Algebraic Bijective Random Oracle Model
- 1.4 Security Proof of Blind ECDSA
- 1.5 Related Work
- 2 Preliminaries
- 2.1 ECDSA
- 2.2 Blind Signature
- 3 Algebraic Bijective Random Oracle Model
- 3.1 AGM and BRO
- 3.2 Algebraic Bijective Random Oracle Model
- 4 Blind ECDSA
- 4.1 Building Blocks
- 4.2 Construction
- 4.3 Assumptions
- 4.4 Security Proof
- 4.5 EUF-CMA Security of ECDSA in the ABRO Model
- 5 Hardness of the ECDSA-ROS Problem
- 6 Conclusion
- A Comparison with Existing Blind ECDSA Protocols
- B Blindness
- B.1 Security Model of Blindness
- B.2 Security Proof of Blindness
- References
- MPC-in-Multi-Heads: A Multi-Prover Zero-Knowledge Proof System
- 1 Introduction
- 1.1 Related Works
- 2 Preliminaries
- 2.1 Basic Notations
- 2.2 Secure Computation
- 2.3 Helper Functionalities
- 3 Multi-Prover Zero-Knowledge
- 3.1 Relation and Language
- 3.2 Proof System Syntax
- 3.3 Formal Definition
- 3.4 Public-Coin and Non-interactive Proof
- 4 MPC-in-Multi-Heads: A Black-Box Construction from MPC
- 4.1 Intuitions
- 4.2 Protocol Description
- 4.3 Instantiation with Different Inner Protocols
- 5 Implementation and Experimental Results
- 6 Conclusion and Future Directions
- A Missing Proofs
- References
- Complexity and Performance of Secure Floating-Point Polynomial Evaluation Protocols
- 1 Introduction
- 2 Secure Floating-Point Arithmetic
- 3 Secure Polynomial Evaluation
- 3.1 Generic Protocols for Secure Polynomial Evaluation
- 3.2 Optimized Protocols for Polynomials Defined by Coefficients
- 3.3 Optimized Protocols for Polynomials Defined by Roots
- 4 Performance Measurements
- 5 Conclusions
- References
- SERVAS! Secure Enclaves via RISC-V Authenticryption Shield
- 1 Introduction
- 2 Challenges of Memory Isolation
- 3 RISC-V Authenticryption Shield (RVAS)
- 3.1 RVAS Tweak Design
- 3.2 Solving the Challenges
- 4 SERVAS
- 4.1 Threat Model
- 4.2 Enclave Life Cycle
- 4.3 Enclave Memory Management
- 5 SERVAS Implementation Details
- 5.1 Instruction Set Extension
- 5.2 Tweak
- 5.3 Page Types
- 5.4 Security Monitor (SM)
- 5.5 Caching
- 5.6 Encryption Bypass Optimization
- 6 Security Analysis
- 6.1 Attacks on Physical Memory
- 6.2 Attacks on Virtual Memory
- 7 Evaluation
- 7.1 Performance Overhead
- 7.2 Hardware Overhead
- 7.3 Prototype Limitations
- 8 Related Work
- 9 Future Work
- 10 Conclusion
- A Detailed Evaluation Results
- References
- Privacy
- Privacy-Preserving Gradient Descent for Distributed Genome-Wide Analysis
- 1 Introduction
- 2 System Design
- 2.1 Frag Overview
- 2.2 Attacker Model and Assumptions
- 3 Privacy-Preserving Gradient Descent
- 4 Modeling Attacks for Privacy Analysis
- 4.1 Modeling the LFS Attack
- 4.2 Modeling the Genotype Imputation
- 5 Analysis of Privacy Preservation
- 5.1 The Collection-Level Analysis
- 5.2 The Individual-Level Analysis
- 6 Performance Evaluation
- 7 Discussion
- 8 Related Work
- 9 Conclusion
- A Notation Table
- B Functionalities in Genome-Wide Analysis
- References
- Privug: Using Probabilistic Programming for Quantifying Leakage in Privacy Risk Analysis
- 1 Introduction
- 2 Overview
- 3 Privug
- 4 Evaluation
- 5 Related Work and Concluding Remarks
- References
- Transparent Electricity Pricing with Privacy
- 1 Introduction
- 2 Electricity Pricing
- 3 System and Security Model
- 3.1 Security Model
- 3.2 Security Properties
- 4 Baseline Protocol
- 4.1 Preliminaries
- 4.2 Instantiation
- 4.3 Security Analysis
- 4.4 Performance Analysis
- 4.5 Discussion
- 5 Merkle Tree Protocol
- 5.1 Overview
- 5.2 Instantiation
- 5.3 Security Analysis
- 5.4 Performance Analysis
- 6 Implementation
- 7 Related Work
- 8 Conclusions
- References
- CoinJoin in the Wild
- 1 Introduction
- 1.1 Empirical Analysis of Anonymity
- 1.2 Cookie Monster Mixing
- 1.3 Responsible Disclosure
- 1.4 Related Work
- 2 Preliminaries
- 2.1 Transaction
- 2.2 Multi-Input Heuristic
- 2.3 CoinJoin
- 2.4 Cluster-Intersection Attack
- 3 Dash
- 3.1 Overview
- 3.2 PrivateSend
- 4 Empirical Anonymity Analysis
- 4.1 Transaction Type Detection
- 4.2 Backlink Attack
- 4.3 DC Attack
- 5 Enhancing Privacy of Mixing
- 5.1 Preventing backlinks
- 5.2 Cookie Monster Mixing
- A Differences in the Analysis in Bitcoin
- B Limitations to Arbitrary-Value Mixing
- References
- One-Time Traceable Ring Signatures
- 1 Introduction
- 1.1 Our Contribution
- 1.2 Our Technique
- 1.3 Performance Comparison
- 2 Related Work
- 3 Definitions
- 3.1 One-Time Traceable Ring Signatures
- 4 One-Time Traceable Ring Signature Scheme
- References
- PACE with Mutual Authentication - Towards an Upgraded eID in Europe
- 1 Introduction
- 1.1 Role of eIDs
- 1.2 New Regulations for eIDs
- 1.3 Rationale for Including Mutual Authentication
- 1.4 Other extensions and Modifications of PACE
- 2 PACE with Mutual Authentication
- 2.1 PACE with Mutual Authentication
- 2.2 A Lightweight Version
- 2.3 Backwards Compatibility
- 3 Security and Privacy Issues
- 3.1 Fragility
- 3.2 Protection of Secrets
- 3.3 Impersonation
- 3.4 Security of the Session Key
- 3.5 Resistance to Tracing
- 3.6 Simultability
- 4 PACE-MA Versus PACE-CAM
- References
- Differential Privacy
- Secure Random Sampling in Differential Privacy
- 1 Introduction
- 2 Background
- 2.1 Floating Point Numbers
- 2.2 Random Number Sampling
- 2.3 Mironov Attack
- 2.4 Gaussian Attack
- 2.5 Existing Defences
- 3 General Principles
- 4 Divisibility of Probability Distributions
- 4.1 Preliminaries
- 4.2 Gaussian Distribution
- 4.3 Laplace Distribution
- 5 Sampling Implementations
- 5.1 Gaussian Sampling
- 5.2 Laplace Sampling
- 5.3 Choosing n
- 6 Gaussian Attack Complexity
- 7 Related Work
- 8 Conclusion
- A Probability Density Functions
- A.1 Uniform Distribution
- A.2 Gaussian Distribution
- A.3 Laplace Distribution
- A.4 Exponential Distribution
- A.5 Gamma Distribution
- A.6 Chi-Squared Distribution
- B Code Samples
- B.1 Naïve Sampling
- B.2 Theorem 1 Sampling
- B.3 Sampling with math and random
- B.4 Sampling with Numpy
- References
- Training Differentially Private Neural Networks with Lottery Tickets
- 1 Introduction
- 2 Preliminaries
- 2.1 Differential Privacy
- 2.2 Lottery Ticket Hypothesis
- 3 Differentially Private Lottery Ticket Hypothesis
- 3.1 Overview
- 3.2 DPLTH Walkthrough
- 3.3 Differential Privacy Guarantees of DPLTH
- 3.4 Discussion
- 4 Experiments
- 4.1 Datasets
- 4.2 Competitor
- 4.3 Setup
- 4.4 Main Comparison
- 4.5 Convergence and Early Stopping
- 4.6 Investigating the Score Function
- 4.7 Robustness to P
- 5 Related Work
- 6 Conclusion
- References
- Locality Sensitive Hashing with Extended Differential Privacy
- 1 Introduction
- 2 Related Work
- 2.1 Extended DP
- 2.2 Privacy-Preserving Friend Matching
- 2.3 Privacy-Preserving LSH
- 3 Preliminaries
- 3.1 Locality Sensitive Hashing (LSH)
- 3.2 Examples of LSHs
- 3.3 Approximate Nearest Neighbor Search
- 3.4 Privacy Measures and Privacy Mechanisms
- 4 Privacy Properties of LSH
- 5 LSH-Based Privacy Mechanisms
- 6 Privacy Analyses of the Mechanisms
- 6.1 LSHRR's Privacy W.r.t. the Particular LSH Function
- 6.2 LSHRR's Privacy W.r.t. the Distribution of LSH Functions
- 6.3 Privacy Guarantee for LapLSH
- 7 Experimental Evaluation
- 7.1 Datasets and Experimental Setup
- 7.2 Comparing Privacy and Utility
- 7.3 Experimental Results
- 7.4 Inapplicability of the RAPPOR
- 8 Conclusion
- A Total Privacy Budgets in Extended DP and LDP
- B More Details on the Privacy Analyses
- References
- Zero Knowledge
- MLS Group Messaging: How Zero-Knowledge Can Secure Updates
- 1 Introduction
- 2 Backgrounds
- 3 MLS Updates
- 3.1 Message Layer Security
- 3.2 Securing MLS Updates
- 4 ZK for a PRF on Committed Input and Output
- 4.1 ComInOutZK: A Bit-Wise Solution
- 4.2 A Second Solution: CopraZK
- 5 Conclusion
- A Key Size and Group Orders in MLS Updates
- B Security of Our Zero-Knowledge Protocols
- References
- More Efficient Amortization of Exact Zero-Knowledge Proofs for LWE
- 1 Introduction
- 1.1 Prior Work
- 1.2 Our Results
- 1.3 Technical Overview
- 2 Preliminaries
- 3 Basic Protocol
- 3.1 Proof Size and Concrete Parameter Choices
- 4 Amortized Protocol for a Fixed Public Randomness
- 4.1 Proof Size
- A The Hiding Property of Reed-Solomon Codes
- References
- Zero Knowledge Contingent Payments for Trained Neural Networks
- 1 Introduction
- 2 Preliminaries
- 3 Design Overview
- 4 Instantiation
- 4.1 zk-SNARKs-Based Solution
- 4.2 Libra-Based Solution
- 5 Security Analysis
- 6 Implementation and Experiments
- 7 Related Work
- 8 Conclusion
- A The Main Building Blocks of Libra
- B Proof of Theorem 1
- References
- Key Exchange
- Identity-Based Identity-Concealed Authenticated Key Exchange
- 1 Introduction
- 2 Preliminaries
- 2.1 Notation
- 2.2 Bilinear Pairings and Assumptions
- 2.3 Authenticated Encryption
- 3 Security Model
- 3.1 System and Adversary Setting
- 3.2 Definition of Security
- 4 Construction of IB-CAKE Protocol
- 5 Security Analysis of IB-CAKE
- 5.1 Proof of Label Security
- 5.2 Proof of ID-Concealed Session-Key Security
- 6 Comparison and Implementation
- A Structures of IB-CAKE Protocol with Asymmetric Bilinear Pairing
- A.1 Protocol Structure with Bilinear Pairing of Type-II
- A.2 Protocol Structure with Bilinear Pairing of Type-III
- B Review of the TFNS19-Protocol
- References
- Privacy-Preserving Authenticated Key Exchange: Stronger Privacy and Generic Constructions
- 1 Introduction
- 2 On Modeling Privacy in AKE
- 2.1 What Can(not) Be Handled by PPAKE
- 2.2 Privacy Goals in PPAKE
- 3 Our PPAKE Model
- 3.1 Security Model
- 3.2 Relation Between Privacy Notions
- 3.3 Discussion and Limitations of Our PPAKE Model
- 4 Constructing PPAKE with Strong Privacy
- 4.1 Achieving Weak MITM Private PPAKE Using Shared Secrets
- 4.2 Generic Construction of Strongly MITM Private PPAKE
- 4.3 Two-Move PPAKE Protocol Without Forward Privacy
- 5 Discussion and Future Work
- References
- Multi-party Computation
- Correlated Randomness Teleportation via Semi-trusted Hardware-Enabling Silent Multi-party Computation
- 1 Introduction
- 2 Preliminaries
- 3 Security Model
- 3.1 Semi-trusted Hardware Model
- 4 Correlated Randomness Teleportation
- 4.1 Random OT Teleportation
- 4.2 GC Teleportation with Applications to Silent 2PC
- 5 Security
- 6 Implementation and Benchmarks
- 7 Related Work
- 8 Conclusion
- A Appendix
- A.1 Security Proof of Our Main Theorems
- References
- Polynomial Representation Is Tricky: Maliciously Secure Private Set Intersection Revisited
- 1 Introduction
- 2 Related Work
- 3 Background
- 3.1 Representing Sets by Polynomials
- 3.2 Oblivious Linear Function Evaluation
- 3.3 Oblivious Polynomial Addition
- 3.4 Two-Party PSI
- 4 Attack 1: Making Honest Party Learn Incorrect Result
- 4.1 Attack Description
- 4.2 Attack Analysis
- 4.3 Candidate Mitigation
- 5 Attack 2: Learning Honest Party's Element Beyond the Intersection
- 5.1 Attack Description
- 5.2 Attack Analysis
- 5.3 Candidate Mitigations
- 6 Attack 3: Deleting Honest Party's Set Elements
- 6.1 Attack Description
- 6.2 Attack Analysis
- 6.3 Candidate Mitigation
- 7 Conclusion and Future Work
- A Identified Flaws In The Security Proofs
- A.1 Class 1: Not All Checks Have Been Included
- A.2 Class 2: Incomplete Simulator
- A.3 Class 3: Incomplete Definition Of Malformed Input
- B Attack 3 Theorems
- References
- Posters
- RIoTPot: A Modular Hybrid-Interaction IoT/OT Honeypot
- 1 Introduction
- 2 RIoTPot Design
- 3 Preliminary Results
- 4 Conclusion
- References
- Towards Automatically Generating Security Analyses from Machine-Learned Library Models
- 1 Introduction and Motivation
- 2 Vision
- 2.1 Phase 1: Generate Library Models
- 2.2 Phase 2: Generate Security Analyses
- 3 Experiments and Preliminary Results
- 4 Related Work
- 5 Conclusion and Future Work
- References
- Jamming of NB-IoT Synchronisation Signals
- 1 Introduction
- 2 The UE and eNodeB Synchronisation Process
- 3 Jamming the NB-IoT Synchronization Process
- 4 Jamming Evaluation
- 5 Conclusions
- References
- TPRou: A Privacy-Preserving Routing for Payment Channel Networks
- 1 Introduction
- 2 Our Design
- 3 Security Analysis
- 4 Performance Evaluation
- 5 Conclusion
- References
- Determining Asset Criticality in Cyber-Physical Smart Grid
- Abstract
- 1 Introduction: Context and Motivation
- 2 Related Work
- 3 Approach
- 3.1 System Model and Simulation Scenario
- 3.2 Proposed Method
- 4 Experimental Results and Evaluation
- 4.1 System Operations Under No Attack Scenario
- 4.2 System Operations Under Attack Scenario
- 5 Conclusion and Future Work
- References
- Signature-in-Signature: The Last Line of Defence in Case of Signing Key Compromise
- 1 Example Sig-in-Sig Scheme
- A Appendix
- References
- Author Index
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