
Applied Cryptography and Network Security
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The 54 full papers included in these proceedings were carefully reviewed and selected from 230 submissions. They have been organized in topical sections as follows: Part I: Cryptographic protocols; encrypted data; signatures; Part II: Post-quantum; lattices; wireless and networks; privacy and homomorphic encryption; symmetric crypto; Part III: Blockchain; smart infrastructures, systems and software; attacks; users and usability.
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Persons
Content
- Intro
- Preface
- Organization
- Abstracts of Keynote Talks
- Applying Machine Learning to Securing Cellular Networks
- Real-World Cryptanalysis
- CAPTCHAs: What Are They Good For?
- Contents - Part III
- Blockchain
- Mirrored Commitment: Fixing ``Randomized Partial Checking'' and Applications
- 1 Introduction
- 1.1 Notation
- 2 Chaumian Randomized Partial Checking (RPC) Mix Net
- 2.1 Protocol Description
- 2.2 RPC Audit
- 2.3 Attacks on RPC
- 3 Mirrored Randomized Partial Checking (mRPC)
- 3.1 Protocol Description
- 3.2 mRPC Audit
- 3.3 Attack Examples on mRPC
- 3.4 Security of mRPC
- 4 Privacy Guarantees of RPC and mRPC
- 4.1 Constant Number of Mix-Servers
- 4.2 Mixing Time
- 5 Application: CryptoCurrency Unlinkability
- 6 Conclusions
- A Proofs
- A.1 Proof of Lemma 4
- A.2 Proof of Lemma 6
- A.3 Proof of Lemma 7
- References
- Bitcoin Clique: Channel-Free Off-Chain Payments Using Two-Shot Adaptor Signatures
- 1 Introduction
- 1.1 Our Contributions
- 1.2 Related Work
- 2 Preliminaries
- 3 Model
- 3.1 Blockchain and Transaction Model
- 3.2 Commit-Chain Model
- 3.3 Communication and Adversarial Assumptions
- 3.4 Security and Performance Guarantees
- 4 Protocol Overview
- 5 Bitcoin Clique Protocol
- 6 Future Work
- A Bitcoin Clique Healing
- A.1 Healing Extension Details
- A.2 Discussion and Future Work
- References
- Programmable Payment Channels
- 1 Introduction
- 1.1 Our Contributions
- 1.2 Related Work
- 2 Preliminaries
- 3 Programmable Payment Channels
- 3.1 Defining FPPC
- 3.2 PPC Preliminaries
- 3.3 Ideal Functionality FPPC
- 3.4 Concrete Implementation of FPPC
- 3.5 Lightweight Applications of Programmable Payments
- 3.6 Implementation and Evaluation
- 4 State Channels from FPPC
- 4.1 Modifying FPPC to Capture State Channels
- 4.2 Defining FSC
- 4.3 Implementing FSC in theFPPC-Hybrid World
- 5 Conclusions
- References
- Fair Private Set Intersection Using Smart Contracts
- 1 Introduction
- 1.1 Other Coin-Compensated PSI
- 2 Related Work
- 3 Preliminaries and Notations
- 4 Fair PSI Using Smart Contracts
- 4.1 Smart Contract as the TTP in Optimistic Mutual PSI
- 4.2 Security Model
- 4.3 Ideal Functionality for Coin-Compensated PSI
- 5 A Coin-Compensated Fair SC-Aided PSI
- 5.1 Security Analysis
- 6 Improving the Efficiency of
- 6.1 Our Technique for Optimizing the Protocol
- 6.2 Overview of *
- 6.3 Security Analysis
- 7 Complexity Analysis
- 8 Implementation
- 8.1 Evaluation
- 9 Concluding Remarks
- References
- Powers-of-Tau to the People: Decentralizing Setup Ceremonies
- 1 Introduction
- 2 Related Work
- 2.1 Multiparty Setup Ceremonies
- 2.2 Setup Ceremonies in Practice
- 2.3 Proof Systems with Transparent Setup
- 3 A Powers-of-Tau System: Definitions
- 4 Powers-of-Tau Setup with Full Data On-Chain
- 4.1 Security
- 5 Powers-of-Tau Setup Protocol with Data Off-Chain
- 5.1 Off-Chain Setup Using a Transparent Succinct Proof
- 5.2 Off-Chain Setup Using AFGHO Commitments On-Chain
- 6 Implementation and Evaluation on Ethereum
- 7 Concluding Discussion and Open Problems
- 7.1 Incentives for Participation
- 7.2 Verifying Participation
- 7.3 Sequential Participation and Denial-of-Service
- 7.4 Verification with General-Purpose Roll-Ups
- 7.5 Protocol-Specific ZK Rollups via Proof Batching
- 7.6 Protocol-Specific Optimistic Verification and Checkpointing
- 7.7 Fully Off-Chain Verification via IVC/PCD
- 7.8 Forking/Re-starting
- A Proof of Theorem 2
- B Inner-Pairing Product Arguments for Sect.5.2
- C Off-Chain Setup from IPP Arguments with a Smaller Setup
- D Powers-of-Tau with a Punctured Point
- References
- Smart Infrastructures, Systems and Software
- Self-sovereign Identity for Electric Vehicle Charging
- 1 Introduction
- 2 Background
- 2.1 E-mobility
- 2.2 Self-Sovereign Identity (SSI)
- 3 Related Work
- 4 System Model and Requirement Analysis
- 4.1 Scope
- 4.2 Attacker Model
- 4.3 Functional Requirements
- 4.4 Security and Privacy Requirements
- 5 SSI Concept
- 5.1 Concept Overview
- 5.2 Provisioning DID Creation
- 5.3 Contract Credential Installation
- 5.4 Charging Process and Credential Validation
- 5.5 Integration into ISO 15118-20
- 6 Implementation
- 7 Evaluation
- 7.1 Performance Measurements
- 7.2 Security and Privacy Analysis with Tamarin
- 7.3 Discussion of Requirements
- 8 Conclusion
- References
- ``Hello? Is There Anybody in There?'' Leakage Assessment of Differential Privacy Mechanisms in Smart Metering Infrastructure
- 1 Introduction
- 2 Preliminaries
- 2.1 Differential Privacy
- 2.2 Statistical t-test Analysis
- 3 System and Threat Model
- 3.1 Threat Surfaces
- 3.2 Capabilities of the Adversary
- 3.3 Goal of the Adversary
- 4 Formal Analysis of Leakage Due to Privacy-Utility Trade-Off in Smart Metering Systems
- 5 Proposed Attack Methodology
- 5.1 Precomputation Phase
- 5.2 t-test Based Attack Methodology
- 6 Evaluation of the Proposed Attack Methodology
- 6.1 Experimental Setup
- 6.2 Experimental Evaluation
- 7 Discussion
- 8 Conclusion and Future Work
- References
- Security Analysis of BigBlueButton and eduMEET
- 1 Introduction
- 2 Background
- 2.1 WebRTC
- 2.2 WebRTC Architectures in Conferencing Systems
- 3 Analysis Method
- 3.1 High-Level Analysis
- 3.2 Source Code Supported Security Analysis
- 4 Architectures of the Analyzed Open-Source Conferencing Systems (RQ1)
- 4.1 Shared Architecture
- 4.2 Implementation of BigBlueButton
- 4.3 Implementation of eduMEET
- 5 Features and User Roles (RQ2)
- 5.1 Comparison of Features
- 5.2 User Roles
- 6 Attacker Model
- 7 Evaluation (RQ3)
- 7.1 BigBlueButton
- 7.2 eduMEET
- 7.3 Responsible Disclosure
- 8 Discussion
- 8.1 BigBlueButton
- 8.2 eduMEET
- 8.3 Limitations
- 9 Related Work
- 10 Conclusions and Future Work
- A Appendix
- A.1 eduMEET
- A.2 Status of Fixes in BigBlueButton
- References
- An In-Depth Analysis of the Code-Reuse Gadgets Introduced by Software Obfuscation
- 1 Introduction
- 2 Background
- 2.1 Code Obfuscation
- 2.2 Code-Reuse Attack
- 3 Code-Reuse Gadgets Introduced by Obfuscation
- 3.1 Benchmark and Obfuscation Selection
- 3.2 Gadget Measurement
- 4 Study Results
- 4.1 Gadget Quantity
- 4.2 Gadget Exploitability
- 4.3 Gadget Quality
- 4.4 Code-Reuse Attack Risk
- 5 The Anatomy of the Obfuscations and Gadgets
- 5.1 Instructions Substitution
- 5.2 Control Flow Flattening
- 5.3 Bogus Control Flow
- 5.4 Virtualization
- 5.5 Just-In-Time Dynamic
- 5.6 Self-modification
- 5.7 Encode Components
- 6 Mitigation
- 6.1 Strategy
- 6.2 Evaluation
- 7 Related Work
- 8 Conclusion
- References
- ProvIoT: Detecting Stealthy Attacks in IoT through Federated Edge-Cloud Security
- 1 Introduction
- 2 Background
- 2.1 Fileless Attacks on IoT Devices
- 2.2 System Provenance and Graph Learning
- 3 Threat Model
- 4 System Overview
- 4.1 Local Brain
- 4.2 Cloud Brain
- 5 Federated Detection
- 5.1 Graph Building and Path Selection
- 5.2 Document Embedding Model
- 5.3 Federated Autoencoder
- 6 Implementation
- 7 Evaluation
- 7.1 Dataset
- 7.2 Experimental Protocol
- 7.3 IoT Malware Detection
- 7.4 APT Detection
- 7.5 Federated Learning Benefits
- 7.6 ProvIoT Overhead
- 8 Limitations
- 9 Related Work
- 10 Discussion and Future Work
- 11 Conclusion
- A Appendix
- A.1 IoT Workload.
- A.2 Dataset Statistics.
- A.3 APT Scenarios
- References
- Attacks
- A Practical Key-Recovery Attack on LWE-Based Key-Encapsulation Mechanism Schemes Using Rowhammer
- 1 Introduction
- 1.1 Paper Organization
- 2 Preliminaries
- 2.1 Learning with Errors (LWE) Problem and Its Variants
- 2.2 LPR Public-Key Encryption
- 2.3 Kyber
- 2.4 Saber
- 2.5 Related Works
- 3 Our Attack Using Binary Decision Tree on the LPR-Based Schemes
- 3.1 Implementing a Parallel Plaintext Checking (PC) Oracle
- 3.2 Generic Attack Model Using PC Oracle
- 3.3 Model for Kyber and Saber
- 3.4 Comparing Our Attack with the State-of-the-Art
- 4 Realization of the Fault Model
- 4.1 Nature of the Fault in the Attack
- 4.2 Our Target Devices
- 4.3 Probabilities of Incorporating Precise Fault Using Random Rowhammer
- 5 Discussion and Future Direction
- 5.1 Shuffling and Masking:
- 5.2 Extension of Our Attack on Other PQC Schemes
- 5.3 Combining of Lattice Reduction Techniques with Our Attack
- 5.4 Possible Countermeasures
- References
- A Side-Channel Attack on a Higher-Order Masked CRYSTALS-Kyber Implementation
- 1 Introduction
- 2 Previous Work
- 3 Background
- 3.1 Notation
- 3.2 Kyber Algorithm
- 4 Adversary Model
- 5 Attack Description
- 5.1 Profiling Stage
- 5.2 Attack Stage
- 6 Experimental Setup
- 7 Leakage Analysis
- 7.1 Unprotected Message Encoding
- 7.2 Masked Message Encoding
- 7.3 Finding New Leakage Points
- 8 Neural Network Training
- 8.1 Trace Acquisition and Pre-processing
- 8.2 Network Architecture and Training Parameters
- 9 New Chosen Ciphertext Construction Method
- 9.1 Constructing Chosen Ciphertexts
- 9.2 Selecting Optimal Mapping
- 10 Experimental Results
- 10.1 Message Recovery Attack
- 10.2 Secret Key Recovery Attack
- 11 Countermeasures
- 12 Conclusion
- References
- Time Is Money, Friend! Timing Side-Channel Attack Against Garbled Circuit Constructions
- 1 Introduction
- 2 Background and Adversary Model
- 2.1 Yao's Garbled Circuit (GC)
- 2.2 k-means Algorithm
- 2.3 Cache Architecture
- 2.4 Adversary Model
- 3 Timing Side-Channel Leakage in Garbling Tools: An Observation
- 4 Goblin and Its Building Blocks
- 4.1 Our Eviction Method: Junk Generator
- 4.2 Measuring Time on CPUs
- 4.3 Recovering Garbler's Input
- 4.4 Performance Metric
- 5 Experimental Results
- 5.1 Results for Benchmark Functions
- 5.2 Scalability of Goblin
- 5.3 Impact of the Number of Traces
- 6 Discussion
- 6.1 Potential Countermeasures
- 7 Conclusion
- 8 Responsible Disclosure
- References
- Related-Tweak and Related-Key Differential Attacks on HALFLOOP-48
- 1 Introduction
- 2 Preliminaries
- 2.1 Differential Cryptanalysis
- 2.2 Related-Key and Related-Tweak Differential Cryptanalyses
- 2.3 Specification of HALFLOOP-48
- 3 Automatic Search of Differentials
- 3.1 Boolean Satisfiability Problem
- 3.2 SAT Models for Linear Operations of HALFLOOP-48
- 3.3 SAT Model for the S-Box of HALFLOOP-48
- 3.4 SAT Model for the Objective Function
- 3.5 Finding More Differential Characteristics in the Differential
- 4 Differential Properties of HALFLOOP-48
- 4.1 Conventional Differential Properties of HALFLOOP-48
- 4.2 Related-Tweak Differential Properties of HALFLOOP-48
- 4.3 Related-Key Differential Properties of HALFLOOP-48
- 5 Differential Attacks on HALFLOOP-48
- 5.1 Related-Tweak Differential Attack on HALFLOOP-48
- 5.2 Full-Round Related-Key Differential Attack on HALFLOOP-48
- 6 Conclusion
- References
- Users and Usability
- How Users Investigate Phishing Emails that Lack Traditional Phishing Cues
- 1 Introduction
- 2 Background
- 3 Related Work
- 4 Method and Study Design
- 4.1 Participant Recruitment
- 4.2 Ethical Study Design
- 4.3 Email and Webpage Content Design
- 4.4 Data Collection and Cleaning
- 5 Overview of Study Data and Participant Population
- 6 Study Results
- 6.1 Mapping of Responses to the Human-In-The-Loop-Model
- 6.2 Impact of Features on Participants' Reactions
- 7 Discussion and Contextualization of Results
- 7.1 Noticing, Expecting and Suspecting Context
- 7.2 Investigative Measures
- 7.3 Biases and Limitations
- 8 Future Work
- 9 Conclusion
- A Appendix: Survey Instrument
- A.1 Demography
- A.2 Phishing Emails and Reactions
- A.3 IT-Context and Sensitization
- B Appendix: Large Scale Images of Phishing Content
- C Appendix: HITL-Model: Figures
- D Appendix: Resulting Correlations
- References
- Usable Authentication in Virtual Reality: Exploring the Usability of PINs and Gestures
- 1 Introduction
- 2 Background
- 2.1 Virtual Reality
- 2.2 Authentication
- 2.3 Usability
- 3 Related Work
- 3.1 Interaction in VR
- 3.2 Authentication in VR
- 3.3 Usability Issues in VR Authentication
- 4 Study Design and Implementation
- 4.1 Methodology
- 4.2 Recruitment
- 4.3 Data Collection
- 4.4 Pilot Testing
- 4.5 Data Analysis
- 4.6 Ethical Considerations
- 5 Results
- 5.1 Authentication Type and Usability
- 5.2 Authentication Type and Login Time
- 5.3 PIN: Experienced vs. First-Time User
- 5.4 Gesture: Experienced vs. First-Time User
- 6 Discussion
- 6.1 Impact of Authentication Type on Usability in VR
- 6.2 Impact of Experience on Usability in VR
- 6.3 Limitations
- 7 Conclusion and Future Work
- A System Usability Scale
- References
- Living a Lie: Security Analysis of Facial Liveness Detection Systems in Mobile Apps
- 1 Introduction
- 2 Background
- 2.1 Facial Recognition Pipeline
- 2.2 Design Patterns of Mobile Facial Recognition Systems
- 2.3 Modes of Liveness Detection
- 3 Threat Model
- 4 Mobile Facial Liveness Detection Protocols
- 4.1 General Protocol Flow
- 4.2 Design and Implementation Details
- 5 Weakness of Liveness Detection SDKs
- 5.1 Insufficient Client-Side Code Protection
- 5.2 Insecure Protocol Design
- 5.3 Flaws in SDK Implementations
- 5.4 Mistakes by App Developers
- 6 Empirical Study
- 6.1 Retrieval of Face SDKs
- 6.2 Security Metrics of Face SDKs
- 6.3 Face SDKs in High-Profile Financial Apps
- 6.4 Market Scale Evaluation
- 6.5 Case Study
- 7 Discussion on Mitigation
- 8 Related Work
- 9 Conclusion
- A Flawed Encryption Scheme and Oracle Attack
- B Face SDK Scanning Result of App Categories
- C Reference Protocol with Security and Usability Consideration
- References
- Author Index
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