Intro
Preface
Organization
Abstracts of Keynote Addresses
The Rise of Cyber Physical Security
Research and Engineering Challenges of Blockchain and Web3
Security and Privacy in Federated Learning
Web3 and the Interoperability of Asset Networks
Abstracts of Invited Addresses
Securing Cyber-Physical and IoT Systems in Smart Living Environments
Advanced Persistent Threats: A Study in Indian Context
Technology Transfer from Security Research Projects: A Personal Perspective
Contents

Ostinato: Cross-host Attack Correlation Through Attack Activity Similarity Detection
1 Introduction
2 Problem Description
3 Approach and Architecture
3.1 Tagged Provenance Graphs
3.2 Identifying Similar Nodes
3.3 Edge Label Similarity
3.4 Graph Similarity Detection
4 Evaluation
4.1 Ostinato Efficacy
4.2 Node Similarity Accuracy
4.3 Run-Time Performance
4.4 Threat Alert Fatigue Mitigation
4.5 Comparison with Other Tools
5 Related Work
6 Conclusion
References
DKS-PKI: A Distributed Key Server Architecture for Public Key Infrastructure

1 Introduction
2 Related Work
3 DKS-PKI Architecture
3.1 Overview
3.2 Node Operations
3.3 Authoritative Signing Keys (ASKs)
3.4 Certificate Registration/Issuance and Storage
3.5 Certificate Distribution
3.6 Certificate Revocation
3.7 Stored-Data Validation
4 Evaluation
4.1 Security Analysis
4.2 Implementation
4.3 Experimental Environment
4.4 Performance Analysis
5 Conclusion
References
Generating-Set Evaluation of Bloom Filter Hardening Techniques in Private Record Linkage
1 Introduction
2 Background and Related Work

2.1 Linkage with Bloom Filters
2.2 Hardening Bloom Filters
2.3 Privacy Measures
3 Generating-Sets and Amplification
3.1 Generating-Set Amplification Factor
3.2 Amplification Factor in Deterministic Methods
3.3 Amplification Factor in Probabilistic Methods
4 Parameter Selection in Probabilistic Methods
5 Empirical Evaluation
5.1 Setup
5.2 Bit Frequency Measures
5.3 Generating-Set Amplification Factor
5.4 Linkage Quality
5.5 Discussion
6 Conclusion and Future Work
References

.26em plus .1em minus .1emSHIELD: A Multimodal Deep Learning Framework for Android Malware Detection
1 Introduction
2 Related Work
2.1 Static Analysis Based Android Malware Detection Techniques
2.2 Dynamic Analysis Based Android Malware Detection Techniques
2.3 Hybrid Analysis Based Android Malware Detection Techniques
3 SHIELD: The Proposed Framework
3.1 Feature Extraction
3.2 Markov Image Generation
3.3 Network Construction
4 Experimental Evaluation
4.1 Dataset
4.2 Evaluation Environment
4.3 Performance Analysis Based Markov Images Separately