Artifacts
To help support the reproducibility for research results, ACSAC encourages authors of accepted papers to submit software they develop and datasets they use to perform their research and make them publicly available to the entire community. We believe that this is an important initiative that can help the entire community increase its reputation, and make research in the security field proceeds faster by taking advantage of systems previously built by other researchers. We thank all the authors who participated in this initiative, now in its third year!
For more details on the artifact evaluations process, please refer to the Call for Paper Artifacts.
Link Legend: GitHub Web archive
The artifacts associated with the research are found to be documented, consistent, complete, exercisable, and include appropriate evidence of verification and validation.
- Learning from Failures: Secure and Fault-Tolerant Aggregation for Federated Learning
- Better Together: Attaining the Triad of Byzantine-robust Federated Learning via Local Update Amplification
- DeView: Confining Progressive Web Applications by Debloating Web APIs
- Reconstruction Attack on Differential Private Trajectory Protection Mechanisms
- Practical Binary Code Similarity Detection with BERT-based Transferable Similarity Learning
- Curiosity-Driven and Victim-Aware Adversarial Policies
- TyPro: Forward CFI for C-Style Indirect Function Calls Using Type Propagation
- Snappy: Efficient Fuzzing with Adaptive and Mutable Snapshots
- CryptoGo: Automatic Detection of Go Cryptographic API Misuses
- Trebiz: Byzantine Fault Tolerance with Byzantine Merchants
- ENIDrift: A Fast and Adaptive Ensemble System for Network Intrusion Detection under Real-world Drift
- FAuST: Striking a Bargain between Forensic Auditing’s Security and Throughput
- DF-SCA: Dynamic Frequency Side Channel Attacks are Practical
- Transformer-Based Language Models for Software Vulnerability Detection
- BayesImposter: Bayesian Estimation Based .bss Imposter Attack on Industrial Control Systems
- Make Data Reliable : An Explanation-powered Cleaning on Malware Dataset Against Backdoor Poisoning Attacks
- Cloak: Transitioning States on Legacy Blockchains Using Secure and Publicly Verifiable Off-Chain Multi-Party Computation
- More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
- ArchiveSafe LT: Secure Long-term Archiving System
- User Perceptions of the Privacy and Usability of Smart DNS
- SPACELORD: Private and Secure Smart Space Sharing
- A Qualitative Evaluation of Reverse Engineering Tool Usability
- User Perceptions of Five-Word Passwords
- From Hindsight to Foresight: Enhancing Design Artifacts for Business Logic Flaw Discovery
- Squeezing More Utility via Adaptive Clipping on Deferentially Private Gradients in Federated Meta-Learning
The artifacts associated with the paper are of a quality that significantly exceeds minimal functionality. That is, they have all the qualities of the Artifacts Evaluated – Functional level, but, in addition, they are very carefully documented and well-structured to the extent that reuse and repurposing is facilitated. In particular, norms and standards of the research community for artifacts of this type are strictly adhered to.
- Formal Modeling and Security Analysis for Intra-level Privilege Separation
- Designing a Provenance Analysis for SGX Enclaves
- SpacePhish: The Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning
- DitDetector: Bimodal Learning based on Deceptive Image and Text for Macro Malware Detection
- Drone Authentication via Acoustic Fingerprint
- Alphuzz: Monte Carlo Search on Seed-Mutation Tree for Coverage-Guided Fuzzing
- SLOPT: Bandit Optimization Framework for Mutation-Based Fuzzing
- Parallel Small Polynomial Multiplication for Dilithium: A Faster Design and Implementation
- Assessing Model-free Anomaly Detection in Industrial Control Systems Against Generic Concealment Attacks
- Stopping Silent Sneaks: Defending against Malicious Mixes with Topological Engineering
- Making Memory Account Accountable: Analyzing and Detecting Memory Missing-account bugs for Container Platforms
- StateDiver: Testing Deep Packet Inspection Systems with State-Discrepancy Guidance
- Stepping out of the MUD: Contextual threat information for IoT devices with manufacturer-provided behaviour profiles
- Randezvous: Making Randomization Effective on MCUs
- Analysis of Payment Service Provider SDKs in Android
- One Fuzz Doesn’t Fit All: Optimizing Directed Fuzzing via Target-tailored Program State Restriction
- POPKORN: Popping Windows Kernel Drivers At Scale
- Privacy-Preserving Trajectory Matching on Autonomous Unmanned Aerial Vehicles