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!
For more details on the artifact evaluations process, please refer to the Call for Paper Artifacts.
Link Legend: 
GitHub 
Web archive
This badge signals that author-created digital objects used in the research (including data and code) are permanently archived in a public repository that assigns a global identifier and guarantees persistence, and are made available via standard open licenses that maximize artifact availability.
- TRACES: TEE-based Runtime Auditing for Commodity Embedded Systems
- Leveraging Intensity as a New Feature to Detect Physical Adversarial Attacks Against LiDARs
- Physical ID-Transfer Attacks against Multi-Object Tracking via Adversarial Trajectory
- R+R: Understanding Hyperparameter Effects in DP-SGD
- ConProv: A Container-Aware Provenance System for Attack Investigation
- T-Edge: Trusted Heterogeneous Edge Computing
- FLUENT: A Tool for Efficient Mixed-Protocol Semi-Private Function Evaluation
This badge signals that all relevant author-created digital objects used in the research (including data and code) were reviewed according to the criteria provided by the badge issuer.
- Faking deduplication to prevent timing side-channel attacks on memory deduplication
- SecurityHub: Electromagnetic Fingerprinting USB Peripherals using Backscatter-assisted Commodity Hardware
- R+R: Demystifying ML-Assisted Side-Channel Analysis Framework: A Case of Image Reconstruction
- You Only Perturb Once: Bypassing (Robust) Ad-Blockers Using Universal Adversarial Perturbations
- Assault and Battery: Evaluating the Security of Power Conversion Systems Against Electromagnetic Injection Attacks
- R+R: Towards Reliable and Generalizable Differentially Private Machine Learning
- RouTEE: Secure, Scalable, and Efficient Off-Chain Payments using Trusted Execution Environments
- R+R: Matrioska: A User-Centric Defense Against Virtualization-Based Repackaging Malware on Android
- Stealing Watermarks of Large Language Models via Mixed Integer Programming
- WiShield: Fine-grained Countermeasure Against Malicious Wi-Fi Sensing in Smart Home
- AirBugCatcher: Automated Wireless Reproduction of IoT Bugs
- Harnessing Multiplicity: Granular Browser Extension Fingerprinting through User Configurations
- Not All Tokens Are Equal: Membership Inference Attacks Against Fine-tuned Language Models
- Reading It like an Open Book: Single-trace Blind Side-channel Attacks on Garbled Circuit Frameworks
- Towards a Taxonomy of Challenges in Security Control Implementation
- Link Inference Attacks in Vertical Federated Graph Learning
- On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World
This badge signals that an additional step was taken or facilitated by the badge issuer (e.g., publisher, trusted third-party certifier) to certify that an independent party has regenerated computational results using the author‑created research objects, methods, code, and conditions of analysis.
- SpecCFA: Enhancing Control Flow Attestation/Auditing via Application-Aware Sub-Path Speculation
- VIMU: Effective Physics-based Realtime Detection and Recovery against Stealthy Attacks on UAVs
- R+R: Revisiting Graph Matching Attacks on Privacy-Preserving Record Linkage
- FreeAuth: Privacy-Preserving Email Ownership Authentication with Verification-Email-Free
- No Leakage Without State Change: Repurposing Configurable CPU Exceptions to Prevent Microarchitectural Attacks
- Robust Device Authentication in Multi-Node Networks: ML-Assisted Hybrid PLA Exploiting Hardware Impairments
- Single Sign-On Privacy: We Still Know What You Did Last Summer
- Sidecar: Leveraging Debugging Extensions in Commodity Processors to Secure Software
- VaktBLE: A Benevolent Man-in-the-Middle Bridge to Guard against Malevolent BLE Connections
- R+R: Security Vulnerability Dataset Quality Is Critical
- FA-SEAL: Forensically Analyzable Symmetric Encryption for Audit Logs
- Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
- Privacy-Preserving Verifiable Neural Network Inference Service
- BinHunter: A Fine-Grained Graph Representation for Localizing Vulnerabilities in Binary Executables
- FedCAP: Robust Federated Learning via Customized Aggregation and Personalization
- Manifest Problems: Analyzing Code Transparency for Android Application Bundles
- Model-Manipulation Attacks Against Black-Box Explanations
- R+R: A Systematic Study of Cryptographic Function Identification Approaches in Binaries
- ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer
- Leaky Autofill: An Empirical Study on the Privacy Threat of Password Managers' Autofill Functionality
- TATTOOED: A Robust Deep Neural Network Watermarking Scheme based on Spread-Spectrum Channel Coding
- SECvma: Virtualization-based Linux Kernel Protection for Arm
- A Security Alert Investigation Tool Supporting Tier 1 Analysts in Contextualizing and Understanding Network Security Events
- CryptoPyt: Unraveling Python Cryptographic APIs Misuse With Precise Static Taint Analysis
- I'll Be There for You! Perpetual Availability in the A^8 MVX System
- I Can Show You the World (of Censorship): Extracting Insights from Censorship Measurement Data Using Statistical Techniques
- Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning
- Practical Light Clients for Committee-Based Blockchains
- BlueScream: Screaming Channels on Bluetooth Low Energy