brycewang-stanford AI Security Papers Guide (BIG4 Venues)
Overview
A curated collection of AI security papers from the top-4 security conferences: IEEE S&P, ACM CCS, USENIX Security, and NDSS. Covers adversarial attacks, model stealing, data poisoning, privacy attacks, deepfake detection, and LLM security. Organized by year and venue, focusing exclusively on peer-reviewed work from these prestigious venues.
Venues
| Venue | Full Name | Focus |
|---|---|---|
| S&P | IEEE Symposium on Security and Privacy | Broad security + privacy |
| CCS | ACM Conference on Computer and Communications Security | Systems security |
| USENIX | USENIX Security Symposium | Systems + network security |
| NDSS | Network and Distributed System Security | Network security |
Topic Categories
AI Security (BIG4)
├── Adversarial ML
│ ├── Evasion attacks (adversarial examples)
│ ├── Poisoning attacks (backdoors, trojans)
│ ├── Model stealing (extraction, distillation)
│ └── Defenses (certified robustness, detection)
├── Privacy Attacks
│ ├── Membership inference
│ ├── Model inversion
│ ├── Attribute inference
│ └── Training data extraction
├── LLM Security
│ ├── Prompt injection
│ ├── Jailbreaking
│ ├── Data leakage
│ └── Alignment attacks
├── Deepfakes
│ ├── Generation methods
│ ├── Detection techniques
│ └── Watermarking
└── Federated Learning Security
├── Byzantine attacks
├── Gradient leakage
└── Secure aggregation
Key Papers by Year
# Recent highlights
papers_2024_2025 = [
{"title": "Not What You've Signed Up For: "
"Compromising Real-World LLM-Integrated Applications",
"venue": "S&P 2024", "topic": "LLM security"},
{"title": "Prompt Stealing Attacks Against "
"Text-to-Image Generation Models",
"venue": "S&P 2024", "topic": "Prompt extraction"},
{"title": "Backdoor Attacks on Language Models",
"venue": "CCS 2024", "topic": "NLP backdoors"},
{"title": "Membership Inference in LLMs",
"venue": "USENIX 2024", "topic": "Privacy"},
]
for p in papers_2024_2025:
print(f"[{p['venue']}] {p['title']}")
print(f" Topic: {p['topic']}")
Research Trends
### Emerging Areas (2024-2025)
1. **LLM security** — Jailbreaking, prompt injection, agent attacks
2. **Supply chain attacks** — Poisoned models, malicious packages
3. **Multi-modal attacks** — Cross-modal adversarial examples
4. **Agent security** — Attacks on LLM-based autonomous systems
5. **Watermarking** — LLM output detection, IP protection
6. **Unlearning** — Machine unlearning verification and attacks
Use Cases
- Security research: Find state-of-the-art attack/defense methods
- Threat modeling: Understand AI system vulnerabilities
- Literature review: Systematic coverage of BIG4 AI security
- Course material: Graduate-level AI security curriculum
- Red teaming: Learn evaluation techniques for AI systems