2020 NDSS SP USENIX ICSE 关于模糊测试论文

• ICSE 2020

  • Typestate-Guided Fuzzer for Discovering Use-after-Free Vulnerabilities
  • MemLock: Memory Usage Guided Fuzzing
  • Ankou: Guiding Grey-box Fuzzing towards Combinatorial Difference
  • JVM Fuzzing for JIT-Induced Side-Channel Detection
  • Targeted Greybox Fuzzing with Static Lookahead Analysis
  • Fuzz Testing based Data Augmentation to Improve Robustness of Deep Neural Networks
  • sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts
  • HyDiff: Hybrid Differential Software Analysis

• NDSS 2020

  • HYPER-CUBE: High-Dimensional Hypervisor Fuzzing
  • HotFuzz: Discovering Algorithmic Denial-of-Service Vulnerabilities Through Guided Micro-Fuzzing
  • HFL: Hybrid Fuzzing on the Linux Kernel
  • Not All Coverage Measurements Are Equal: Fuzzing by Coverage Accounting for Input Prioritization

• S&P 2020

  • SAVIOR: Towards Bug-Driven Hybrid Testing
  • RetroWrite: Statically Instrumenting COTS Binaries for Fuzzing and Sanitization
  • IJON: Exploring Deep State Spaces via Fuzzing
  • PANGOLIN: Incremental Hybrid Fuzzing with Polyhedral Path Abstraction
  • KRace: Data Race Fuzzing for Kernel File Systems
  • [Fuzzing JavaScript Engines with Aspect-preserving Mutation]

• USENIX Security 2020

  • GREYONE: Data Flow Sensitive Fuzzing
  • FuzzGuard: Filtering out Unreachable Inputs in Directed Grey-box Fuzzing through Deep Learning
  • ParmeSan: Sanitizer-guided Greybox Fuzzing
  • EcoFuzz: Adaptive Energy-Saving Greybox Fuzzing as a Variant of the Adversarial Multi-Armed Bandit
  • FANS: Fuzzing Android Native System Services via Automated Interface Analysis

关于模糊测试综述文章：

• Fuzzing: Hack, Art, and Science
• Survey of Directed Fuzzy Technology
• A Review of Machine Learning Applications in Fuzzing
• A systematic review of fuzzing based on machine learning techniques
• The Art, Science, and Engineering of Fuzzing: A Survey
• Fuzzing: Art, Science, and Engineering
• Fuzzing: a survey
• Fuzzing: State of the art