- [CCS'21] SyzGen: Automated Generation of Syscall Specification of Closed-Source macOS Drivers
- [Oakland'21] NTFUZZ: Enabling Type-Aware Kernel Fuzzing on Windows with Static Binary Analysis
- [SOSP'21] HEALER: Relation Learning Guided Kernel Fuzzing
- [SOSP'21] Snowboard: Finding Kernel Concurrency Bugs through Systematic Inter-thread Communication Analysis
- [Oakland'22] GREBE: Unveiling Exploitation Potential for Linux Kernel Bugs
- [Oakland'20] KRACE: Data Race Fuzzing for Kernel File Systems
- [Oakland'19] Razzer: Finding Kernel Race Bugs through Fuzzing
- [Security'19] Precise and Scalable Detection of Double-Fetch Bugs in OS Kernels
- [Security'17] How Double-Fetch Situations turn into DoubleFetch Vulnerabilities: A Study of Double Fetches in the Linux Kernel
- [ESEC/FSE'20] UBITect: a precise and scalable method to detect use-before-initialization bugs in Linux kernel
- [CCS'16] UniSan: Proactive Kernel Memory Initialization to Eliminate Data Leakages
- [Security'21] Static Detection of Unsafe DMA Accesses in Device Drivers
- [CCS'21] CPscan: Detecting Bugs Caused by Code Pruning in IoT Kernels
- [CCS'21] Statically Discovering High-Order Taint Style Vulnerabilities in OS Kernels
- [Security'21] An Investigation of the Android Kernel Patch Ecosystem
- [Security'21] Preventing Use-After-Free Attacks with Fast Forward Allocation
- [Security'21] Nyx: Greybox Hypervisor Fuzzing using Fast Snapshots and Affine Types
- [CCS'21] Demons in the Shared Kernel: Abstract Resource Attacks Against OS-level Virtualization
- [CCS'21] V-SHUTTLE: Scalable and Semantics-Aware Hypervisor Fuzzing
- [Oakland'21] A Secure and Formally Verified Linux KVM Hypervisor