4 citations · 7 across the 6 of their papers we have counts for
6 papers
FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning
Kaled M. Alshmrany, Mohannad Aldughaim, Chenfeng Wei +3
We present FuSeBMC-AI, a test generation tool grounded in machine learning techniques. FuSeBMC-AI extracts various features from the program and employs support vector machine and…
FuSeBMC v4: Improving code coverage with smart seeds via BMC, fuzzing and static analysis
Kaled M. Alshmrany, Mohannad Aldughaim, Ahmed Bhayat +1
Bounded model checking (BMC) and fuzzing techniques are among the most effective methods for detecting errors and security vulnerabilities in software. However, there are still sho…
FuSeBMC v.4: Smart Seed Generation for Hybrid Fuzzing
Kaled M. Alshmrany, Mohannad Aldughaim, Ahmed Bhayat +1
FuSeBMC is a test generator for finding security vulnerabilities in C programs. In earlier work [4], we described a previous version that incrementally injected labels to guide Bou…
FuSeBMC: A White-Box Fuzzer for Finding Security Vulnerabilities in C Programs
Kaled M. Alshmrany, Rafael S. Menezes, Mikhail R. Gadelha +1
We describe and evaluate a novel white-box fuzzer for C programs named FuSeBMC, which combines fuzzing and symbolic execution, and applies Bounded Model Checking (BMC) to find secu…
Incremental Symbolic Bounded Model Checking of Software Using Interval Methods via Contractors
Mohannad Aldughaim, Kaled Alshmrany, Rafael Menezes +2
Bounded model checking (BMC) is vital for finding program property violations. For unsafe programs, BMC can quickly find an execution path from an initial state to the violated sta…
Finding Security Vulnerabilities in Network Protocol Implementations
Kaled Alshmrany, Lucas Cordeiro
Implementations of network protocols are often prone to vulnerabilities caused by developers' mistakes when accessing memory regions and dealing with arithmetic operations. Finding…