As computer programs run on top of blockchain, smart contracts have proliferated a myriad
of decentralized applications while bringing security vulnerabilities, which may cause huge …

Fuzz testing has emerged as a dominant approach for identifying vulnerabilities, significantly
improving software development and testing. Yet, traditional fuzz testing often grapples with …

A growing awareness is brought that the safety and security of industrial control systems
cannot be dealt with in isolation, and the safety and security of industrial control protocols …

We present a novel tool BertRLFuzzer, a BERT and Reinforcement Learning (RL) based
fuzzer aimed at finding security vulnerabilities for Web applications. BertRLFuzzer works as …

Fuzzing is a widely-used testing technique to assure software robustness. However,
automatic generation of high-quality test suites is challenging, especially for software that …

The fuzzing test is able to discover various vulnerabilities and has more chances to hit the
zero-day targets. And ICS (Industrial control system) is currently facing huge security threats …

Reinforcement learning (RL) is a machine learning paradigm, like supervised or
unsupervised learning, which learns the best actions an agent needs to perform to maximize …

We will study the application of Reinforcement Learning techniques in automated GUI
testing. Using the scriptless GUI testing tool TESTAR as a vehicle, we will focus our research …

Abstract To effectively use Machine Learning (ML) in cybersecurity, automation is required.
However, there cannot be true Intelligent Automation in cybersecurity if anomalies are …