Neural networks have been proved efficient in improving many machine learning tasks such
as convolutional neural networks and recurrent neural networks for computer vision and …

With the growing processing power of computing systems and the increasing availability of
massive datasets, machine learning algorithms have led to major breakthroughs in many …

Abstract Internet of Things (IoT) has come a long way since its inception. However, the
standardization process in IoT systems for a secure IoT solution is still in its early days …

The ability to accurately compute the similarity between two pieces of binary code plays an
important role in a wide range of different problems. Several research communities such as …

Internet of things (IoT) devices make up 30% of all network-connected endpoints,
introducing vulnerabilities and novel attacks that make many companies as primary targets …

Binary code similarity detection (BCSD) has important applications in various fields such as
vulnerabilities detection, software component analysis, and reverse engineering. Recent …

Binary code similarity detection (BCSD) serves as a basis for a wide spectrum of
applications, including software plagiarism, malware classification, and known vulnerability …

Greybox fuzzing has become one of the most effective vulnerability discovery techniques.
However, greybox fuzzing techniques cannot be directly applied to applications in IoT …

Detecting semantically similar binary functions–a crucial capability with broad security
usages including vulnerability detection, malware analysis, and forensics–requires …

The complicated multi-step attacks, such as Advanced Persistent Threats (APTs), have
brought considerable threats to cybersecurity because they are naturally varied and …