Botnets are computer networks controlled by malicious actors that present significant
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …

Adversarial machine learning, a technique which seeks to deceive machine learning (ML)
models, threatens the utility and reliability of ML systems. This is particularly relevant in …

Industrial Internet of Things (IIoT) technology, as a subset of the Internet of Things (IoT) in the
concept of Industry 4.0 and, in the future, 5.0, will face the challenge of streamlining the way …

In recent years, the widespread adoption of Machine Learning (ML) at the core of complex IT
systems has driven researchers to investigate the security and reliability of ML techniques. A …

近年来, 机器学习技术逐渐成为主流网络入侵检测方案. 然而机器学习模型固有的安全脆弱性,
使其难以抵抗对抗攻击, 即通过在输入中施加细微扰动而使模型得出错误结果 …

Intrusion detection system plays an important role in defending networks from security
breaches. End-to-end machine learning-based intrusion detection systems are being used …

Adversarial attacks have been extensively studied in the domain of deep image
classification, but their impacts on other domains such as Machine and Deep Learning …

Machine learning (ML) models are essential to securing communication networks. However,
these models are vulnerable to adversarial examples (AEs), in which malicious inputs are …

Adversarial attacks have threatened the credibility of machine learning models and cast
doubts over the integrity of data. The attacks have created much harm in the fields of …

The rapid advancement of artificial intelligence within the realm of cybersecurity raises
significant security concerns. The vulnerability of deep learning models in adversarial …