Over the last decade, video surveillance systems have become a part of the Internet of
Things (IoT). These IP-based surveillance systems now protect industrial facilities, railways …

The problem of data skewness, class imbalance, data scarcity and noise limits the
application of machine learning and deep learning models in applications like anomaly …

In this paper, we propose a new method for detecting adversarial attacks on deep neural
networks. Our algorithm is based on the intuition that attacking input images results in …

Abstract Cyber-Physical System (CPS) is used in industries and automated plants as they
have modern administration abilities and are capable of performing real-time processing in …

In minority class and noisy data situations, supervised learning performs more favorably for
the majority class but cannot generalize testing data. Performance in the aforementioned …

Edge computing based on intelligent techniques provides powerful processing abilities in
cyber‐physical systems (CPS), thereby enabling real‐time insights, and analyses for …

Abstract Cyber-Physical Systems (CPS) are recognized by a broad range of complicated
multi-tasking fixings with good interaction which results in combining cyber areas within the …

In this paper, detection of deception attack on deep neural network (DNN) based image
classification in autonomous and cyber-physical systems is considered. Several studies …

基于视频监控系统网络化和智能化发展带来的风险, 研究其隐蔽式网络攻击问题,
目的在于调研大量隐蔽式网络攻击案例, 总结针对视频监控系统的隐蔽式攻击特异性 …

The vulnerability of Deep Neural Network (DNN) models to maliciously crafted adversarial
perturbations is a critical topic considering their ongoing large-scale deployment. In this …