Recently, Internet of Things (IoT) devices produces massive quantity of data from distinct
sources that get transmitted over public networks. Cybersecurity becomes a challenging …

本文从三个方面介绍了机器学习. 首先简单介绍5 种典型的机器学习算法,
以及典型算法之间结合的集成算法. 其次, 在典型算法基础上介绍了结合其他学科的量子机器 …

基于“分而治之” 方法提出了一种在完全未知明文, 密文及泄露中间值情况下的电磁泄漏攻击方法.
设计深度残差神经网络模型, 对基于现场可编程逻辑门阵列(field programmable gate array …

In big data era, machine learning is one of fundamental techniques in intrusion detection
systems (IDSs). Poisoning attack, which is one of the most recognized security threats …

We introduce the problem of learning-based attacks in a simple abstraction of cyber-physical
systems—the case of a discrete-time, linear, time-invariant plant that may be subject to an …

Machine Learning (ML) and Deep Learning (DL) technologies are gaining prominence,
particularly in computer network security. Cutting-edge technologies, such as fraud detection …

Deep neural networks are widely used in many walks of life. Techniques such as transfer
learning enable neural networks pre-trained on certain tasks to be retrained for a new duty …

While wide-area communication networks facilitate the exchange of measurements and
control signals for wide-area damping controllers, they bring in new threats of cyberattacks …

入侵检测作为一种主动的信息安全保障措施, 有效地弥补了传统安全防护技术的缺陷.
本文利用鸟群特性和神经网络对任意非线性函数的逼近能力, 提出了一种基于鸟群神经网络的 …

This paper proposes a network security situation assessment model of the industrial control
system, and the model divides the industrial control network security situation assessment …