Titlebook: Machine Learning for Cyber Security; Third International Xiaofeng Chen,Hongyang Yan,Xiangliang Zhang Conference proceedings 2020 Springer

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Dynamic Adjusting ABC-SVM Anomaly Detection Based on Weighted Function Code Correlation,odest accomplishments in industrial cyber security. However, a significant issue is how to effectively extract industrial control features which can accurately and comprehensively describe industrial control operations. Aiming at the function code field in industrial Modbus/TCP communication protoco

Deadpan

mortuary

极小

A Malware Classification Method Based on the Capsule Network,and variants. Dynamic analysis is not efficient when dealing with large amounts of malware. Aiming at the shortcomings of the existing methods, this paper proposes a method for analyzing malware based on the capsule network. It uses a supervised learning method to train the capsule network with a la

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A Novel Intrusion Detection System for Malware Based on Time-Series Meta-learning,tools leads to reduce the efficiency of CPU or GPU. Meanwhile, they give up active defense and increase the security risk. Unfortunately, the existing intrusion detection systems seldom adjust the defense policy according to the host’s performance and the time when the attack might occur. Thus, diff

Neutral-Spine

DAD: Deep Anomaly Detection for Intelligent Monitoring of Expressway Network,k (IMN) of expressway based on edge computing and deep learning is studied. The video data collected by the camera equipment in the IMN structure of the expressway is transmitted to the edge processing server for screening and then sent to the convolution neural network. Then video data was preproce

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A Two-Phase Cycle Algorithm Based on Multi-objective Genetic Algorithm and Modified BP Neural Network (MBPNN), namely TPC-MOGA-MBPNN, is proposed for effective intrusion detection based on benchmark datasets. In the first phase, the MOGA is employed to build multi-objective optimization model that tries to find Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied fo

障碍物

An Improved Localization Algorithm Based on Invasive Weed Optimization for WSNs,, key technologies and application models have been widely studied in the industry and academia. As one of its key supporting technologies, localization technology has attracted much attention. In this paper, an improved localization algorithm based on invasive weed optimization is presented and use

围裙

A Scientometric Analysis of Malware Detection Research Based on CiteSpace, have been devoting significant efforts to solve the numerous challenges in malware detection and a large amount of literature available which worthies deeply analyzing and sorting out to offer guidance for the developmental research on malicious code detection. In this paper, the visualized tool of

DENT

Malware Detection Based on Static and Dynamic Features Analysis,ess of detecting malicious samples. In this paper, the potential malicious features are summarized with their effectiveness in detection. Moreover, the machine learning approaches based on static and dynamic features analysis are studied with both merits and limitations. Finally, possible solutions