A review of android malware detection approaches based on machine learning

K Liu, S Xu, G Xu, M Zhang, D Sun, H Liu - IEEE access, 2020 - ieeexplore.ieee.org
Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

Analysis framework of network security situational awareness and comparison of implementation methods

Y Li, G Huang, C Wang, Y Li - EURASIP Journal on Wireless …, 2019 - Springer
Abstract Information technology has penetrated into all aspects of politics, economy, and
culture of the whole society. The information revolution has changed the way of …

An automatic classification algorithm for software vulnerability based on weighted word vector and fusion neural network

Q Wang, Y Gao, J Ren, B Zhang - Computers & Security, 2023 - Elsevier
To address the problem that the traditional vectored representation of software vulnerability
data has high-dimensional sparsity and leads to unsatisfactory automatic classification, this …

Cross-method-based analysis and classification of malicious behavior by api calls extraction

B Ndibanje, KH Kim, YJ Kang, HH Kim, TY Kim… - Applied Sciences, 2019 - mdpi.com
Data-driven public security networking and computer systems are always under threat from
malicious codes known as malware; therefore, a large amount of research and development …

Intrusion detection model using temporal convolutional network blend into attention mechanism

P Zhao, Z Fan, Z Cao, X Li - International Journal of Information …, 2022 - igi-global.com
In order to improve the ability to detect network attacks, traditional intrusion detection models
often used convolutional neural networks to encode spatial information or recurrent neural …

[PDF][PDF] 基于优化支持向量回归的工业互联网安全态势预测方法

胡向东, 吕高飞, 白银 - 电子学报, 2023 - ejournal.org.cn
作为支撑智能制造等的新型工业基础设施, 工业互联网的安全态势预测是一个关键性需求和应用
新挑战. 本文提出一种基于优化支持向量回归的工业互联网安全态势预测方法 …

Intrusion detection classification model on an improved k-dependence Bayesian network

H Yin, M Xue, Y Xiao, K Xia, G Yu - IEEE Access, 2019 - ieeexplore.ieee.org
Edge computing extends traditional cloud services to the edge of the network, and the highly
dynamic and heterogeneous environment at the edge of the network makes the network …

电力工控系统攻击渗透技术综述

张晓娟, 曹靖怡, 缪思薇, 朱亚运, 王海翔… - 电力信息与通信 …, 2021 - epjournal.csee.org.cn
电力工业控制系统作为国家关键基础设施的一部分, 其安全与否关系到国家安全和社会稳定,
对网络入侵行为和网络攻击技术进行研究, 也是确保电力工控系统网络安全的关键 …

A simhash-based integrative features extraction algorithm for malware detection

Y Li, F Liu, Z Du, D Zhang - Algorithms, 2018 - mdpi.com
In the malware detection process, obfuscated malicious codes cannot be efficiently and
accurately detected solely in the dynamic or static feature space. Aiming at this problem, an …

安卓恶意软件检测方法综述

M Fan, T Liu, J Liu, X Luo, L Yu… - Scientia Sinica …, 2020 - research.polyu.edu.hk
Android has become the most popular mobile operating system in the past ten years due to
its three main advantages, namely, the openness of source code, richness of hardware …