Malware recognition approach based on self‐similarity and an improved clustering algorithm-Reference-Cited by-同舟云学术

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Malware recognition approach based on self‐similarity and an improved clustering algorithm

Published:2022-07-10 Issue:5 Volume:16 Page:527-541
ISSN:1751-8806
Container-title:IET Software
language:en
Short-container-title:IET Software

Author:

Chen Jinfu¹²,Zhang Chi¹²,Cai Saihua¹²^ORCID,Zhang Zufa¹,Liu Lu³,Huang Longxia¹

Affiliation:

1. School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

2. Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu University Zhenjiang China

3. School of Computing and Mathematical Sciences University of Leicester Leicester UK

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Natural Science Foundation of Jiangsu Province

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Graphics and Computer-Aided Design

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/sfw2.12067

Reference51 articles.

1. Detecting the network attack vectors on SCADA systems

2. A Novel Approach for Network Attack Classification Based on Sequential Questions

3. 2019 CWE top 25 most dangerous software errors[Online].http://cwe.mitre.org/top25/. Accessed 10 July 2020

4. Data Clustering with Grasshopper Optimization Algorithm

5. An Empirical Study on Detecting and Fixing Buffer Overflow Bugs

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