Classification of Grayscale Malware Images Using the K-Nearest Neighbor Algorithm
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-37629-1_75
Reference12 articles.
1. Cakir, B., Dogdu, E.: Malware classification using deep learning methods. In: Proceedings of the ACMSE 2018 Conference, pp. 10:1–10:5. ACM, New York (2018). https://doi.org/10.1145/3190645.3190692
2. Islam, R., et al.: Classification of malware based on integrated static and dynamic features. J. Netw. Comput. Appl. 36(2), 646–656 (2013). https://doi.org/10.1016/j.jnca.2012.10.004
3. Jerlin, M.A., Marimuthu, K.: A new malware detection system using machine learning techniques for API call sequences. J. Appl. Secur. Res. 13(1), 45–62 (2018). https://doi.org/10.1080/19361610.2018.1387734
4. Luo, J., Lo, D.C.: Malware image classification using machine learning with local binary pattern. In: 2017 IEEE International Conference on Big Data (Big Data), pp. 4664–4667 (2017). https://doi.org/10.1109/BigData.2017.8258512
5. Makandar, A., Patrot, A.: Malware analysis and classification using artificial neural network. In: 2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15), pp. 1–6 (2015). https://doi.org/10.1109/ITACT.2015.7492653
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. PAFE: A lightweight visualization-based fast malware classification method;Heliyon;2024-08
2. Enhancing Malware Classification via Self-Similarity Techniques;IEEE Transactions on Information Forensics and Security;2024
3. A novel deep learning-based approach for malware detection;Engineering Applications of Artificial Intelligence;2023-06
4. A comparative study of deep transfer learning models for malware classification using image datasets;International Journal of Information and Computer Security;2023
5. An Assessment of the Effectiveness of Pretrained Neural Networks for Malware Detection;IEEE Latin America Transactions;2023-01
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3