Assessing the Impact of Ransomware on Information Security Management: Prevention and Mitigation Strategies
DOI:
https://doi.org/10.5281/zenodo.13194418ARK:
https://n2t.net/ark:/40704/JETBM.v1n4a01Keywords:
Ransomware, Network Security, Cybersecurity, Ransomware-as-a-Service (RaaS), Phishing, Multi-Factor Authentication (MFA), Network Segmentation, Patch Management, Data Backup, incident ResponseAbstract
Ransomware attacks have emerged as one of the most significant threats to network security in recent years. These attacks not only target large organizations but also small businesses and individuals, indicating the pervasive nature of this threat. This paper examines the impact of ransomware on network security, providing a comprehensive analysis of its evolution, the tactics employed by attackers, and the implications for organizations across various sectors.[1] The study delves into various prevention and mitigation strategies, evaluating their effectiveness and offering recommendations for enhancing network defenses. Furthermore, it addresses the growing trend of ransomware-as-a-service (RaaS), which has lowered the entry barrier for cybercriminals, making ransomware attacks more frequent and widespread. Through a review of current literature, case studies, and expert interviews, this paper aims to provide a thorough understanding of the challenges posed by ransomware and the best practices for protecting against such threats. The findings emphasize the need for a multi-layered defense approach, continuous monitoring, and collaboration with law enforcement to mitigate the impact of ransomware attacks effectively.
References
Liu, T., Cai, Q., Xu, C., Zhou, Z., Ni, F., Qiao, Y., & Yang, T. (2024). Rumor Detection with a novel graph neural network approach. arXiv Preprint arXiv:2403. 16206.
Liu, T., Cai, Q., Xu, C., Zhou, Z., Xiong, J., Qiao, Y., & Yang, T. (2024). Image Captioning in news report scenario. arXiv Preprint arXiv:2403. 16209.
Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024a). Accelerating Semi-Asynchronous Federated Learning. arXiv Preprint arXiv:2402. 10991.
Zhou, J., Liang, Z., Fang, Y., & Zhou, Z. (2024). Exploring Public Response to ChatGPT with Sentiment Analysis and Knowledge Mapping. IEEE Access.
Zhou, Z., Xu, C., Qiao, Y., Xiong, J., & Yu, J. (2024). Enhancing Equipment Health Prediction with Enhanced SMOTE-KNN. Journal of Industrial Engineering and Applied Science, 2(2), 13–20.
Zhou, Z., Xu, C., Qiao, Y., Ni, F., & Xiong, J. (2024). An Analysis of the Application of Machine Learning in Network Security. Journal of Industrial Engineering and Applied Science, 2(2), 5–12.
Zhou, Z. (2024). ADVANCES IN ARTIFICIAL INTELLIGENCE-DRIVEN COMPUTER VISION: COMPARISON AND ANALYSIS OF SEVERAL VISUALIZATION TOOLS.
Xu, C., Qiao, Y., Zhou, Z., Ni, F., & Xiong, J. (2024b). Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach. Computer Life, 12(1), 1–4.
Wang, L., Xiao, W., & Ye, S. (2019). Dynamic Multi-label Learning with Multiple New Labels. Image and Graphics: 10th International Conference, ICIG 2019, Beijing, China, August 23--25, 2019, Proceedings, Part III 10, 421–431. Springer.
Wang, L., Fang, W., & Du, Y. (2024). Load Balancing Strategies in Heterogeneous Environments. Journal of Computer Technology and Applied Mathematics, 1(2), 10–18.
Wang, L. (2024). Low-Latency, High-Throughput Load Balancing Algorithms. Journal of Computer Technology and Applied Mathematics, 1(2), 1–9.
Wang, L. (2024). Network Load Balancing Strategies and Their Implications for Business Continuity. Academic Journal of Sociology and Management, 2(4), 8–13.
Li, W. (2024). The Impact of Apple’s Digital Design on Its Success: An Analysis of Interaction and Interface Design. Academic Journal of Sociology and Management, 2(4), 14–19.
Wu, R., Zhang, T., & Xu, F. (2024). Cross-Market Arbitrage Strategies Based on Deep Learning. Academic Journal of Sociology and Management, 2(4), 20–26.
Wu, R. (2024). Leveraging Deep Learning Techniques in High-Frequency Trading: Computational Opportunities and Mathematical Challenges. Academic Journal of Sociology and Management, 2(4), 27–34.
Wang, L. (2024). The Impact of Network Load Balancing on Organizational Efficiency and Managerial Decision-Making in Digital Enterprises. Academic Journal of Sociology and Management, 2(4), 41–48.
Chen, Q., & Wang, L. (2024). Social Response and Management of Cybersecurity Incidents. Academic Journal of Sociology and Management, 2(4), 49–56.
Song, C. (2024). Optimizing Management Strategies for Enhanced Performance and Energy Efficiency in Modern Computing Systems. Academic Journal of Sociology and Management, 2(4), 57–64.
Zhou, Z., & Wu, R. (2024). Stock Price Prediction Model Based on Convolutional Neural Networks. Journal of Industrial Engineering and Applied Science, 2(4), 1–7.
Zhang, C., Zhou, Z., & Wu, R. (2024). Optimization of Automated Trading Systems with Deep Learning Strategies. Journal of Industrial Engineering and Applied Science, 2(4), 8–14.
Zhang, C., Zhou, Z., & Wu, R. (2024). Analyzing and Predicting Financial Time Series Data Using Recurrent Neural Networks. Journal of Industrial Engineering and Applied Science, 2(4), 15–21.
Zhang, C., Zhou, Z., & Wu, R. (2024). Analyzing and Predicting Financial Time Series Data Using Recurrent Neural Networks. Journal of Industrial Engineering and Applied Science, 2(4), 15–21.
Chen, Q., Li, D., & Wang, L. (2024). Blockchain Technology for Enhancing Network Security. Journal of Industrial Engineering and Applied Science, 2(4), 22–28.
Chen, Q., Li, D., & Wang, L. (2024). The Role of Artificial Intelligence in Predicting and Preventing Cyber Attacks. Journal of Industrial Engineering and Applied Science, 2(4), 29–35.
Chen, Q., Li, D., & Wang, L. (2024). Network Security in the Internet of Things (IoT) Era. Journal of Industrial Engineering and Applied Science, 2(4), 36–41.
Li, D., Chen, Q., & Wang, L. (2024). Cloud Security: Challenges and Solutions. Journal of Industrial Engineering and Applied Science, 2(4), 42–47.
Li, D., Chen, Q., & Wang, L. (2024). Phishing Attacks: Detection and Prevention Techniques. Journal of Industrial Engineering and Applied Science, 2(4), 48–53.
Song, C., Zhao, G., & Wu, B. (2024). Applications of Low-Power Design in Semiconductor Chips. Journal of Industrial Engineering and Applied Science, 2(4), 54–59.
Zhao, G., Song, C., & Wu, B. (2024). 3D Integrated Circuit (3D IC) Technology and Its Applications. Journal of Industrial Engineering and Applied Science, 2(4), 60–65.
Wu, B., Song, C., & Zhao, G. (2024). Applications of Heterogeneous Integration Technology in Chip Design. Journal of Industrial Engineering and Applied Science, 2(4), 66–72.
Song, C., Wu, B., & Zhao, G. (2024). Optimization of Semiconductor Chip Design Using Artificial Intelligence. Journal of Industrial Engineering and Applied Science, 2(4), 73–80.
Song, C., Wu, B., & Zhao, G. (2024). Applications of Novel Semiconductor Materials in Chip Design. Journal of Industrial Engineering and Applied Science, 2(4), 81–89.
Berr, J. (2021, June 2). The Colonial Pipeline Ransomware Attack: What You Need to Know. CBS News. Retrieved from https://www.cbsnews.com/news/colonial-pipeline-ransomware-attack-what-to-know/
Europol. (2017). WannaCry Ransomware: How to Protect Your Network. Retrieved from https://www.europol.europa.eu/activities-services/public-awareness-and-prevention-guides
Kshetri, N. (2018). The Economics of Ransomware. IEEE Security & Privacy, 16(1), 24-30. https://doi.org/10.1109/MSP.2018.1331213
Mandiant. (2021). Ransomware Trends and Mitigation Strategies. Mandiant Threat Intelligence Report. Retrieved from https://www.mandiant.com/resources/ransomware-trends-and-mitigation-strategies
Symantec. (2018). Internet Security Threat Report. Retrieved from https://www.symantec.com/content/dam/symantec/docs/reports/istr-23-2018-en.pdf
Yadav, T., & Rao, A. M. (2015). Technical Aspects of Ransomware: A Survey. Information Security Journal: A Global Perspective, 24(2-3), 61-72. https://doi.org/10.1080/19393555.2015.1035005
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