TARU PUBLICATIONS
Journal of Information and Optimization Sciences cover

Journal of Information and Optimization Sciences

(Since 1980)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667
Powered by:DOICrossrefiThenticate

The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to: • Information Sciences • Optimization Sciences • Control Theory • Operational Research • Decision Sciences • Information Theory • Information Technology • Computer Networks and Communications • Mathematical Programming • Modelling and Simulation • Database Management • Applications to Engineering Sciences • Applications to Technology

Issues up to 2022 co-published with and available at:Taylor & Francis
submissions@tarupublications.com
Taru Online First Current IssueSpecial IssuesBrowse all Issues
Journal of Information and Optimization Sciences
Open Access Research Article

Prevention of ransomware attacks using advanced encryption and behavioral analysis

* , , , , , , ,

* Corresponding author · click or hover a name for details

pp. 1897–1906Vol. 47Issue 5-BMay 2026DOI: 10.47974/JIOS-2282XML
Received:
01 Apr 2025
Published Online:
01 May 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2282
Pages:
1897–1906

Abstract

In an evolving digital era, and ransomware forms are significantly increasing day by day. These attacks use encryption to lock down victims’ data and ask for cash (a ransom) in turn for a decrypting key, leaving many people/organizations seriously out of pocket. Here, we will take a case study where these encryption tricks are combined with behavioral analysis and how it can be used to avoid ransomware attacks. It is based on the use of cryptographic methods to secure data and analysis of behavior monitoring in order to identify system operation practices that could cause ransomware. In it, we cover the theoretical background of this approach and how he formed these conclusions as well as the results. Look for new reports on wider implications using encryption alongside behavioral detection to protect against ransomware soon! The report also showcases the changing landscape of Ransomware with real-world case studies coupled with a literature review as well as documents how different methodologies proposed before adding value in mitigating these threats. 

Keywords

RansomwareFile encryptionEncryption systemsDeviant behavior recognitionSecurity against cyber attacksInformation security principlesMalicious softwareSecret key cryptographyPublic key cryptographyParameters of cyber lawsOffensive cyberspace

Subject Classifications

Primary 94A60Secondary 68T05

References

[1] J. Smith and R. Doe, “Advanced Encryption Strategies for Ransomware Defense,” Cybersecurity Review Journal, vol. 14, no. 2, pp. 89–97 (2022).[2] M. Johnson, “Secure Communication and Anomaly Detection in Cyber Defense,” Journal of Information Security Technologies, vol. 19, no. 1, pp. 45–53 (2021).[3] Y. Zhang, L. Wu, and A. Gupta, “Limitations of Cryptography in Malware Mitigation: A Case Study on Ransomware,” Proceedings of the International Conference on Cyber Threat Intelligence, pp. 102–110 (2020).[4] Kaspersky Lab, “Heuristic Detection and Behavioral Analysis in Ransomware Defense,” Kaspersky Research Report, pp. 33–41 (2021).[5] X. Xu, J. Lin, and C. Zhao, “Behavioral Threat Intelligence and Ransomware Detection,” International Journal of Cybersecurity Research, vol. 17, no. 3, pp. 124–131 (2019).[6] A. Kharraz, S. Arshad, C. Mulliner, W. Robertson, and E. Kirda, “Cutting the Gordian Knot: A Look Under the Hood of Ransomware Attacks,” in Proc. of the 12th Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA) (2015).[7] M. Conti, A. Gangwal, and S. Ruj, “On the Economic Significance of Ransomware Campaigns: A Bitcoin Transactions Perspective,” Computers & Security, vol. 92 (2020).[8] Symantec Corporation, Internet Security Threat Report, vol. 21 (2016).[9] A. Godbole, R. Dhabliya, and V. Tiwari, “Ethical hacking and penetration testing: Strengthening cybersecurity posture through offensive security measures,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 27, no. 4, pp. 1295–1305 (2024), doi: 10.47974/JDMSC-1983[10] M. Bishop, Computer Security: Art and Science, 2nd ed., Addison-Wesley (2019).[11] C. Tankard, “Advanced persistent threats and how to monitor and deter them,” Network Security, vol. 2011, no. 8, pp. 16-19 (2011).[12] S. Shone, P. J. D. Williams, D. N. S. Parekh, and Q. Liu, “A hybrid genetic algorithm for feature selection to improve data mining classification,” Information Sciences, vol. 177, no. 18, pp. 3782–3792 (2007).[13] NIST, “Guide for Cybersecurity Event Recovery,” NIST Special Publication 800-184 (Dec. 2016).[14] P. Bagane, S. Kothari, A. Goyal, K. Joshi, M. Garg, N. Namboodiri, and P. Karthik Krishna, “CyberCraft: Encryption and decryption tool for images using AES, DES, and chaotic logistic map,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 29, no. 2-B, pp. 797–806 (2026), DOI: 10.47974/JDMSC-2526[15] A. Pratap Singh and M. Singh, “Real time malware detection in encrypted network traffic using machine learning with time based features,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 26, no. 3, pp. 841-850 (2023), DOI: 10.47974/JDMSC-1760[16] V. Ramachandran, H. M. A. Ghanimi, B. Marapelli, N. Kaur, M. Rajya Laxmi, R. Kumar Bommisetti, S. Sengan and Pankaj Dadheech, “An enterprise blockchain model: A reliable cryptography-based cyber-physical systems for securing user data, Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 5-B, pp. 2103–2114, (2025), DOI: 10.47974/JDMSC-2368
Views: 65Downloads: 11Citations: 0