Ransomware Attacks and Their Evolving Strategies: A Systematic Review of Recent Incidents
DOI:
https://doi.org/10.47941/jts.2399Keywords:
Ransomware, Cybersecurity, Cyber threat, security.Abstract
Ransomware attacks have emerged as a significant cybersecurity concern, posing intricate risks to individuals, institutions, and governments. Because cybercriminals are always improving their methods, it is important to understand how these changing approaches affect things. This study explores the complexity of ransomware attacks by looking into previous cases to identify trends, tactics, and how economic and technological advancements affect these risks. Through an extensive examination of cutting-edge ransomware tactics, the paper pinpoints a major research void with regard to current, fine-grained incident analyses and sector-specific impacts. A systematic literature review has been done using four ransomware and six cybersecurity keywords. The purpose of this study is to analyze the evolving complexity of ransomware attacks by examining past cases to identify trends, tactics, and the impact of economic and technological advancements on these risks. It also aims to address gaps in detailed incident analyses and sector-specific impacts, providing actionable insights and recommendations for strengthening cybersecurity defenses and legislative measures. The study adds to the body of knowledge by analyzing recent examples, identifying the dynamic nature of threat actor actions, and assessing the efficacy of countermeasures in a variety of industries through qualitative and quantitative data. The conclusions reached provide insightful analysis and practical suggestions for cybersecurity professionals to strengthen defenses, reduce risks, and predict future advancements in ransomware operations. In the end, this report hopes to set the groundwork for stronger cybersecurity standards and well-informed legislative solutions to counteract the increasingly complex ransomware techniques.
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References
B. J. Chinmaya, S. A. Kudtarkar, and Mohana, “Targeted Ransomware Attacks and Detection to Strengthen Cybersecurity Strategies,” in 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS), Pudukkottai, India: IEEE, Dec. 2023, pp. 1039–1044. doi: 10.1109/ICACRS58579.2023.10404203.
M. Medhat, M. Essa, H. Faisal, and S. G. Sayed, “YARAMON: A Memory-based Detection Framework for Ransomware Families,” in 2020 15th International Conference for Internet Technology and Secured Transactions (ICITST), London, United Kingdom: IEEE, Dec. 2020, pp. 1–6. doi: 10.23919/ICITST51030.2020.9351319.
N. Aldaraani and Z. Begum, “Understanding the impact of Ransomware: A Survey on its Evolution, Mitigation and Prevention Techniques,” in 2018 21st Saudi Computer Society National Computer Conference (NCC), Riyadh: IEEE, Apr. 2018, pp. 1–5. doi: 10.1109/NCG.2018.8593029.
Mulungushi University/Department of Computer Science & Information Technology, Kabwe, 10101, Zambia, A. Zimba, and M. Chishimba, “Understanding the Evolution of Ransomware: Paradigm Shifts in Attack Structures,” IJCNIS, vol. 11, no. 1, pp. 26–39, Jan. 2019, doi: 10.5815/ijcnis.2019.01.03.
J. Chen, C. Wang, Z. Zhao, K. Chen, R. Du, and G.-J. Ahn, “Uncovering the Face of Android Ransomware: Characterization and Real-Time Detection,” IEEE Trans.Inform.Forensic Secur., vol. 13, no. 5, pp. 1286–1300, May 2018, doi: 10.1109/TIFS.2017.2787905.
K. Cabaj and W. Mazurczyk, “Using Software-Defined Networking for Ransomware Mitigation: The Case of CryptoWall,” IEEE Network, vol. 30, no. 6, pp. 14–20, Nov. 2016, doi: 10.1109/MNET.2016.1600110NM.
F. Aldauiji, O. Batarfi, and M. Bayousef, “Utilizing Cyber Threat Hunting Techniques to Find Ransomware Attacks: A Survey of the State of the Art,” IEEE Access, vol. 10, pp. 61695–61706, 2022, doi: 10.1109/ACCESS.2022.3181278.
M. Husak, “Towards a Data-Driven Recommender System for Handling Ransomware and Similar Incidents,” in 2021 IEEE International Conference on Intelligence and Security Informatics (ISI), San Antonio, TX, USA: IEEE, Nov. 2021, pp. 1–6. doi: 10.1109/ISI53945.2021.9624774.
A. Bertia, S. B. Xavier, G. J. W. Kathrine, and G. M. Palmer, “A Study about Detecting Ransomware by Using Different Algorithms,” in 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India: IEEE, May 2022, pp. 1293–1300. doi: 10.1109/ICAAIC53929.2022.9792587.
B. E. M. Yamany and M. A. Azer, “SALAM Ransomware Behavior Analysis Challenges and Decryption,” in 2021 Tenth International Conference on Intelligent Computing and Information Systems (ICICIS), Cairo, Egypt: IEEE, Dec. 2021, pp. 273–277. doi: 10.1109/ICICIS52592.2021.9694154.
School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor 81310, MALAYSIA et al., “Zero-Day Aware Decision Fusion-Based Model for Crypto-Ransomware Early Detection,” IJIE, vol. 10, no. 6, Nov. 2018, doi: 10.30880/ijie.2018.10.06.011.
C. G. Akcora, Y. Li, Y. R. Gel, and M. Kantarcioglu, “BitcoinHeist: Topological Data Analysis for Ransomware Detection on the Bitcoin Blockchain,” 2019, doi: 10.48550/ARXIV.1906.07852.
D. Javaheri, M. Hosseinzadeh, and A. M. Rahmani, “Detection and Elimination of Spyware and Ransomware by Intercepting Kernel-Level System Routines,” IEEE Access, vol. 6, pp. 78321–78332, 2018, doi: 10.1109/ACCESS.2018.2884964.
E. Kirda, “UNVEIL: A large-scale, automated approach to detecting ransomware (keynote),” in 2017 IEEE 24th International Conference on Software Analysis, Evolution and Reengineering (SANER), Klagenfurt, Austria: IEEE, Feb. 2017, pp. 1–1. doi: 10.1109/SANER.2017.7884603.
E. Rouka, C. Birkinshaw, and V. G. Vassilakis, “SDN-based Malware Detection and Mitigation: The Case of ExPetr Ransomware,” in 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT), Doha, Qatar: IEEE, Feb. 2020, pp. 150–155. doi: 10.1109/ICIoT48696.2020.9089514.
S. Alsoghyer and I. Almomani, “On the Effectiveness of Application Permissions for Android Ransomware Detection,” in 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), Riyadh, Saudi Arabia: IEEE, Mar. 2020, pp. 94–99. doi: 10.1109/CDMA47397.2020.00022.
B. Reidys, P. Liu, and J. Huang, “RSSD: defend against ransomware with hardware-isolated network-storage codesign and post-attack analysis,” in Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Lausanne Switzerland: ACM, Feb. 2022, pp. 726–739. doi: 10.1145/3503222.3507773.
T. Dargahi, A. Dehghantanha, P. N. Bahrami, M. Conti, G. Bianchi, and L. Benedetto, “A Cyber-Kill-Chain based taxonomy of crypto-ransomware features,” J Comput Virol Hack Tech, vol. 15, no. 4, pp. 277–305, Dec. 2019, doi: 10.1007/s11416-019-00338-7.
A. Adamov and A. Carlsson, “Reinforcement Learning for Anti-Ransomware Testing,” in 2020 IEEE East-West Design & Test Symposium (EWDTS), Varna, Bulgaria: IEEE, Sep. 2020, pp. 1–5. doi: 10.1109/EWDTS50664.2020.9225141.
E. Kolodenker, W. Koch, G. Stringhini, and M. Egele, “PayBreak: Defense Against Cryptographic Ransomware,” in Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, Abu Dhabi United Arab Emirates: ACM, Apr. 2017, pp. 599–611. doi: 10.1145/3052973.3053035.
V. Marella, M. Roshan, J. Merikivi, and V. Tuunainen, “Rebuilding Trust in Cryptocurrency Exchanges after Cyber-attacks,” presented at the Hawaii International Conference on System Sciences, 2021. doi: 10.24251/HICSS.2021.684.
C. Moore, “Detecting Ransomware with Honeypot Techniques,” in 2016 Cybersecurity and Cyberforensics Conference (CCC), Amman, Jordan: IEEE, Aug. 2016, pp. 77–81. doi: 10.1109/CCC.2016.14.
M. Alam, S. Bhattacharya, S. Dutta, S. Sinha, D. Mukhopadhyay, and A. Chattopadhyay, “RATAFIA: Ransomware Analysis using Time And Frequency Informed Autoencoders,” in 2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), McLean, VA, USA: IEEE, May 2019, pp. 218–227. doi: 10.1109/HST.2019.8740837.
U. Javed Butt, M. Abbod, A. Lors, H. Jahankhani, A. Jamal, and A. Kumar, “Ransomware Threat and its Impact on SCADA,” in 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3), London, United Kingdom: IEEE, Jan. 2019, pp. 205–212. doi: 10.1109/ICGS3.2019.8688327.
S. Yulianto and B. Soewito, “Ransomware Resilience: Investigating Organizational Security Culture and Its Impact on Cybersecurity Practices against Ransomware Threats,” in 2023 International Conference on Informatics Engineering, Science & Technology (INCITEST), Bandung, Indonesia: IEEE, Oct. 2023, pp. 1–7. doi: 10.1109/INCITEST59455.2023.10396943.
S. R. B. Alvee, B. Ahn, T. Kim, Y. Su, Y.-W. Youn, and M.-H. Ryu, “Ransomware Attack Modeling and Artificial Intelligence-Based Ransomware Detection for Digital Substations,” in 2021 6th IEEE Workshop on the Electronic Grid (eGRID), New Orleans, LA, USA: IEEE, Nov. 2021, pp. 01–05. doi: 10.1109/eGRID52793.2021.9662158.
I. Tunji, A. Chomchoey, N. Phromchan, and K. Chimmanee, “Ransomware Attack Analysis on Banking Systems,” in 2023 7th International Conference on Information Technology (InCIT), Chiang Rai, Thailand: IEEE, Nov. 2023, pp. 121–125. doi: 10.1109/InCIT60207.2023.10412895.
J. Johnson, “Leading cause of ransomware infection 2019,” Statista. com, Jan, vol. 25, 2021.
D. Zhuravchak, T. Ustyianovych, V. Dudykevych, B. Venny, and K. Ruda, “Ransomware Prevention System Design based on File Symbolic Linking Honeypots,” in 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Cracow, Poland: IEEE, Sep. 2021, pp. 284–287. doi: 10.1109/IDAACS53288.2021.9660913.
M. N. Olaimat, M. Aizaini Maarof, and B. A. S. Al-rimy, “Ransomware Anti-Analysis and Evasion Techniques: A Survey and Research Directions,” in 2021 3rd International Cyber Resilience Conference (CRC), Langkawi Island, Malaysia: IEEE, Jan. 2021, pp. 1–6. doi: 10.1109/CRC50527.2021.9392529.
M. Keshavarzi and H. R. Ghaffary, “I2CE3: A dedicated and separated attack chain for ransomware offenses as the most infamous cyber extortion,” Computer Science Review, vol. 36, p. 100233, May 2020, doi: 10.1016/j.cosrev.2020.100233.
H. Fujinoki and L. Manukonda, “Proactive Damage Prevention from Zero-Day Ransomwares,” in 2023 5th International Conference on Computer Communication and the Internet (ICCCI), Fujisawa, Japan: IEEE, Jun. 2023, pp. 133–141. doi: 10.1109/ICCCI59363.2023.10210183.
A. Khan and I. Sharma, “Machine Learning-Based Methodology for Preventing Ransomware Attacks on Healthcare Sector,” in 2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), Chennai, India: IEEE, Nov. 2023, pp. 1–5. doi: 10.1109/RMKMATE59243.2023.10368971.
C. Zhou et al., “Limits of I/O Based Ransomware Detection: An Imitation Based Attack,” in 2023 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA: IEEE, May 2023, pp. 2584–2601. doi: 10.1109/SP46215.2023.10179372.
A. Zahra and M. A. Shah, “IoT based ransomware growth rate evaluation and detection using command and control blacklisting,” in 2017 23rd International Conference on Automation and Computing (ICAC), Huddersfield, United Kingdom: IEEE, Sep. 2017, pp. 1–6. doi: 10.23919/IConAC.2017.8082013.
M. A. Aboud and K. Mariyappn, “Investigation of Modern Ransomware Key Generation Methods: A Review,” in 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India: IEEE, Jan. 2021, pp. 1–5. doi: 10.1109/ICCCI50826.2021.9402680.
S. Karunakaran, M. Manimaraboopathy, M. Maharajothi, P. Kirubasagar, T. Subburaj, and S. Varun, “Internet of Things Assisted Automated Ransomware Recognition using Harmony Search Algorithm with Deep Learning,” in 2023 International Conference on Sustainable Communication Networks and Application (ICSCNA), Theni, India: IEEE, Nov. 2023, pp. 475–480. doi: 10.1109/ICSCNA58489.2023.10370175.
J.-S. Ko, J.-S. Jo, D.-H. Kim, S.-K. Choi, and J. Kwak, “Real Time Android Ransomware Detection by Analyzed Android Applications,” in 2019 International Conference on Electronics, Information, and Communication (ICEIC), Auckland, New Zealand: IEEE, Jan. 2019, pp. 1–5. doi: 10.23919/ELINFOCOM.2019.8706349.
S. A. Wadho, A. Yichiet, G. M. Lee, L. C. Kang, R. Akbar, and R. Kumar, “Impact of Cyber Insurances on Ransomware,” in 2023 IEEE 8th International Conference on Engineering Technologies and Applied Sciences (ICETAS), Bahrain, Bahrain: IEEE, Oct. 2023, pp. 1–6. doi: 10.1109/ICETAS59148.2023.10346341.
J. Venkatesh, V. Vetriselvi, R. Parthasarathi, and G. Subrahmanya V.R.K. Rao, “Identification and isolation of crypto ransomware using honeypot,” in 2018 Fourteenth International Conference on Information Processing (ICINPRO), Bangalore, India: IEEE, Dec. 2018, pp. 1–6. doi: 10.1109/ICINPRO43533.2018.9096875.
A. Ferreira, “Why Ransomware Needs A Human Touch,” in 2018 International Carnahan Conference on Security Technology (ICCST), Montreal, QC: IEEE, Oct. 2018, pp. 1–5. doi: 10.1109/CCST.2018.8585650.
A. Turner, S. Mccombie, and A. Uhlmann, “Follow the money: Revealing risky nodes in a Ransomware-Bitcoin network,” presented at the Hawaii International Conference on System Sciences, 2021. doi: 10.24251/HICSS.2021.189.
J. Huang, J. Xu, X. Xing, P. Liu, and M. K. Qureshi, “FlashGuard: Leveraging Intrinsic Flash Properties to Defend Against Encryption Ransomware,” in Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, Dallas Texas USA: ACM, Oct. 2017, pp. 2231–2244. doi: 10.1145/3133956.3134035.
S.-C. Hsiao and D.-Y. Kao, “The static analysis of WannaCry ransomware,” in 2018 20th International Conference on Advanced Communication Technology (ICACT), Chuncheon-si Gangwon-do, Korea (South): IEEE, Feb. 2018, pp. 153–158. doi: 10.23919/ICACT.2018.8323680.
S. A. Wadho, A. Yichiet, M. L. Gan, L. C. Kang, R. Akbar, and R. Kumar, “Emerging Ransomware Attacks: Improvement and Remedies - A Systematic Literature Review,” in 2023 4th International Conference on Artificial Intelligence and Data Sciences (AiDAS), IPOH, Malaysia: IEEE, Sep. 2023, pp. 148–153. doi: 10.1109/AiDAS60501.2023.10284647.
M. M. Ahmadian and H. R. Shahriari, “2entFOX: A framework for high survivable ransomwares detection,” in 2016 13th International Iranian Society of Cryptology Conference on Information Security and Cryptology (ISCISC), Tehran: IEEE, Sep. 2016, pp. 79–84. doi: 10.1109/ISCISC.2016.7736455.
E. Btoush, X. Zhou, R. Gururaian, K. Chan, and X. Tao, “A Survey on Credit Card Fraud Detection Techniques in Banking Industry for Cyber Security,” in 2021 8th International Conference on Behavioral and Social Computing (BESC), Doha, Qatar: IEEE, Oct. 2021, pp. 1–7. doi: 10.1109/BESC53957.2021.9635559.
S.-B. Cheon, G.-Y. Choi, and D. Kim, “A Cheating Attack on a Whitelist-based Anti-Ransomware Solution and its Countermeasure,” in 2023 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA: IEEE, Jan. 2023, pp. 01–04. doi: 10.1109/ICCE56470.2023.10043480.
A. O. Almashhadani, M. Kaiiali, S. Sezer, and P. O’Kane, “A Multi-Classifier Network-Based Crypto Ransomware Detection System: A Case Study of Locky Ransomware,” IEEE Access, vol. 7, pp. 47053–47067, 2019, doi: 10.1109/ACCESS.2019.2907485.
A. Alqahtani, M. Gazzan, and F. T. Sheldon, “A proposed Crypto-Ransomware Early Detection(CRED) Model using an Integrated Deep Learning and Vector Space Model Approach,” in 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA: IEEE, Jan. 2020, pp. 0275–0279. doi: 10.1109/CCWC47524.2020.9031182.
M. Botes and G. Lenzini, “When Cryptographic Ransomware Poses Cyber Threats: Ethical Challenges and Proposed Safeguards for Cybersecurity Researchers,” in 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Genoa, Italy: IEEE, Jun. 2022, pp. 562–568. doi: 10.1109/EuroSPW55150.2022.00067.
Ekta and U. Bansal, “A Review on Ransomware Attack,” in 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC), Jalandhar, India: IEEE, May 2021, pp. 221–226. doi: 10.1109/ICSCCC51823.2021.9478148.
F. Manavi and A. Hamzeh, “A New Method for Ransomware Detection Based on PE Header Using Convolutional Neural Networks,” in 2020 17th International ISC Conference on Information Security and Cryptology (ISCISC), Tehran, Iran: IEEE, Sep. 2020, pp. 82–87. doi: 10.1109/ISCISC51277.2020.9261903.
M. Medhat, S. Gaber, and N. Abdelbaki, “A New Static-Based Framework for Ransomware Detection,” in 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Athens: IEEE, Aug. 2018, pp. 710–715. doi: 10.1109/DASC/PiCom/DataCom/CyberSciTec.2018.00124.
D. Garg, A. Thakral, T. Nalwa, and T. Choudhury, “A Past Examination and Future Expectation: Ransomware,” in 2018 International Conference on Advances in Computing and Communication Engineering (ICACCE), Paris: IEEE, Jun. 2018, pp. 243–247. doi: 10.1109/ICACCE.2018.8441743.
U. Urooj, M. A. B. Maarof, and B. A. S. Al-rimy, “A proposed Adaptive Pre-Encryption Crypto-Ransomware Early Detection Model,” in 2021 3rd International Cyber Resilience Conference (CRC), Langkawi Island, Malaysia: IEEE, Jan. 2021, pp. 1–6. doi: 10.1109/CRC50527.2021.9392548.
B. A. S. Al-Rimy et al., “A Pseudo Feedback-Based Annotated TF-IDF Technique for Dynamic Crypto-Ransomware Pre-Encryption Boundary Delineation and Features Extraction,” IEEE Access, vol. 8, pp. 140586–140598, 2020, doi: 10.1109/ACCESS.2020.3012674.
T. Nusairat, M. M. Saudi, and A. B. Ahmad, “A Recent Assessment for the Ransomware Attacks Against the Internet of Medical Things (IoMT): A Review,” in 2023 IEEE 13th International Conference on Control System, Computing and Engineering (ICCSCE), Penang, Malaysia: IEEE, Aug. 2023, pp. 238–242. doi: 10.1109/ICCSCE58721.2023.10237161.
A. A. M. A. Alwashali, N. A. A. Rahman, and N. Ismail, “A Survey of Ransomware as a Service (RaaS) and Methods to Mitigate the Attack,” in 2021 14th International Conference on Developments in eSystems Engineering (DeSE), Sharjah, United Arab Emirates: IEEE, Dec. 2021, pp. 92–96. doi: 10.1109/DeSE54285.2021.9719456.
P. Bajpai and R. Enbody, “An Empirical Study of Key Generation in Cryptographic Ransomware,” in 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), Dublin, Ireland: IEEE, Jun. 2020, pp. 1–8. doi: 10.1109/CyberSecurity49315.2020.9138878.
J. Nwokeji, F. Aqlan, A. Anugu, and A. Olagunju, “Big Data ETL Implementation Approaches: A Systematic Literature Review (P),” presented at the The 30th International Conference on Software Engineering and Knowledge Engineering, Jul. 2018, pp. 714–721. doi: 10.18293/SEKE2018-152.
A. Kaplan, K. Busch, A. Koziolek, and R. Heinrich, “Categories of Change Triggers in Business Processes,” in 2018 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Prague: IEEE, Aug. 2018, pp. 252–259. doi: 10.1109/SEAA.2018.00049.
B. S. Ahmed, K. Z. Zamli, W. Afzal, and M. Bures, “Constrained Interaction Testing: A Systematic Literature Study,” IEEE Access, vol. 5, pp. 25706–25730, 2017, doi: 10.1109/ACCESS.2017.2771562.
I. Hydara, A. B. Md. Sultan, H. Zulzalil, and N. Admodisastro, “Current state of research on cross-site scripting (XSS) – A systematic literature review,” Information and Software Technology, vol. 58, pp. 170–186, Feb. 2015, doi: 10.1016/j.infsof.2014.07.010.
A. Freire et al., “Investigating gaps on Agile Improvement Solutions and their successful adoption in industry projects - A systematic literature review,” presented at the The 30th International Conference on Software Engineering and Knowledge Engineering, Jul. 2018, pp. 40–55. doi: 10.18293/SEKE2018-185.
F. Hujainah, R. B. A. Bakar, M. A. Abdulgabber, and K. Z. Zamli, “Software Requirements Prioritisation: A Systematic Literature Review on Significance, Stakeholders, Techniques and Challenges,” IEEE Access, vol. 6, pp. 71497–71523, 2018, doi: 10.1109/ACCESS.2018.2881755.
N. Qureshi, M. Usman, and N. Ikram, “Evidence in software architecture, a systematic literature review,” in Proceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering, Porto de Galinhas Brazil: ACM, Apr. 2013, pp. 97–106. doi: 10.1145/2460999.2461014.
A. Pillai, R. Kadikar, M. S. Vasanthi, and B. Amutha, “Analysis of AES-CBC Encryption for Interpreting Crypto-Wall Ransomware,” in 2018 International Conference on Communication and Signal Processing (ICCSP), Chennai: IEEE, Apr. 2018, pp. 0599–0604. doi: 10.1109/ICCSP.2018.8524494.
R. Agrawal, J. W. Stokes, K. Selvaraj, and M. Marinescu, “Attention in Recurrent Neural Networks for Ransomware Detection,” in ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, United Kingdom: IEEE, May 2019, pp. 3222–3226. doi: 10.1109/ICASSP.2019.8682899.
M. Sukul, S. A. Lakshmanan, and R. Gowtham, “Automated Dynamic Detection of Ransomware using Augmented Bootstrapping,” in 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), Tirunelveli, India: IEEE, Apr. 2022, pp. 787–794. doi: 10.1109/ICOEI53556.2022.9777099.
V. Oujezsky, P. Novak, T. Horvath, M. Holik, and M. Jurcik, “Data Backup System with Integrated Active Protection Against Ransomware,” in 2023 46th International Conference on Telecommunications and Signal Processing (TSP), Prague, Czech Republic: IEEE, Jul. 2023, pp. 65–69. doi: 10.1109/TSP59544.2023.10197687.
R. Agarwal, A. Chaudhary, D. Gupta, and D. Das, “Ransomware Vulnerability used in darknet for web application attack,” in 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India: IEEE, Jun. 2022, pp. 1–5. doi: 10.1109/ICEFEET51821.2022.9847925.
R. Upadhyaya and A. Jain, “Cyber ethics and cyber crime: A deep dwelved study into legality, ransomware, underground web and bitcoin wallet,” in 2016 International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, India: IEEE, Apr. 2016, pp. 143–148. doi: 10.1109/CCAA.2016.7813706.
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