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Leveraging Innovative Technologies for Ransomware Prevention in Healthcare: A Case Study of AIIMS and Beyond

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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

  • 36 Accesses

Abstract

The paper explores the challenges posed by ransomware attacks in the healthcare sector within the context of the digital transformation of healthcare. It examines real-world incidents, such as those at AIIMS hospital, to highlight the disruptive nature of ransomware attacks and underscores the importance of proactive defense strategies. The study introduces three innovative approaches to ransomware prevention in healthcare: blockchain, machine learning, and software-defined networking (SDN). Each approach is analyzed in terms of its role in safeguarding healthcare data. Blockchain ensures data integrity and access control through decentralization, while machine learning enhances threat detection by identifying unusual behaviors, potentially indicative of ransomware. SDN provides dynamic network segmentation, real-time responses, and centralized security updates to counteract attacks. The paper concludes by summarizing the benefits and challenges associated with these methods and emphasizes the necessity of collaboration among healthcare professionals, technologists, and policymakers for effective implementation. These innovations are crucial for the healthcare industry to navigate the evolving cybersecurity landscape and safeguard patient data.

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References

  1. Wazid M, Das AK, Rodrigues JJPC, Shetty S, Park Y (2019) IoMT malware detection approaches: analysis and research challenges. IEEE Access 7:182459–182476. https://doi.org/10.1109/ACCESS.2019.2960412

    Article  Google Scholar 

  2. Maurya AK, Kumar N, Agrawal A, Khan RA (2018) Ransomware evolution, target and safety measures. Int J Comput Sci Eng 6(1):80–85. https://doi.org/10.26438/ijcse/v6i1.8085

    Article  Google Scholar 

  3. Delhi News—Times of India (n.d.) Delhi: Ransomware Cyber attack on AIIMS server. https://timesofindia.indiatimes.com/city/delhi/delhi-ransomware-cyber-attack-on-aiims-server/articleshow/95722736.cms. Accessed 23 Nov 2022

  4. Goldman R (2017) What we know and don’t know about the international cyberattack. New York Times. https://www.nytimes.com/2017/05/12/world/europe/international-cyberattack-ransomware.html. Accessed 12 May 2017

  5. Abrams L (2022) Keralty ransomware attack impacts Colombia’s health care system. https://www.bleepingcomputer.com/news/security/keralty-ransomware-attack-impacts-colombias-health-care-system/. Accessed 30 Nov 2022

  6. Mathews L (2020) For sale: hacked data on 142 million MGM hotel guests. Forbes

    Google Scholar 

  7. Outlook Web Bureau (2021) Chinese Hackers Targeted Serum Institute, Bharat Biotech: Cyber Firm Report. https://www.outlookindia.com/website/story/india-news-chinese-hackers-targeted-serum-institute-bharat-biotech-cyber-firm-report/375867. Accessed 2 Mar 2021

  8. AIIMS (2022) 66th AIIMS Annual Report 2021–2022. New Delhi, 2022. https://www.aiims.edu/images/pdf/annual_reports/english.pdf. Accessed 23 Sep 2023

  9. Manral MS (2023) Probing server attack, CERT-In finds holes in AIIMS cyber security. The Indian Express, New Delhi, Dec. 04, 2022. https://indianexpress.com/article/cities/delhi/probing-server-attack-cert-in-finds-holes-in-aiims-cyber-security-8304657/. Accessed 3 Oct 2023

  10. 211 Ministry of Health and Family Welfare, Government of India 2017 (2017) Digital Information Security in Healthcare, Act: Draft for Public Consultation

    Google Scholar 

  11. Lakhan A, Thinnukool O, Groenli TM, Khuwuthyakorn P (2023) RBEF: ransomware efficient public blockchain framework for digital healthcare application. Sensors 23(11):5256. https://doi.org/10.3390/s23115256

    Article  Google Scholar 

  12. Kumar S, Bharti AK, Amin R (2021) Decentralized secure storage of medical records using Blockchain and IPFS: a comparative analysis with future directions. Secur Privacy. https://doi.org/10.1002/spy2.162

    Article  Google Scholar 

  13. Corbet S, Goodell JW (2022) The reputational contagion effects of ransomware attacks. Financ Res Lett 47:102715. https://doi.org/10.1016/j.frl.2022.102715

    Article  Google Scholar 

  14. Almashhadani AO, Kaiiali M, Sezer S, O’Kane P (2019) A multi-classifier network-based crypto ransomware detection system: a case study of locky ransomware. IEEE Access 7:47053–47067. https://doi.org/10.1109/ACCESS.2019.2907485

    Article  Google Scholar 

  15. Gohar AN, Abdelmawgoud SA, Farhan MS (2022) A patient-centric healthcare framework reference architecture for better semantic interoperability based on blockchain, cloud, and IoT. IEEE Access 10:92137–92157. https://doi.org/10.1109/ACCESS.2022.3202902

    Article  Google Scholar 

  16. Ramzan S, Aqdus A, Ravi V, Koundal D, Amin R, Al Ghamdi MA (2023) Healthcare applications using blockchain technology: motivations and challenges. IEEE Trans Eng Manag 70(8):2874–2890. https://doi.org/10.1109/TEM.2022.3189734

    Article  Google Scholar 

  17. Kumar A et al (2022) A novel decentralized blockchain architecture for the preservation of privacy and data security against cyberattacks in healthcare. Sensors 22(15):5921. https://doi.org/10.3390/s22155921

    Article  Google Scholar 

  18. Tortorella GL, Fogliatto FS, Saurin TA, Tonetto LM, McFarlane D (2022) Contributions of Healthcare 4.0 digital applications to the resilience of healthcare organizations during the COVID-19 outbreak. Technovation 111:102379. https://doi.org/10.1016/j.technovation.2021.102379

    Article  Google Scholar 

  19. Ajayi O, Abouali M, Saadawi T (2021) Blockchain architecture for secured inter-healthcare electronic health records exchange. Springer, Cham, pp 161–172. https://doi.org/10.1007/978-3-030-57796-4_16

  20. Alabdulatif A, Khalil I, Saidur Rahman M (2022) Security of blockchain and AI-empowered smart healthcare: application-based analysis. Appl Sci 12(21):11039. https://doi.org/10.3390/app122111039

    Article  Google Scholar 

  21. Jabbar MA, Samreen S, Aluvalu R (2018) The future of health care: machine learning. Int J Eng Technol 7(4):23. https://doi.org/10.14419/ijet.v7i4.6.20226

  22. Reddy BV, Krishna GV, Ravi V, Dasgupta D (2021) Machine learning and feature selection based ransomware detection using hexacodes. Springer, Singapore, pp 583–597. https://doi.org/10.1007/978-981-15-5788-0_56

  23. Thamer N, Alubady R (2021) A survey of ransomware attacks for healthcare systems: risks, challenges, solutions and opportunity of research. In: 2021 1st Babylon International Conference on Information Technology and Science (BICITS). IEEE, pp 210–216. https://doi.org/10.1109/BICITS51482.2021.9509877

  24. Hirano M, Kobayashi R (2019) Machine learning based ransomware detection using storage access patterns obtained from live-forensic hypervisor. In: 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS). IEEE, 1–6. https://doi.org/10.1109/IOTSMS48152.2019.8939214

  25. Ten C-W, Hong J, Liu C-C (2011) Anomaly detection for cybersecurity of the substations. IEEE Trans Smart Grid 2(4):865–873. https://doi.org/10.1109/TSG.2011.2159406

    Article  Google Scholar 

  26. Martín AG, Fernández-Isabel A, Martín de Diego I, Beltrán M (2021) A survey for user behavior analysis based on machine learning techniques: current models and applications. Appl Intell 51(8):6029–6055. https://doi.org/10.1007/s10489-020-02160-x

    Article  Google Scholar 

  27. Cakir B, Dogdu E (2018) Malware classification using deep learning methods. In: Proceedings of the ACMSE 2018 Conference, New York, NY, ACM, pp 1–5. https://doi.org/10.1145/3190645.3190692

  28. Sarker IH (2022) Machine learning for intelligent data analysis and automation in cybersecurity: current and future prospects. Ann Data Sci. https://doi.org/10.1007/s40745-022-00444-2

    Article  Google Scholar 

  29. Ahsan M, Gomes R, Chowdhury MdM, Nygard KE (2021) Enhancing machine learning prediction in cybersecurity using dynamic feature selector. J Cybersecur Privacy 1(1):199–218. https://doi.org/10.3390/jcp1010011

    Article  Google Scholar 

  30. Nunes BAA, Mendonca M, Nguyen X-N, Obraczka K, Turletti T (2014) A survey of software-defined networking: past, present, and future of programmable networks. IEEE Commun Surv Tutor 16(3):1617–1634. https://doi.org/10.1109/SURV.2014.012214.00180

    Article  Google Scholar 

  31. Suzuki K et al (2014) A survey on openflow technologies. IEICE Trans Commun E97B(2):375–386. https://doi.org/10.1587/transcom.E97.B.375

    Article  Google Scholar 

  32. Shalimov A, Zuikov D, Zimarina D, Pashkov V, Smeliansky R (2013) Advanced study of SDN/OpenFlow controllers. In: Proceedings of the 9th Central and Eastern European Software Engineering Conference in Russia, ACM, New York, NY, pp 1–6. https://doi.org/10.1145/2556610.2556621

  33. Salman O, Elhajj IH, Kayssi A, Chehab A (2016) SDN controllers: A comparative study. In: 2016 18th Mediterranean Electrotechnical Conference (MELECON). IEEE, pp 1–6. https://doi.org/10.1109/MELCON.2016.7495430

  34. Akbanov M, Vassilakis VG, Logothetis MD (2019) Ransomware detection and mitigation using software-defined networking: the case of WannaCry. Comput Electr Eng 76:111–121. https://doi.org/10.1016/j.compeleceng.2019.03.012

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Pranveer Singh Institute of Technology, Kanpur, 209305, India

    Ateen Dubey, Geetika Tiwari, Anshika Dixit, Ananya Mishra & Mohit Pandey

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  1. Ateen Dubey
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  2. Geetika Tiwari
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  3. Anshika Dixit
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  4. Ananya Mishra
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  5. Mohit Pandey
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Correspondence to Ateen Dubey .

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Editors and Affiliations

  1. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  2. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, India

    Sartaj Ul Hasan

  3. Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

    Bimal Kumar Roy

  4. Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel

    Boaz Tsaban

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Dubey, A., Tiwari, G., Dixit, A., Mishra, A., Pandey, M. (2024). Leveraging Innovative Technologies for Ransomware Prevention in Healthcare: A Case Study of AIIMS and Beyond. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_49

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_49

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0640-2

  • Online ISBN: 978-981-97-0641-9

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