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Technical and Behavioural Training and Awareness Solutions for Mitigating Ransomware Attacks

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Applied Informatics and Cybernetics in Intelligent Systems (CSOC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1226))

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Abstract

Over the years, there has been a significant increase in cyber security risks and vulnerabilities with one of the most severe threat being ransomware attacks. Ransomware, a variant of malware, encrypts files, data, and often locks computer systems, and retains the decryption key until victims pay a ransom. Current method of ransomware mitigation is the analysis and classification of the ransomware and its variants to propose solution for detection and prevention. This mitigation approach omits technology users as part of the solution especially given their role in falling prey to ransomware by means of social engineering attack vectors. The purpose of this qualitative study was to highlight current and emerging ransomware vectors, and to identify cyber security awareness and education solutions that can be applied to mitigate socially engineered ransomware attacks. A semi-structured interview with executives and managers from several financial, technology, construction, transportation, education, and health industries revealed the lack of current awareness and training approaches to mitigate against socially engineered ransomware attacks. This study recommends some specific cybersecurity training and awareness approaches to consider in order to enable technology users resist and mitigate against ransomware attacks.

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References

  1. Kostopoulos, G.K.: Cyberspace and Cybersecurity, Second. Taylor and Francis (2017)

    Google Scholar 

  2. FBI. 2018 Internet Crime Report. Federal Bureau of Investigation (2018)

    Google Scholar 

  3. Moore, C.: Detecting ransomware with honeypot techniques. In: 2016 Cybersecurity Cyberforensics Conference (CCC), pp. 77–81 (2016)

    Google Scholar 

  4. Wilding, E.: Popp goes the weasel. Virus Bull. 20 (1992)

    Google Scholar 

  5. Young, Y., Yung, M.: Cryptovirology: extortion-based security threats and countermeasures. In: Proceedings of the IEEE Symposium Security Privacy, pp. 129–140 (1996)

    Google Scholar 

  6. Hampton, N., Baig, Z.A., Zeadally, S.: Ransomware behavioural analysis on windows platforms. J. Inform. Secur. Appl. 40, 44–51 (2018)

    Google Scholar 

  7. Bello, A., Mahadevan, V.: A cloud based conceptual identity management model for secured internet of things operation. J. Cyber Secur. Mobility 8(1), 53–74 (2019)

    Article  Google Scholar 

  8. Lueth, K.L.: State of the IoT 2018: Number of IoT devices now at 7B - Market accelerating. IOT Analytics (2018). https://iot-analytics.com/product/state-of-the-iot-02–2017/. Accessed 14 May 2019

  9. O’Kane, P., Sezer, S., Carlin, D.: Evolution of ransomware. IET Netw. 7(5), 321–327 (2018)

    Article  Google Scholar 

  10. Hull, G., John, H., Arief, B.: Ransomware deployment methods and analysis: views from a predictive model and human responses. Crime Sci. 8(1), 2 (2019)

    Article  Google Scholar 

  11. Bajpai, P., Sood, A.K., Enbody, R.: A key-management-based taxonomy for ransomware. In: APWG Symposium on Electronic Crime Research, pp. 1–12 (2018)

    Google Scholar 

  12. Zimba, A., Mulenga, M.: A dive into the deep: demystifying wannacry crypto ransomware network attacks via digital forensics. Int. J. Inform. Technol. Secur. 4(2), 57–68 (2018)

    Google Scholar 

  13. Salvi, M.H.U., Kerkar, M.R.V.: Ransomware: a cyber extortion. Asianj J. Convergence Technol. 2 (2016)

    Google Scholar 

  14. Gibbs, S.: Wannacry: Hackers Withdraw £108,000 Of Bitcoin Ransom| Technology| The Guardian (2017). https://www.theguardian.com/technology/2017/aug/03/wannacry-hackers-withdraw-108000-pounds-bitcoin-ransom. Accessed 28 Oct 2019

  15. Bistarelli, S., Parroccini, M., Santini, F.: Visualising bitcoin flows of ransomware: wannacry one week later. In: ITASEc, p. 8 (2018)

    Google Scholar 

  16. Liao, K., Zhao, Z., Doupe, A., et al.: Behind closed doors: measurement and analysis of cryptolocker ransoms In: Bitcoin. APWG Symposium on Electronic Crime Research, pp. 1–13 (2016)

    Google Scholar 

  17. Ament, C., Jaeger, L.: Unconscious on their own ignorance: overconfidence. Inform. Secur. 13 (2017)

    Google Scholar 

  18. Wang, J., Li, Y., Rao, H.R.: Overconfidence in phishing email detection. J. Assoc. Inform. Syst. 17(11) (2016)

    Google Scholar 

  19. Zimba, A., Wang, Z., Chen, H.: Reasoning crypto ransomware infection vectors with bayesian networks. In: IEEE International Conference Intelligence and Security Informatics, pp. 149–151 (2017)

    Google Scholar 

  20. Gallegos-Segovia, P.L., Bravo-Torres, J.F., Larios-Rosillo, V.M., et al.: Social engineering as an attack vector for ransomware. In: CHILEAN Conference on Electrical, Electronics Engineering, and Informatics and Communication Technologies, pp. 1–6 (2017)

    Google Scholar 

  21. Al-rimy, B.A.S., Maarof, M.A., Shaid, S.Z.: Ransomware threat success factors, taxonomy, and countermeasures: a survey and research directions. Comput. Secur. 74, 144–166 (2018)

    Article  Google Scholar 

  22. Ferreira, A.: Why ransomware needs a human touch. In: International Carnahan Conference on Security Technology, pp. 1–5 (2018)

    Google Scholar 

  23. Conti, M., Dragoni, N., Lesyk, V.: A survey of man in the middle attacks. IEEE Commun. Surv. Tutorials 18(3), 2027–2051 (2016)

    Article  Google Scholar 

  24. Provos, N., Mavrommatis, P., Rajab, M.A., et al.: All Your iFRAMEs Point to Us, p. 15 (2008)

    Google Scholar 

  25. Wang, Z., Wu, X., Liu, C., et al.: Ransomtracer: exploiting cyber deception for ransomware tracing. In: IEEE Third International Conference Data Science Cyberspace, pp. 227–234 (2018)

    Google Scholar 

  26. Symantec: Android.Lockdroid.E| Symantec (2015). https://www.symantec.com/security-center/writeup/2014–103005–2209-99. Accessed 21 May 2019

  27. Chen, Z.G., Kang, H-S., Yin, S.N., et al.: Automatic ransomware detection and analysis based on dynamic API calls flow graph. In: RACS, pp. 196–201 (2017)

    Google Scholar 

  28. Sheen, S., Yadav, A.: Ransomware detection by mining API call usage. In: International Conference Advance Computing Communication Information, pp. 983–987 (2018)

    Google Scholar 

  29. Lika, R.A., Murugiah, D., Brohi, S.N., Ramasamy, D.: NotPetya: cyber attack prevention through awareness via gamification. In: International Conference on Smart Computing and Electronic Enterprise, pp. 1–6 (2018)

    Google Scholar 

  30. Alzahrani, A., Alshehri, A., Alharthi, R., et al.: An overview of ransomware in the windows platform. In: Conference on Computer Science and Computational Intelligence, pp. 612–617 (2017)

    Google Scholar 

  31. Maiorca, D., Mercaldo, F., Giacinto, G., et al.: R-PackDroid: API package-based characterization and detection of mobile ransomware. In: SA, pp. 1718–1723 (2017)

    Google Scholar 

  32. Scaife, N., Carter, H., Traynor, P., et al.: CryptoLock (and Drop It): stopping ransomware attacks on user data. In: IEEE 36th. International Conference Distributed Computing Systems, pp. 303–312 (2016)

    Google Scholar 

  33. Al-rimy, B.A.S., Maarof, M.A., Prasetyo, Y.A., et al.: Zero-day aware decision fusion-based model for crypto-ransomware early detection. Int. J. Integr. Eng. 10(6), 82–88 (2018)

    Article  Google Scholar 

  34. Homayoun, S.: DRTHIS: deep ransomware threat hunting and intelligence system at the fog layer. Future Gener. Comput. Syst. 90, 94–104 (2019)

    Article  Google Scholar 

  35. Azmoodeh, A., Dehghantanha, A., Conti, M., et al.: Detecting crypto-ransomware. In: Iot Network Based Energy Consumption Footprint, vol. 9, no. 4 (2018)

    Google Scholar 

  36. Torres, P.E.P., Yoo, S.G.: Detecting and neutralizing encrypting ransomware attacks by using machine-learning techniques: a literature review. Int. J. Appl. Eng. Res. 12(18), 7902–7911 (2017)

    Google Scholar 

  37. Sgandurra, D., Muñoz-González, L., Mohsen, R., et al.: Automated dynamic analysis of ransomware: benefits, limitations and use for detection arXiv:1609.03020 [cs] (2016)

  38. Zhang, H., Xiao, X., Mercaldo, F., et al.: Classification of ransomware families with machine learning based on n-gram of opcodes. Future Gener. Comput. Syst. 90, 211–221 (2019)

    Article  Google Scholar 

  39. Dion, Y.L., Joshua, A., Brohi, S.N.: Negation of ransomware via gamification and enforcement of standards. In: Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence, pp. 203–208 (2017)

    Google Scholar 

  40. Luo, X., Liao, W.: Awareness education as the key to ransomware prevention. Inform. Syst. Secur. 16(4), 195–202 (2007)

    Article  Google Scholar 

  41. Raman, R., Lal, A.K.: Achuthan: serious games based approach to cyber security concept learning: indian context. In: 2014 International Conference on Green Computing, Communication and Electrical Engineering (ICGCCEE), Coimbatore, India, pp. 1–5 (2014)

    Google Scholar 

  42. Aldawood, H., Skinner, G.: An academic review of current industrial and commercial cyber security social engineering solutions. In: Proceedings of the 3rd International Conference Cryptography, Security and Privacy. ICCSP 2019, Kuala Lumpur, Malaysia, pp. 110–115 (2019)

    Google Scholar 

  43. Tillmann, N., de Halleux, J., Xie, T.: Pex for fun: engineering an automated testing tool for serious games in computer science, p. 9 (2011)

    Google Scholar 

  44. Micallef, N., Arachchilage, N.: Involving users in the design of a serious game for security questions education. arXiv:1710.03888 [cs] (2017)

  45. Beckers, K., Pape, S., Fries, V.: HATCH: hack and trick capricious humans – a serious game on social engineering. In: Proceedings of the 30th International BCS Human Computer Interaction Conference (2016)

    Google Scholar 

  46. Soceanu, A., Vasylenko, M., Gradinaru, A.: Improving cybersecurity skills using network security virtual labs. In: International MultiConference Engineering Computer Science, Hong Kong, vol. 2, p. 6 (2017)

    Google Scholar 

  47. Krombholz, K., Hobel, H., Huber, M., et al.: Advanced social engineering attacks. J. Inform. Secur. Appl. 22, 113–122 (2015)

    Google Scholar 

  48. Veksler, V.D., Buchler, N., Hoffman, B.E., et al.: Simulations in cyber-security: a review of cognitive modeling of network attackers, defenders, and users. Front. Psychol. 9 (2018)

    Google Scholar 

  49. Crouse, P., Farmer, R.: Information security awareness: a course module using simulated spear-phishing. Inform. Secur. Educ. J. 3(1), 21–25 (2016)

    Google Scholar 

  50. Alarcon-Ramirez, A., Martinez-Pabón, M., Kim, C.: Design and prototype of a wireless tailgate detection system using sun spot platform. Int. J. Embed. Syst. Appl. 14 (2011)

    Google Scholar 

  51. Airehrour, D., Nair, N.V., Madanian, S.: Social engineering attacks and countermeasures in the new zealand banking system: advancing a user-reflective mitigation model. Inform. 9(5), 110 (2018)

    Google Scholar 

  52. Social-Engineer LLC.: The 2018 Social Engineering Capture the Flag. Report (2018)

    Google Scholar 

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Authors and Affiliations

  1. School of Social Sciences, WSU, Sydney, NSW, Australia

    Abubakar Bello & Alana Maurushat

Authors
  1. Abubakar Bello
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  2. Alana Maurushat
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Correspondence to Abubakar Bello .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Bello, A., Maurushat, A. (2020). Technical and Behavioural Training and Awareness Solutions for Mitigating Ransomware Attacks. In: Silhavy, R. (eds) Applied Informatics and Cybernetics in Intelligent Systems. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1226. Springer, Cham. https://doi.org/10.1007/978-3-030-51974-2_14

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