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Safeguarding Networks: Combatting Mirai Malware Attacks in the IoT Era

Learn about real-world evidence on ISP and consumer efforts to remove Mirai malware from IoT devices, including solutions and criticisms.

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Safeguarding Networks: Combatting Mirai Malware Attacks in the IoT Era

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  1. Cleaning Up the Internet of Evil Things: Real-World Evidence on ISP and Consumer Efforts to Remove Mirai Zhuohao Li Sep 25, 2019

  2. Introduction • Understanding how to guarantee the internal and external security of networks is an essential element especially in the modern era where the IoT has become a common aspect. • Reports from research on IoT has revealed that approximately 6.5 billion gadgets are connected to the internet, a figure that means they have surpassed human connections (Angrishi, 2017). • The attack on consumer products has made the situation even worse because people lack the information. • IoT botnet is a term that refers to a collection of IoT devices that have been compromised such as DVRs, cameras, wearables, routers and other technologies that can be embedded.

  3. Introduction Continued 5. The variant of the Internet of Thing’s malware has been changing constantly and therefore essential to analyze the architecture to determine malfunctions. 6. A common algorithm used is the Artificial Neural Network that clearly detects anomalies.

  4. Solutions • To handle Mirai infection, users are educated about the importance of a walled garden that has managed to successfully solve 92% of the affected cases (Cetin et al., 2019). • End-users should be aware of technical issues and the best ways to remediate and protect their gadgets. • After guaranteeing and notifying customers who have reported a more than 90% success rate, the rates of reinfection have also been considerably low. • The lack of information about the IoT botnet has made many users to run anti-virus software that do not solve the problem.

  5. Solutions Continued 5. Another effective solution to the malware problem affecting the operations of devices connected to the internet is the utilization of abuse feeds. 6. There are other solutions to the IoT malware attacks such as the Censys Scans and the Darknet.

  6. Criticism • The solutions suggested to tackle malware cases in the era of IoT reveals there are strengths and weaknesses. • All stakeholders such as companies, government, research institutions among others are supposed to be uniting in developing measures to improve the security of IoT. • There is more than just the lack of knowledge which affect the intervention techniques. • The concept of walled garden is impossible due to governments’ needs to consolidate and acquire more power.

  7. Criticism Continued 5. Illegal workarounds and cloud attacks further makes it impossible to implement IoT security measure. 6. More research can be conducted on the possible security measures to be introduced in the area because hackers and other malicious people are constantly looking for possible loopholes to exploit in order to compromise the data of the network.

  8. References • Angrishi, K. (2017). Turning internet of things (iot) into internet of vulnerabilities (iov): Iot botnets. arXiv preprint arXiv:1702.03681. • Antonakakis, M., April, T., Bailey, M., Bernhard, M., Bursztein, E., Cochran, J., ... & Kumar, D. (2017). Understanding the mirai botnet. In 26th {USENIX} Security Symposium ({USENIX} Security 17) (pp. 1093-1110). • Ashok, R., Zinopoulou, M., Atlam, H., Wills, G., & Zulkipli, N. H. (2016). Building on a secure foundation for the Internet of Things. • Bertino, E., & Islam, N. (2017). Botnets and internet of things security. Computer, (2), 76-79. • Brous, P., & Janssen, M. (2015, October). A systematic review of impediments blocking internet of things adoption by governments. In Conference on e-Business, e-Services and e Society (pp. 81-94). Springer, Cham.

  9. Çetin, O., Gañán, C., Altena, L., Kasama, T., Inoue, D., Tamiya, K., ... & van Eeten, M. (2019, February). Cleaning Up the Internet of Evil Things: Real-World Evidence on ISP and Consumer Efforts to Remove Mirai. In NDSS. • Kolias, C., Kambourakis, G., Stavrou, A., & Voas, J. (2017). DDoS in the IoT: Mirai and other botnets. Computer, 50(7), 80-84. • Lim, S., & Cortina, L. M. (2005). Interpersonal mistreatment in the workplace: the interface and impact of general incivility and sexual harassment. Journal of applied psychology, 90(3), 483. • Matz, S., Chan, Y. W. F., & Kosinski, M. (2016). Models of personality. In Emotions and Personality in Personalized Services (pp. 35-54). Springer, Cham. • Risavy, S. D., & Hausdorf, P. A. (2011). Personality testing in personnel selection: Adverse impact and differential hiring rates. International Journal of Selection and Assessment, 19(1), 18-30. • Seibert, S. E., & DeGeest, D. S. (2017). The five factor model of personality in business and industry. The Oxford Handbook of the Five Factor Model, 27, 381. • Zhao, H., Seibert, S. E., & Lumpkin, G. T. (2010). The relationship of personality to entrepreneurial intentions and performance: A meta analytic review. Journal of management, 36(2), 381-404.

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