Opportunistic security architecture for osmotic computing paradigm in dynamic IoT-Edge's resource diffusion

ABSTRACT

Increased heterogeneity of physical resources has had positive and negative effects in Internet of Things (IoT) through the existence of edge computing. As a result, there has been a need for effective dynamic management of IoT, cloud and edge resources, in order to address the existence of low-level constraints during resource migration. Nevertheless, the explosion of IoT devices and data has allowed orchestration of microservices to adopt an opportunistic approach to how applications and services are deployed in the edge in IoT platform. A notable approach has been osmotic computing that allows resources from a federated cloud to be able to diffuse from an ecosystem of higher solute (network properties and entities) concentration to solvent (applications, layered interfaces and services). We posit that, while computing resources and applications are able to move from the federated environment, to the cloud deployable models, to the edge, then to IoT ecosystem, there is a higher chance of susceptibility of threats and attacks that may be directed to the emerging edge applications/data due to dynamic emergent configurations. This paper proposes a 5-layer opportunistic architecture that adds security metrics across different levels of osmotic computing paradigm. The proposed 5-layer security architecture addresses the need for autonomously securing resources-edge computation, edge storage and emerging edge configurations as the computing resources move to a higher solute in heterogenous edge and cloud datacenters across IoT devices. This has been achieved by proposing security metrics that address the prevailing challenge with a degree of certainty.

References

1. Yousefpour, A., Fung, C, Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A.....& Jue, J. P. (2019). All one needs to know about fog computing and related edge computing paradigms: A complete survey. Journal of Systems Architecture.
2. Alkhabbas, F. (2018). Towards Emergent Configurations in the Internet of Things (Doctoral dissertation, Malmö university. Faculty of Technology and Society).
3. Villari, M., Fazio, M., Dustdar, S., Rana, O., & Ranjan, R. (2016). Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Computing, 3(6), 76--83.
4. Villari, M., Fazio, M., Dustdar, S., Rana, O., & Ranjan, R. (2016). Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Computing, 3(6), 76--83.
5. Nardelli, M., Nastic, S., Dustdar, S., Villari, M., & Ranjan, R. (2017). Osmotic flow: Osmotic computing+ iot workflow. IEEE Cloud Computing, 4(2), 68--75.
6. Villari, M., Celesti, A., & Fazio, M. (2017). Towards Osmotic Computing: Looking at Basic Principles and Technologies. CISIS 2017: Complex, Intelligent, and Software Intensive Systems (pp. 906--915). Springer.
7. Sharma, V., Srinivasan, K., Jayakody, D. N. K., Rana, O., & Kumar, R. (2017). Managing service-heterogeneity using osmotic computing. arXiv preprint arXiv:1704.04213.
8. Ah, S., Kibria, M. G., Jarwar, M. A., Kumar, S., & Chong, I. (2017). Microservices Model in WoO based IoT Platform for Depressive Disorder Assistance. 2017 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 864--866). Yonginsi:IEEE.
9. Kebande, V. R., & Ray, I. (2016, August). A generic digital forensic investigation framework for internet of things (iot). In 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud) (pp. 356--362). IEEE.
10. Kebande, V. R., & Venter, H. S. (2018). On digital forensic readiness in the cloud using a distributed agent-based solution: issues and challenges. Australian Journal of Forensic Sciences, 50(2), 209--238.
11. Coulson, N. C, Sotiriadis, S., & Bessis, N. (2020). Adaptive microservice scaling for elastic applications. IEEE Internet of Things Journal, 1--8.
12. Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2017, March). Blockchain for IoT security and privacy: The case study of a smart home. In 2017 IEEE international conference on pervasive computing and communications workshops (PerCom workshops) (pp. 618--623). IEEE.
13. Morabito, R., Cozzolino, V., Ding, A. Y., Beijar, N., & Ott, J. (2018). Consolidate IoT edge computing with lightweight virtualization. IEEE Network, 32(1), 102--111.
14. Shi, W., Pallis, G., & Xu, Z. (2019). Edge Computing [Scanning the Issue]. Proceedings of the IEEE, 107(8), 1474--1481.
15. Maxime Lagrasse, Avinash Singh, Howard Munkhondya, Adeyemi Ikuesan, and Hein Venter. 2020. Digital forensic readiness framework for software-defined networks using a trigger-based collection mechanism. Proceedings of the 15th International Conference on Cyber Warfare and Security, ICCWS 2020, 296--305.
16. Howard Munkhondya, Adeyemi R. Ikuesan, and Hein S. Venter. 2020. A case for a dynamic approach to digital forensic readiness in an SDN platform. Proceedings of the 15th International Conference on Cyber Warfare and Security, ICCWS 2020, 584--593.
17. Howard Munkhondya, Adeyemi Ikuesan, and Hein Venter. 2019. Digital forensic readiness approach for potential evidence preservation in software-defined networks. 14th International Conference on Cyber Warfare and Security, ICCWS 2019, 268--276.
18. Jamshidi, P.; Pahl, C; Mendonça, N. C; Lewis, J.; Tilkov, S. (May 2018). "Microservices: The Journey So Far and Challenges Ahead". IEEE Software. 35 (3): 24--35.
19. Xu, R., Jin, W., & Kim, D. (2019). Microservice Security Agent Based on API Gateway in Edge Computing. Sensors, 19(22), 4905.
20. N. M. Karie, N. M. Sahri and P. Haskell-Dowland, "IoT Threat Detection Advances, Challenges and Future Directions," 2020 Workshop on Emerging Technologies for Security in IoT (ETSecIoT), Sydney, Australia, 2020, pp. 22--29
21. Kebande, V. R., Bugeja, J., & Persson, J. A. (2020). Internet of Threats Introspection in Dynamic Intelligent Virtual Sensing. arXiv preprint arXiv:2006.11801.
22. Kebande, V. R., Karie, N. M., & Venter, H. S. (2018). Adding digital forensic readiness as a security component to the IoT domain.
23. Khorashadizadeh, S., Ikuesan, A. R., & Kebande, V. R. (2019, September). Generic 5G Infrastructure for IoT Ecosystem. In International Conference of Reliable Information and Communication Technology (pp. 451--462). Springer, Cham.
24. Pundir, Y., Sharma, N. and Singh, Y. (2016). Internet of Things (IoT): Challenges and Future Directions. International Journal of Advanced Research in Computer and Communication Engineering Vol.5, Issue 3, pp.960--964
25. Burhanuddin, M. A., Mohammed, A.A., Ismail, R.and Basiron, H, (2017). Internet of Things Architecture: Current Challenges and Future Direction of Research. International Journal of Applied Engineering Research. ISSN 0973-4562 Vol. 12, Number 21 pp.11055--11061
26. Hamilton, E., (2018). "What is Edge Computing: The Network Edge Explained". cloudwards.net. Retrieved 2019-05-14.
27. Kebande, V. R., & Venter, H. S. (2018). Novel digital forensic readiness technique in the cloud environment. Australian Journal of Forensic Sciences, 50(5), 552--591.
28. Kebande, V. R., Kigwana, I, Venter, H. S., Karie, N. M., & Wario, R. D. (2018, August). CVSS Metric-Based Analysis, Classification and Assessment of Computer Network Threats and Vulnerabilities. In 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD) (pp. 1--10). IEEE.

Index Terms

• Security and privacy

  • Formal methods and theory of security

    • Formal security models