Security and Privacy Challenges in AI Microservices: A Review of Threats and Mitigation Strategies

Jorge Silva, Maria Gomez

Abstract


The rapid adoption of artificial intelligence (AI) in various industries has led to the development of AI microservices, which are modular, scalable, and independently deployable services that encapsulate AI functionalities. While AI microservices offer numerous benefits, including flexibility, scalability, and ease of integration, they also introduce significant security and privacy challenges. This article provides a comprehensive review of the security and privacy challenges associated with AI microservices, focusing on the threats that arise from their distributed nature, the complexity of AI models, and the sensitive data they often handle. We also explore various mitigation strategies that can be employed to address these challenges, including secure design principles, encryption techniques, access control mechanisms, and privacy-preserving AI methods. The article concludes with a discussion of future research directions in this area, emphasizing the need for a holistic approach to securing AI microservices.

Full Text:

PDF

References


R. R. Palle and K. C. R. Kathala, “Balance between security and privacy,” in Privacy in the Age of Innovation, Berkeley, CA: Apress, 2024, pp. 129–135.

R. R. Palle and K. C. R. Kathala, “Information security and data privacy landscape,” in Privacy in the Age of Innovation, Berkeley, CA: Apress, 2024, pp. 21–30.

J. G. C. Ramírez, “Integrating AI and NISQ technologies for enhanced mobile network optimization,” QJETI, vol. 5, no. 1, pp. 11–22, Jan. 2020.

A. K. Saxena, “Advancing Location Privacy in Urban Networks: A Hybrid Approach Leveraging Federated Learning and Geospatial Semantics,” International Journal of Information and Cybersecurity, vol. 7, no. 1, pp. 58–72, Mar. 2023.

J. G. C. Ramírez, “Quantum control and gate optimization in graphane-based quantum systems,” J. Appl. Math. Mech., vol. 4, no. 1, pp. 69–79, Oct. 2020.

I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. London, England: MIT Press, 2016.

I. Doghudje and O. Akande, “Securing the Internet of Things: Cybersecurity Challenges for Smart Materials and Big Data,” IJIC, vol. 6, no. 1, pp. 82–108, Mar. 2022.

“Analysis of Social Network Data Mining for Security Intelligence Privacy Machine Learning,” International Journal on Recent and Innovation Trends in Computing and Communication.

M.-Y. Wu, M.-C. Yu, J.-S. Leu, and S.-K. Chen, “Correction to: Enhancing security and privacy of images on cloud by histogram shifting and secret sharing,” Multimed. Tools Appl., vol. 77, no. 13, pp. 17307–17307, Jul. 2018.

J. G. C. Ramírez, “Vibration analysis with AI: Physics-informed neural network approach for vortex-induced vibration,” Int. J. Radiat. Appl. Instrum. C Radiat. Phys. Chem., vol. 11, no. 3, Mar. 2021.

E. Ismagilova, L. Hughes, N. P. Rana, and Y. K. Dwivedi, “Security, privacy and risks within smart cities: Literature review and development of a smart city interaction framework,” Inf. Syst. Front., vol. 24, no. 2, pp. 393–414, 2022.

L. Benarous and B. Kadri, “Hybrid pseudonym change strategy for location privacy in VANET: protecting location privacy in VANET,” Int. J. Inf. Priv. Secur. Integr., vol. 4, no. 3, p. 153, 2020.

V. Ramamoorthi, “Applications of AI in Cloud Computing: Transforming Industries and Future Opportunities,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 9, no. 4, pp. 472–483, Aug. 2023.

V. Ramamoorthi, “Real-Time Adaptive Orchestration of AI Microservices in Dynamic Edge Computing,” Journal of Advanced Computing Systems, vol. 3, no. 3, pp. 1–9, Mar. 2023.

T. K. Dang, J. Küng, T. M. Chung, and M. Takizawa, Eds., Future data and security engineering. Big data, security and privacy, smart city and industry 4.0 applications, 1st ed. Singapore, Singapore: Springer, 2021.

I. Krontiris, F. Freiling, and T. Dimitriou, “Location privacy in urban sensing networks: research challenges and directions [Security and Privacy in Emerging Wireless Networks,” IEEE Wirel. Commun., vol. 17, no. 5, pp. 30–35, Oct. 2010.

C. Thota, G. Manogaran, D. Lopez, and Vijayakumar V., “Big Data security framework for distributed cloud data centers,” in Cybersecurity Breaches and Issues Surrounding Online Threat Protection, IGI Global, 2017, pp. 288–310.

V. Ramamoorthi, “Optimizing Cloud Load Forecasting with a CNN-BiLSTM Hybrid Model,” International Journal of Intelligent Automation and Computing, vol. 5, no. 2, pp. 79–91, Nov. 2022.

Y. Han, Z. Wang, Q. Ruan, and B. Fang, “SAPIENS CHAIN: A BLOCKCHAIN-BASED CYBERSECURITY FRAMEWORK,” in Computer Science & Information Technology (CS & IT), 2018.

H. X. Nguyen, S. Zhu, and M. Liu, “A survey on graph neural networks for microservice-based cloud applications,” Sensors (Basel), vol. 22, no. 23, p. 9492, Dec. 2022.

V. R. V. Lakshmi, TIFAC-CORE in Cyber Security, Amrita School of Engineering, Coimbatore Amrita Vishwa Vidyapeetham, Amrita University, India, and G. K. T, “Mobile social networks: Architecture, privacy, security issues and solutions,” J. Commun., 2017.

V. Ramamoorthi, “Exploring AI-Driven Cloud-Edge Orchestration for IoT Applications,” 2023.

J. G. C. Ramírez and M. Kamal, “Theoretical exploration of two-dimensional materials for quantum computing applications,” JICET, vol. 8, no. 4, pp. 45–57, Nov. 2023.

M. G. Samaila, M. Neto, D. A. B. Fernandes, M. M. Freire, and P. R. M. Inácio, “Challenges of securing Internet of Things devices: A survey,” Secur. Priv., vol. 1, no. 2, p. e20, Mar. 2018.

S. Taheri, M. Salem, and J.-S. Yuan, “Leveraging image representation of network traffic data and transfer learning in botnet detection,” Big Data Cogn. Comput., vol. 2, no. 4, p. 37, Nov. 2018.

J. G. C. Ramírez and M. Kamal, “Graphene plasmonics for enhanced quantum information processing,” AIFIR, vol. 13, no. 11, pp. 18–25, Nov. 2023.

V. Malik and S. Singh, “Big data computing: Privacy risks management,” J. Comput. Theor. Nanosci., vol. 17, no. 5, pp. 2248–2253, May 2020.

X. Zhang and A. A. Ghorbani, “Human Factors in Cybersecurity: Issues and Challenges in Big Data,” in Research Anthology on Privatizing and Securing Data, IGI Global, 2021, pp. 1695–1725.

J. G. C. Ramirez, “From Autonomy to Accountability: Envisioning AI’s Legal Personhood,” ARAIC, vol. 6, no. 9, pp. 1–16, Sep. 2023.

J. G. C. Ramirez, “How Mobile Applications can improve Small Business Development,” ERST, vol. 7, no. 1, pp. 291–305, Nov. 2023.

C. Dwork and A. Roth, “The algorithmic foundations of differential privacy,” Found. Trends Theor. Comput. Sci., vol. 9, no. 3–4, pp. 211–407, 2013.

J. G. C. Ramírez, “Incorporating Information Architecture (ia), Enterprise Engineering (ee) and Artificial Intelligence (ai) to Improve Business Plans for Small Businesses in the United States,” Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), vol. 2, no. 1, pp. 115–127, 2023.

T. D. Breaux and A. I. Anton, “Analyzing regulatory rules for privacy and security requirements,” IEEE Trans. Softw. Eng., vol. 34, no. 1, pp. 5–20, Jan. 2008.

Q. Huang, L. Wang, and Y. Yang, “Secure and Privacy-Preserving Data Sharing and Collaboration in Mobile Healthcare Social Networks of Smart Cities,” Security and Communication Networks, vol. 2017, Aug. 2017.

J. G. C. Ramirez, “Comprehensive exploration of the CR model: A systemic approach to Strategic Planning,” International Journal of Culture and Education, vol. 1, no. 3, Aug. 2023.

J. T. Koyazo, C. Antonio, M. Villari, A. Lay-Ekuakille, and M. Fazio, “Collaborative edge computing to bring microservices in smart rural areas,” in 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Taormina, Italy, 2022.

A. C. Murphy and J. D. Moreland, “Integrating AI microservices into hard-real-time SoS to ensure trustworthiness of digital enterprise using mission engineering,” J. Integr. Des. Process Sci., vol. 25, no. 1, pp. 38–54, Apr. 2022.

J. G. C. Ramírez, “Struggling Small Business in the US. The next challenge to economic recovery,” IJBIBDA, vol. 5, no. 1, pp. 81–91, Feb. 2022.

M. Karimi and A. A. Barfroush, “Proposing a dynamic executive microservices architecture model for AI systems,” arXiv [cs.SE], 10-Aug-2023.

J. G. C. Ramírez, M. Hassan, and M. Kamal, “Applications of artificial intelligence models for computational flow dynamics and droplet microfluidics,” JSTIP, vol. 6, no. 12, Dec. 2022.

B. Barua and M. S. Kaiser, “A next-generation approach to airline reservations: Integrating Cloud microservices with AI and blockchain for enhanced operational performance,” arXiv [cs.AI], 10-Nov-2024.

B. Barua and M. S. Kaiser, “Optimizing travel itineraries with AI algorithms in a microservices architecture: Balancing cost, time, preferences, and sustainability,” arXiv [cs.SE], 23-Oct-2024.

Y. Gahi and M. Guennoun, “Big data analytics: Security and privacy challenges,” 2016 IEEE Symposium on, 2016.

P. Yuan, Y. Xia, Y. Tian, and H. Xu, “TRiP: a transfer learning based rice disease phenotype recognition platform using SENet and microservices,” Front. Plant Sci., vol. 14, p. 1255015, 2023.

Y. Han, W. Li, J. Gao, and Z. Zhao, “Provisioning big data applications as services on containerised cloud: a microservices-based approach,” Int. J. Serv. Technol. Manag., vol. 26, no. 2–3, p. 167, 2020.

J. G. C. Ramírez, “The role of graphene in advancing quantum computing technologies,” Annu. Rep. - Aust. Inst. Criminol., vol. 4, no. 1, pp. 62–77, Feb. 2021.

B. E. Khalyly, A. Belangour, M. Banane, and A. Erraissi, “A comparative study of microservices-based IoT platforms,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 8, 2020.

J. G. C. Ramírez, “Enhancing temporal quantum coherence in graphene-based superconducting circuits,” International Journal of Applied Machine Learning and Computational Intelligence, vol. 11, no. 12, Dec. 2021.

I. Vistbakka and E. Troubitsyna, “Analysing privacy-preserving constraints in microservices architecture,” in 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid, Spain, 2020.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.