Secure Embedded Systems on a Budget: Low-Cost Privilege Separation Strategies

By: Arti Sachan, Insights2Techinfo, USA; Kwok Tai Chui, Hong Kong Metropolitan University (HKMU) , Hong Kong

Embedded systems play a crucial role in various industries, powering devices such as IoT devices, medical equipment, and industrial control systems. Ensuring the security of these systems is of paramount importance in today’s interconnected world. However, securing embedded systems can be challenging, especially when resources are limited. In this blog post, we will explore low-cost privilege separation strategies that can enhance the security of embedded systems without breaking the budget.

Understanding Privilege Separation in Embedded Systems

 Privilege separation is a security principle that involves dividing the system’s components into different privilege levels, limiting the capabilities of each component to only what is necessary. This separation helps to mitigate security risks by containing the impact of potential vulnerabilities and preventing unauthorized access or control over critical components. In embedded systems, privilege separation typically involves separating privileges at the kernel, user, and application levels.

Low-Cost Privilege Separation Strategies

 To achieve privilege separation in embedded systems without incurring high costs, several strategies can be implemented:

  1. Hardware Isolation Techniques: Hardware features can be leveraged to achieve privilege separation. This involves utilizing mechanisms like memory protection units (MPUs) and virtualization to isolate critical components from less trusted ones. By assigning different memory regions and access permissions, hardware-based partitioning ensures that each component operates within its designated privilege level.
  2. Software-Based Isolation: Software-based isolation techniques provide an alternative to hardware isolation. This includes containerization and virtualization techniques, where applications are encapsulated within their own virtual environments, limiting their access to the underlying system resources. Sandboxing techniques further enhance security by enforcing strict boundaries around applications and restricting their interactions with the rest of the system.
  3. Role-Based Access Control (RBAC): Role-Based Access Control (RBAC) is a security model that defines and enforces user roles and their associated privileges. By implementing RBAC in embedded systems, access to critical functions and resources can be restricted based on predefined roles. RBAC ensures that only authorized users or applications have the necessary privileges to perform specific actions, reducing the risk of unauthorized access and potential security breaches.

Overcoming Budget Constraints

 Implementing low-cost privilege separation strategies can help overcome budget constraints while ensuring security. Here are some approaches to consider:

  1. Open-Source Solutions: Leveraging open-source operating systems and frameworks can significantly reduce costs. These solutions often come with built-in security features, such as access control mechanisms and sandboxing capabilities. Additionally, collaborating with the open-source community allows for cost-effective security solutions tailored to the specific needs of embedded systems.
  2. Minimalistic Designs: Designing embedded systems with minimalistic architectures can help reduce the attack surface and resource requirements. By prioritizing critical components and functions, resources can be allocated efficiently to secure those areas. Lightweight security mechanisms, tailored to the specific needs of the system, can provide cost-effective protection while minimizing resource consumption.
  3. Efficient Resource Allocation: Conducting a risk assessment helps prioritize security measures based on their importance. By focusing resources on critical components and functions that pose higher security risks, embedded systems can achieve effective security within budget constraints. This approach ensures that resources are allocated where they are most needed, maximizing the system’s overall security posture.

Case Studies and Real-World Examples

 Let’s examine some real-world examples of low-cost privilege separation strategies in embedded systems:

Table 1: Low-Cost Privilege Separation Strategies in Embedded Systems

StrategyDescription
Hardware IsolationLeveraging hardware features for privilege separation
Software-Based IsolationContainerization and virtualization techniques
Role-Based Access Control (RBAC)Enforcing access control based on predefined user roles

Integration with Secure Development Lifecycle

 To ensure the effectiveness of privilege separation strategies, integration with the Secure Development Lifecycle (SDL) is crucial. This includes incorporating privilege separation considerations from the early stages of system development, conducting security testing and verification, and implementing continuous monitoring and updates to address emerging threats and vulnerabilities.

Future Trends and Conclusion

 The security landscape for embedded systems continues to evolve, and new technologies and trends emerge to address the challenges. By implementing low-cost privilege separation strategies, even with limited resources, embedded systems can achieve enhanced security. Continuous improvement, adaptation to evolving threats, and a proactive security approach are essential for safeguarding embedded systems on a budget. By considering cost-effective privilege separation strategies, organizations can protect their embedded systems and maintain the integrity and confidentiality of critical data.

References

  1. Vai, M., Whelihan, D. J., Nahill, B. R., Utin, D. M., O’Melia, S. R., & Khazan, R. I. (2016). Secure embedded systemsLincoln Laboratory Journal22(1), 110-122.
  2. Ravi, S., Raghunathan, A., & Chakradhar, S. (2004, January). Tamper resistance mechanisms for secure embedded systems. In 17th International Conference on VLSI Design. Proceedings. (pp. 605-611). IEEE.
  3. Hwang, D. D., Schaumont, P., Tiri, K., & Verbauwhede, I. (2006). Securing embedded systems. IEEE Security & Privacy4(02), 40-49.
  4. Zhou, L., et al. (2022). Panner: Pos-aware nested named entity recognition through heterogeneous graph neural networkIEEE Transactions on Computational Social Systems.
  5. McLoughlin, I. (2008, December). Secure embedded systems: The threat of reverse engineering. In 2008 14th IEEE International Conference on Parallel and Distributed Systems (pp. 729-736). IEEE.
  6. Choi, C., et al. (2021). Sensored semantic annotation for traffic control based on knowledge inference in videoIEEE Sensors Journal21(10), 11758-11768.
  7. Heiser, G. (2005). Secure embedded systems need microkernelsUSENIX; login30(6), 9-13.
  8. Casillo, M., et al. (2021). Fake news detection using LDA topic modelling and K-nearest neighbor classifier. In Computational Data and Social Networks: 10th International Conference, CSoNet 2021, Virtual Event, November 15–17, 2021, Proceedings 10 (pp. 330-339). Springer International Publishing.
  9. Kleidermacher, D., & Kleidermacher, M. (2012). Embedded systems security: practical methods for safe and secure software and systems development. Elsevier.
  10. Bhatti, M. H., et al. (2019). Soft computing-based EEG classification by optimal feature selection and neural networksIEEE Transactions on Industrial Informatics15(10), 5747-5754.
  11. Gebotys, C. H. (2006). A table masking countermeasure for low-energy secure embedded systemsIEEE Transactions on Very Large Scale Integration (VLSI) Systems14(7), 740-753.
  12. Gebotys, C. H. (2006). A table masking countermeasure for low-energy secure embedded systemsIEEE Transactions on Very Large Scale Integration (VLSI) Systems14(7), 740-753.
  13. Sahoo, S. R., et al. (2019). Hybrid approach for detection of malicious profiles in twitter. Computers & Electrical Engineering76, 65-81.
  14. Cvitić, I., et al. (2021). Boosting-based DDoS detection in internet of things systemsIEEE Internet of Things Journal9(3), 2109-2123.
  15. Almakhdhub, N. S., Clements, A. A., Bagchi, S., & Payer, M. (2020, February). $\mu $ RAI: Securing Embedded Systems with Return Address Integrity. In Network and Distributed Systems Security (NDSS) Symposium.
  16. Alieyan, K., et al. (2021). DNS rule-based schema to botnet detectionEnterprise Information Systems15(4), 545-564.
  17. Mozaffari-Kermani, M., Tian, K., Azarderakhsh, R., & Bayat-Sarmadi, S. (2014). Fault-resilient lightweight cryptographic block ciphers for secure embedded systems. IEEE Embedded Systems Letters6(4), 89-92.
  18. Gupta, B. B., Yadav, K., Razzak, I., Psannis, K., Castiglione, A., & Chang, X. (2021). A novel approach for phishing URLs detection using lexical based machine learning in a real-time environment. Computer Communications175, 47-57.
  19. Fournaris, A. P., & Sklavos, N. (2014). Secure embedded system hardware design–A flexible security and trust enhanced approach. Computers & Electrical Engineering40(1), 121-133.

Cite As

Sachan A., Chui K. T. (2023) Secure Embedded Systems on a Budget: Low-Cost Privilege Separation Strategies, Insights2Techinfo, pp.1

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