Cybersecurity Dissertation Topics

Cybersecurity Dissertation Topics

Info: Cybersecurity Dissertation Topics
Published: 27th November 2025 in Cybersecurity Dissertation Topics

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Dissertation Topic 1:

Standardisation Challenges in Distributed Energy Resource Cybersecurity: Fragmented Protocols, Inconsistent Controls, and the Governance Gap

Background Context

The current DER cybersecurity standards are still fragmented and vary across different communication protocols, including IEC 62351, IEEE 1815, and proprietary vendor-specific ones. This situation has led to a disordered state of governance where the utilities, aggregators, and DER owners are applying different security protocol fragmentation controls that not only limit interoperability but also create a situation where the whole system is more vulnerable. The literature has pointed out more often that the multi-vendor DER ecosystems do not have a common security baseline, thus becoming “weak points” that attackers could utilise.
PhD-Level Verification
This research topic is very promising and well-grounded in a recognised albeit unsolved issue in the cybersecurity of smart grids: the absence of unified standards. The literature supports the claim of a huge fragmentation of DER protocols, but very little research has been done on the topic of the cascading vulnerabilities that are formed as a result of these discrepancies in distributed energy ecosystems.
Research Questions
How do inconsistencies in DER communication protocols contribute to the creation of systemic cybersecurity vulnerabilities? What are the factors in the organisational, technical, and regulatory areas that hinder the implementation of unified cybersecurity principles among the different DER stakeholders (utilities, aggregators, prosumers)? What kind of standardisation frameworks or governance models can make it possible to have secure, interoperable, and scalable DER communication?
PhD-Level Contributions
  • A conceptual model for unified cybersecurity baselines for distributed energy resources (DER) that takes into account different protocols.
  • Guidelines for regulators that are valid in practice concerning the standardisation of the protocols for multi-vendor DER setups.
Suggested Readings
International Electrotechnical Commission (IEC). (2018). IEC 62351: Power Systems Management and Associated Information Exchange – Data and Communications Security. Geneva: IEC. National Institute of Standards and Technology (NIST). (2014). NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 3.0 (NIST SP 1108R3).

Dissertation Topic 2:

Cybersecurity Risks in Emerging DER Management Platforms: VPPs, DERMS, and V2G/B2G Vulnerability Propagation

Background Context
VPPs, DERMS platforms, and V2G/B2G systems form new operational strata that pool together distributed resources. They provide more flexibility, but the literature indicates that little is known regarding the attack surfaces at the platform level caused by extensive connectivity, multi-stakeholder controls, and the integration of household appliances. There is a considerable gap in modelling the transmission of vulnerabilities across the DERMS-VPP cybersecurity risk-device ecosystems.
PhD-Level Verification
Technological progress has outstripped the pace of cybersecurity research; hence, this is a new research area with a lot of potential. Platform-level risks seem to exist, but they are not elaborated or empirically tested to the desired extent.
Research Questions
  • What novel cyber threats are present in the operational models of VPPs, DERMS and V2G/B2G ecosystems? How do connectivity patterns between household devices and DER platforms heighten exposure to B2G energy grid cyber threats Are there any chances that DERMS and VPPs will necessitate collaborative cybersecurity mechanisms across different control layers to be able to avert systemic risks?

PhD-Level Contributions

A multi-layered threat model for next-generation distributed energy resource management platforms.A cybersecurity framework for the platform that combines VPP and DERMS device interactions.

Suggested Readings

  • Australian Energy Market Operator (AEMO). (2020). VPP Demonstrations Program – Cybersecurity and API Insights Report. Melbourne: AEMO.
  • Mwasilu, F., Justo, J. J., Kim, E.-K., Do, T. D., & Jung, J.-W. (2014). Electric vehicles and smart grid interaction: A review on V2G integration. Renewable and Sustainable Energy Reviews, 34, 501–516.

Dissertation Topic 3:

Market-Driven Cyber Risks in Transactive Energy Systems: Vulnerabilities of DER Aggregators in Deregulated Electricity Markets

Background Context
The involvement of distributed energy resources (DERs) in deregulated markets, peer-to-peer (P2P) trading, and transactive energy cybersecurity challenges. The literature points out that DER aggregators are more vulnerable because of their resource variability and frequent communication. However, the investigation seldom clarifies the reasons for the appearance of aggregator weaknesses or the ways of their spreading in the market-based systems. As cyber risk in deregulated electricity markets continues to increase, understanding these vulnerabilities becomes crucial.
PhD Level Verification
The intersection of cybersecurity, energy economics, and market design is a quite unexplored area that will probably result in a strong academic contribution if the issue is dealt with properly.
Research Questions
To what extent do deregulation and the introduction of new markets lead to an increased cyber vulnerability in transactive energy and P2P markets? What makes DER (Distributed Energy Resources) aggregators more prone to hacking, and how do these vulnerabilities affect the entire system? What are the cybersecurity standards and measures to be embraced by the market-driven DER coordination platforms?
PhD-Level Contributions
A model for the transmission of risks in betterment-driven DER ecosystems. Security and regulation guidelines for transactive platforms. Secure architecture for flexible DER aggregator operations The proposed research is likely to lead to highly impactful interdisciplinary publications.
Suggested Readings
Gupta, N., Prusty, B. R., Alrumayh, O., Almutairi, A., & Alharbi, T. (2022). The Role of Transactive Energy in the Future Energy Industry: A Critical Review. Energies, 15(21), 8047. https://doi.org/10.3390/en15218047 Kok and S. Widergren, “A Society of Devices: Integrating Intelligent Distributed Resources with Transactive Energy,” in IEEE Power and Energy Magazine, vol. 14, no. 3, pp. 34-45, May-June 2016, doi: 10.1109/MPE.2016.2524962.

Dissertation Topic 4:

Cybersecurity Challenges of IoT, Cloud/Edge Computing, and SDN in Large-Scale DER Integration

Background
Modern DER integration is mainly supported by IoT devices, cloud/edge architectures, and SDN. IoT technologies open up weaknesses at the device level, raising concerns around IoT smart grid security. Cloud/edge systems distribute data over a larger area and make it more likely to be attacked; SDN gives control to one central point, which can cause single points of failure. The interaction of these technologies in terms of cybersecurity for DER is pointed out by the literature; however, it is not systematically explained yet. Understanding how cloud/edge computing and SDN in smart grid cybersecurity interact with IoT infrastructures is essential for future DER deployments.
PhD-Level Verification

The subject matter presents a combination of three technological foundations with differing security implications—a complex and developing issue which is appropriate for doctoral research.

Research Questions
  • What are the systemic cybersecurity vulnerabilities that IoT-enabled DER devices, together with their characteristics, can bring about?
  • What kind of threats are involved in the management of data through cloud and edge in the aggregation of DER?
Contributions at the PhD-Level
A comprehensive architectural model for IoT-Edge-SDN secured DER networks. Design principles for the development of resilient and robust communication infrastructures of DER. Utilities’ guidance in the adoption of next-gen DER Technologies. A very technical and futuristic topic with considerable publication potential.
Suggested Readings
W. Yu et al., “A Survey on the Edge Computing for the Internet of Things,” in IEEE Access, vol. 6, pp. 6900-6919, 2018, doi: 10.1109/ACCESS.2017.2778504. S. Scott-Hayward, G. O’Callaghan and S. Sezer, “Sdn Security: A Survey,” 2013 IEEE SDN for Future Networks and Services (SDN4FNS), Trento, Italy, 2013, pp. 1-7, doi: 10.1109/SDN4FNS.2013.6702553.

Dissertation Topic 5:

Large Language Models (LLMs) in DER Cybersecurity: Opportunities, Risks, and Their Impact on Smart Grid Defence

Background Context
Large Language Models (LLMs) are being more and more utilised in grid operations, spotting anomalies, optimising dispatch, and security tasks. Their role in AI for grid security is expanding rapidly. At the same time, there are still questions about the risks of operating these models, how easily they could be threatened, and their overall effect on the system if they were to be used in the Distributed Energy Resources (DER) ecosystem. The literature points out this issue of research gap in terms of treating LLMs as partners in defence and at the same time, as new attack vectors. This gap is especially evident when considering LLM cyber defense smart grid strategies.
PhD-Level Verification
AI–critical infrastructure security is an up-and-coming research area that is getting a lot of attention. This topic is exactly what academic, industrial, and policymakers want and is, therefore, really good for a future-proof PhD.
Research Questions
In what ways can large language models (LLMs) enhance the cybersecurity monitoring, detection and decision-making processes, specifically in decentralised energy resources (DER)? When LLMs are incorporated into DER or grid operations, what additional cyber risks come up? How will high-DER systems’ cybersecurity architectures be changing with LLM-based agents’ integration?
PhD-Level Contributions
Frameworks for the risk-free application of LLM in DER/critical infrastructure. A classification of LLM-induced threats in power systems. AI-enabled, dynamic cybersecurity models for DER. This discussion presents both a theoretical and practical impact and, in addition, is in line with worldwide research priorities.
Suggested Readings
  • Fakih, M., Dharmaji, R., Moghaddas, Y., Quiros, G., Ogundare, O., & Al Faruque, M. A. (2024, April). Llm4plc: Harnessing large language models for verifiable programming of PLCs in industrial control systems.
  • Carlini, N., Nasr, M., Choquette-Choo, C. A., Jagielski, M., Gao, I., Koh, P. W. W., … & Schmidt, L. (2023). Are aligned neural networks adversarially aligned?. Advances in Neural Information Processing Systems, 36, 61478-61500.

Conclusion

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