I design and analyse security protocols for systems where trust is scarce, mobility is high, and delay budgets are unforgiving. My current research sits around AI-based provably secure authentication, post-quantum cryptography, federated learning, and privacy-preserving security for Smart Grid, V2G, IoT, and Industrial Cyber-Physical Systems.
My work is motivated by a fairly practical question: how can a small device prove the right thing, at the right time, without leaking more than it should?
- PhD Candidate, School of Computer Science and Electronic Engineering, University of Essex, United Kingdom.
- Research focus: AI-based provably secure and cost-effective authentication protocols for demand response power management in the Vehicle-to-Intelligent-Grid paradigm.
- Core domains: Smart Grid, Vehicle-to-Grid communication, high-mobility IoT, Industrial CPS, VANETs, wireless sensor networks, and edge-assisted security.
- Cryptographic lens: ECC, signcryption, zero-knowledge authentication, PUFs, threshold cryptography, post-quantum primitives, and formal security reductions.
- AI security lens: reinforcement learning, federated learning, predictive token learning, adversarial robustness, and intrusion detection.
I tend to start from simple protocol logic first, then push it toward a formal model. A useful sketch is:
and, for an authentication experiment with security parameter \lambda:
That inequality is not decoration. It is the basic research habit: name the adversary, name the assumption, and make the cost visible.
These threads describe the direction of my recent work and the code I am actively shaping into reproducible research artifacts.
| Thread | What I am studying | Representative work |
|---|---|---|
| Zero-knowledge mobility authentication | Compact proofs for high-speed IoT and V2G roaming without exposing long-term identity or movement patterns. | AI-enhanced ZK authentication |
| Post-quantum V2G security | Authentication and federated trust under quantum-capable adversarial models. | PQ-V2G |
| Federated learning security | Byzantine-resilient aggregation, trust scoring, and adaptive defence under poisoning attacks. | tars-fl-sim |
| AI-assisted vehicle security | Intrusion detection and authentication for autonomous and connected vehicle environments. | AIDAS implementation |
| Secure cyber-physical energy systems | Blockchain, access control, and AI-supported authentication for multi-domain V2G networks. | lqap_project |
| UAV and command security | Authenticated command pipelines for UAV and high-mobility environments, including LLM-facing control interfaces. | uav-llm-command |
The list below is deliberately short. For the complete and live scholarly record, please use Google Scholar or DBLP.
- S. Ahmed and M. H. Anisi, "AI-Enhanced Zero-Knowledge Authentication for High-Mobility IoT Using Predictive Token Learning," IEEE Internet of Things Journal, vol. 13, no. 5, pp. 9068-9077, 2026. DOI
- S. Ahmed and M. H. Anisi, "A Post-Quantum Secure Federated Learning Framework for Cross-Domain V2G Authentication," IEEE Transactions on Consumer Electronics, vol. 71, no. 3, pp. 8433-8440, 2025. DOI
- S. Ahmed and M. H. Anisi, "AIDAS: AI-Enhanced Intrusion Detection and Authentication for Autonomous Vehicles," IEEE Transactions on Intelligent Transportation Systems, vol. 26, no. 8, pp. 12548-12557, 2025. DOI
- S. Ahmed and M. H. Anisi, "Optimizing V2G Dynamics: An AI-Enhanced Secure Protocol for Energy Management in Industrial Cyber-Physical Systems," IEEE Transactions on Industrial Cyber-Physical Systems, vol. 2, pp. 312-320, 2024. DOI
- S. Ahmed et al., "Signcryption Based Authenticated and Key Exchange Protocol for EI-Based V2G Environment," IEEE Transactions on Smart Grid, vol. 12, no. 6, pp. 5290-5298, 2021. DOI
- S. Ahmed et al., "Anonymous Key-Agreement Protocol for V2G Environment Within Social Internet of Vehicles," IEEE Access, vol. 8, pp. 119829-119839, 2020. DOI
I use tools that let me move between proof, simulation, and implementation without pretending those are separate worlds.
Formal verification and protocol analysis
ProVerif, AVISPA, Scyther, Tamarin, Random Oracle Model analysis, informal attack modelling.
Cryptography and security
ECC, signcryption, key agreement, zero-knowledge proofs, PUFs, Kyber, Dilithium, XMSS, threshold cryptography, privacy-preserving authentication.
AI and systems
Python, C, C++, Java, JavaScript, MATLAB, federated learning, reinforcement learning, intrusion detection, blockchain access control.
Writing and research workflow
LaTeX, Git, GitHub, VS Code, reproducible experiments, paper-to-code translation.
These repositories show the research shift in my GitHub profile from teaching and application development toward security protocol research.
| Repository | Focus |
|---|---|
| AI-Enhanced-Zero-Knowledge-Authentication-for-High-Mobility-IoT-Using-Predictive-Token-Learning | Zero-knowledge authentication, predictive token learning, high-mobility IoT |
| PQ-V2G | Post-quantum identity, privacy, and resilience for V2G communication |
| AIDAS-Implementation | AI-enhanced intrusion detection and authentication for autonomous vehicles |
| tars-fl-sim | Trust-aware reinforcement selection for secure federated learning |
| lqap_project | Blockchain-based federated learning architecture for secure multi-domain V2G |
| NSRG | Network Security Research Group code and experiments |
Numbers are useful, but they are only a partial signal. I care more about whether a repository makes a claim reproducible.
I am interested in research collaborations where the goal is clear: design a protocol, prove what it claims, and test whether it survives the limits of real systems.
- Secure authentication for Smart Grid, V2G, IoT, UAV, and cyber-physical systems.
- Post-quantum and zero-knowledge protocol design.
- Federated learning security under non-IID data and adaptive adversaries.
- AI-assisted security mechanisms that remain auditable rather than mysterious.
For research contact, email me at csshafiqahmed@gmail.com.