All Outputs (8)

Logical circuits in colloids (2024)
Journal Article
Roberts, N., Raeisi Kheirabadi, N., Tsompanas, M. A., Chiolerio, A., Crepaldi, M., & Adamatzky, A. (2024). Logical circuits in colloids. Royal Society Open Science, 11(5), Article 231939. https://doi.org/10.1098/rsos.231939

Colloid-based computing devices offer remarkable fault tolerance and adaptability to varying environmental conditions due to their amorphous structure. An intriguing observation is that a colloidal suspension of ZnO nanoparticles in dimethylsulfoxide... Read More about Logical circuits in colloids.

Vulnerability detection through machine learning-based fuzzing: A systematic review (2024)
Journal Article
Bamohabbat Chafjiri, S., Legg, P., Hong, J., & Tsompanas, M. A. (2024). Vulnerability detection through machine learning-based fuzzing: A systematic review. Computers and Security, 143, Article 103903. https://doi.org/10.1016/j.cose.2024.103903

Modern software and networks underpin our digital society, yet the rapid growth of vulnerabilities that are uncovered within these threaten our cyber security posture. Addressing these issues at scale requires automated proactive approaches that can... Read More about Vulnerability detection through machine learning-based fuzzing: A systematic review.

Outline of an evolutionary morphology generator towards the modular design of a biohybrid catheter (2024)
Journal Article
Tsompanas, M. A., & Balaz, I. (2024). Outline of an evolutionary morphology generator towards the modular design of a biohybrid catheter. Frontiers in Robotics and AI, 11, Article 1337722. https://doi.org/10.3389/frobt.2024.1337722

Biohybrid machines (BHMs) are an amalgam of actuators composed of living cells with synthetic materials. They are engineered in order to improve autonomy, adaptability and energy efficiency beyond what conventional robots can offer. However, designin... Read More about Outline of an evolutionary morphology generator towards the modular design of a biohybrid catheter.

Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators (2024)
Conference Proceeding
Tsompanas, M. A. (2024). Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators. In Applications of Evolutionary Computation (275-289). https://doi.org/10.1007/978-3-031-56855-8_17

One of the training methods of Artificial Neural Networks is Neuroevolution (NE) or the application of Evolutionary Optimization on the architecture and weights of networks to fit the target behaviour. In order to provide competitive results, three k... Read More about Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators.

Improving search space analysis of fuzzing mutators using cryptographic structures (2023)
Conference Proceeding
Chafjiri, S. B., Legg, P., Tsompanas, M., & Hong, J. (in press). Improving search space analysis of fuzzing mutators using cryptographic structures. In Lecture Notes in Network Security

This paper introduces a novel approach to enhance the performance of software fuzzing mutator tools, by leveraging cryptographic structures known as substitution-permutation networks and Feistel networks. By integrating these structures into the exis... Read More about Improving search space analysis of fuzzing mutators using cryptographic structures.

Chemically-inspired memristor-based neuron-like oscillating circuit (2022)
Conference Proceeding
Chatzinikolaou, T. P., Fyrigos, I. A., Tsioustas, C., Bousoulas, P., Tsompanas, M. A., Tsoukalas, D., & Sirakoulis, G. C. (2022). Chemically-inspired memristor-based neuron-like oscillating circuit. In 2022 Panhellenic Conference on Electronics & Telecommunications (PACET). https://doi.org/10.1109/PACET56979.2022.9976319

There is a constant push for ever increasing performance in traditional computing systems, leading to high power consumption and, in the end, to the incapacity of conventional electronics to handle heavy computing tasks, which usually require learnin... Read More about Chemically-inspired memristor-based neuron-like oscillating circuit.

Unconventional logic on unipolar CBRAM based oscillators (2022)
Conference Proceeding
Chatzinikolaou, T. P., Fyrigos, I. A., Kitsios, S., Bousoulas, P., Tsompanas, M. A., Tsoukalas, D., & Sirakoulis, G. C. (2022). Unconventional logic on unipolar CBRAM based oscillators. In 2022 IEEE 22nd International Conference on Nanotechnology (NANO) (539-542). https://doi.org/10.1109/NANO54668.2022.9928664

Plenty of unconventional computing techniques aim to compete with, if not outperform, traditional computers in solving high-complexity problems. The classical von Neumann computing architecture depends on centralized and sequential data processing, w... Read More about Unconventional logic on unipolar CBRAM based oscillators.

Material design strategies for emulating neuromorphic functionalities with resistive switching memories (2022)
Journal Article
Bousoulas, P., Kitsios, S., Chatzinikolaou, T. P., Fyrigos, I. A., Ntinas, V., Tsompanas, M. A., …Tsoukalas, D. (2022). Material design strategies for emulating neuromorphic functionalities with resistive switching memories. Japanese Journal of Applied Physics, 61(SM), Article SM0806. https://doi.org/10.35848/1347-4065/ac7774

Nowadays, the huge power consumption and the inability of the conventional circuits to deal with real-time classification tasks have necessitated the devising of new electronic devices with inherent neuromorphic functionalities. Resistive switching m... Read More about Material design strategies for emulating neuromorphic functionalities with resistive switching memories.