no code implementations • 17 Sep 2023 • Petar Radanliev, David De Roure, Omar Santos
In the contemporary digital age, Quantum Computing and Artificial Intelligence (AI) convergence is reshaping the cyber landscape, introducing unprecedented opportunities and potential vulnerabilities. This research, conducted over five years, delves into the cybersecurity implications of this convergence, with a particular focus on AI/Natural Language Processing (NLP) models and quantum cryptographic protocols, notably the BB84 method and specific NIST-approved algorithms.
no code implementations • 19 May 2020 • Petar Radanliev, David De Roure, Kevin Page, Max Van Kleek, Omar Santos, La Treall Maddox, Pete Burnap, Eirini Anthi, Carsten Maple
This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real time intelligence in edge computing.