- author = "Hasanen Alyasiri and John A Clark and Ali Malik and Ruairi {de Frein}",
- title = "Grammatical Evolution for Detecting Cyberattacks in Internet of Things Environments",
- booktitle = "2021 International Conference on Computer Communications and Networks (ICCCN)",
- year = "2021",
- address = "Athens, Greece",
- month = "19-22 " # jul,
- organization = "IEEE",
- keywords = "genetic algorithms, genetic programming, Grammatical Evolution",
- isbn13 = "978-1-6654-4835-2",
-
URL = "
https://ieeexplore.ieee.org/abstract/document/9522283",
-
DOI = "
doi:10.1109/ICCCN52240.2021.9522283",
- abstract = "The Internet of Things (IoT) is revolutionising nearly every aspect of modern life, playing an ever greater role in both industrial and domestic sectors. The increasing frequency of cyber-incidents is a consequence of the pervasiveness of IoT. Threats are becoming more sophisticated, with attackers using new attacks or modifying existing ones. Security teams must deal with a diverse and complex threat landscape that is constantly evolving. Traditional security solutions cannot protect such systems adequately and so researchers have begun to use Machine Learning algorithms to discover effective defense systems. we investigate how one approach from the domain of evolutionary computation, grammatical evolution, can be used to identify cyberattacks in IoT environments. The experiments were conducted on up-to-date datasets and compared with state-of-the-art algorithms. The potential application of evolutionary computation-based approaches to detect unknown attacks is also examined and discussed.",
-
notes = "Also known as \cite{9522283}
University of Kufa, Iraq",
