City Research Online

Bio/Nature-inspired algorithms in A.I. for malicious activity detection

Komninos, N. ORCID: 0000-0003-2776-1283 and Procopiou, A. (2019). Bio/Nature-inspired algorithms in A.I. for malicious activity detection. In: El-Alfy, E-S. M., Elroweissy, M., Fulp, E. W. and Mazurczyk, W. (Eds.), Nature-Inspired Cyber Security and Resiliency: Fundamentals, techniques and applications. . IET. ISBN 978-1-78561-638-9

Publication Type: Book Section
Additional Information: This is the submitted version of an chapter published by the Institution fof Engineering and Technology. The version of record is to be available at https://www.theiet.org/resources/books/security/nature-cyb-secur.cfm.
Publisher Keywords: computer network security; Internet of Things; biomimetics; computer crime; invasive software; learning algorithms; malicious software; Internet of Things; bio-inspired algorithm detection; IoT; intrusion detection; bio-inspired techniques; DDoS
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
URI: http://openaccess.city.ac.uk/id/eprint/21105
[img]
Preview
Text - Submitted Version
Download (485kB) | Preview

Export

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login