Refereed article in conference proceedings (A4)

Conceptual Security System Design for Mobile Platforms Based on Human Nervous System




List of Authors: Nanda Kumar Thanigaivelan, Ethiopia Nigussie, Seppo Virtanen, Jouni Isoaho

Conference name: International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

Publisher: Springer Verlag

Publication year: 2019

Journal: International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

Book title *: Innovative Mobile and Internet Services in Ubiquitous Computing: Proceedings of the 13th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS-2019)

Title of series: Advances in Intelligent Systems and Computing

Volume number: 994

ISBN: 978-3-030-22262-8

eISBN: 978-3-030-22263-5

ISSN: 2194-5357

DOI: http://dx.doi.org/10.1007/978-3-030-22263-5_42

URL: https://link.springer.com/chapter/10.1007/978-3-030-22263-5_42

Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/41800353


Abstract

We present the conceptual security system design for mobile platform based on the human nervous system in order to achieve security resilience against threats. The reason for imitation of the human nervous system is to achieve distributed decision making and instinctive reaction against threats by observing the entire device activities. The system is adapted to have the functionalities of the nervous system through the creation of event detection and controlling mechanisms. The two main subsystems, brain and spinal cord, are created through sharing of security related operations in order to act independently without contradicting each other‘s decisions. The brain comprises of modules that handles the incidents and learning of behaviours to realise holistic view of security against ongoing activities. The spinal cord is responsible for spawning receptor and effector pairs against application activities to establish a medium to communicate and exercise control over them. Some of the factors that influence the method of implementation are usability, acceptability and the type of learning algorithms.


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Last updated on 2022-07-04 at 17:27