Publication: Forensic Analysis on False Data Injection Attack on IoT Environment
No Thumbnail Available
Date
2021
Authors
Nizam S.A.S.
Ibrahim Z.-A.
Rahim F.A.
Fadzil H.S.
Mohd Abdullah H.I.
Mustaffa M.Z.
Journal Title
Journal ISSN
Volume Title
Publisher
Science and Information Organization
Abstract
False Data Injection Attack (FDIA) is an attack that could compromise Advanced Metering Infrastructure (AMI) devices where an attacker may mislead real power consumption by falsifying meter usage from end-users smart meters. Due to the rapid development of the Internet, cyber attackers are keen on exploiting domains such as finance, metering system, defense, healthcare, governance, etc. Securing IoT networks such as the electric power grid or water supply systems has emerged as a national and global priority because of many vulnerabilities found in this area and the impact of the attack through the internet of things (IoT) components. In this modern era, it is a compulsion for better awareness and improved methods to counter such attacks in these domains. This paper aims to study the impact of FDIA in AMI by performing data analysis from network traffic logs to identify digital forensic traces. An AMI testbed was designed and developed to produce the FDIA logs. Experimental results show that forensic traces can be found from the evidence logs collected through forensic analysis are sufficient to confirm the attack. Moreover, this study has produced a table of attributes for evidence collection when performing forensic investigation on FDIA in the AMI environment. � 2021
Description
Advanced metering infrastructures; Digital forensics; Electric power system security; Electric power transmission networks; Network security; Water supply; Water supply systems; Cyber attackers; Electric power grids; Evidence collection; False data injection attacks; Forensic analysis; Forensic investigation; Internet of thing (IOT); Metering systems; Internet of things