Forensic analysis on false data injection attack on IoT environment
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 e...
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| Format: | Article |
| Language: | English |
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Science and Information Organization
2021
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| Online Access: | http://eprints.utm.my/95737/1/FizaAbdulRahim2021_ForensicAnalysisonFalseData.pdf |
| _version_ | 1796866079405899776 |
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| author | Sharul Nizam, Saiful Amin Ibrahim, Zul-Azri Abdul Rahim, Fiza Fadzil, Hafizuddin Shahril Mohd. Abdullah, Haris Iskandar Mustaffa, Muhammad Zulhusni |
| author_facet | Sharul Nizam, Saiful Amin Ibrahim, Zul-Azri Abdul Rahim, Fiza Fadzil, Hafizuddin Shahril Mohd. Abdullah, Haris Iskandar Mustaffa, Muhammad Zulhusni |
| author_sort | Sharul Nizam, Saiful Amin |
| collection | ePrints |
| description | 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. |
| first_indexed | 2024-03-05T21:06:50Z |
| format | Article |
| id | utm.eprints-95737 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T21:06:50Z |
| publishDate | 2021 |
| publisher | Science and Information Organization |
| record_format | dspace |
| spelling | utm.eprints-957372022-05-31T13:18:27Z http://eprints.utm.my/95737/ Forensic analysis on false data injection attack on IoT environment Sharul Nizam, Saiful Amin Ibrahim, Zul-Azri Abdul Rahim, Fiza Fadzil, Hafizuddin Shahril Mohd. Abdullah, Haris Iskandar Mustaffa, Muhammad Zulhusni QA75 Electronic computers. Computer science T58.5-58.64 Information technology 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. Science and Information Organization 2021-10 Article PeerReviewed application/pdf en http://eprints.utm.my/95737/1/FizaAbdulRahim2021_ForensicAnalysisonFalseData.pdf Sharul Nizam, Saiful Amin and Ibrahim, Zul-Azri and Abdul Rahim, Fiza and Fadzil, Hafizuddin Shahril and Mohd. Abdullah, Haris Iskandar and Mustaffa, Muhammad Zulhusni (2021) Forensic analysis on false data injection attack on IoT environment. International Journal of Advanced Computer Science and Applications, 12 (10). pp. 265-271. ISSN 2158-107X http://dx.doi.org/10.14569/IJACSA.2021.0121029 DOI:10.14569/IJACSA.2021.0121029 |
| spellingShingle | QA75 Electronic computers. Computer science T58.5-58.64 Information technology Sharul Nizam, Saiful Amin Ibrahim, Zul-Azri Abdul Rahim, Fiza Fadzil, Hafizuddin Shahril Mohd. Abdullah, Haris Iskandar Mustaffa, Muhammad Zulhusni Forensic analysis on false data injection attack on IoT environment |
| title | Forensic analysis on false data injection attack on IoT environment |
| title_full | Forensic analysis on false data injection attack on IoT environment |
| title_fullStr | Forensic analysis on false data injection attack on IoT environment |
| title_full_unstemmed | Forensic analysis on false data injection attack on IoT environment |
| title_short | Forensic analysis on false data injection attack on IoT environment |
| title_sort | forensic analysis on false data injection attack on iot environment |
| topic | QA75 Electronic computers. Computer science T58.5-58.64 Information technology |
| url | http://eprints.utm.my/95737/1/FizaAbdulRahim2021_ForensicAnalysisonFalseData.pdf |
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