Identity theft on e-government/e-governance digital forensics
Title | Identity theft on e-government/e-governance digital forensics |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Al-Nemrat, Ameer |
Conference Name | 2018 International Symposium on Programming and Systems (ISPS) |
Date Published | April 2018 |
Publisher | IEEE |
ISBN Number | 978-1-5386-4690-8 |
Keywords | blockchain technology, Collaboration, Computer crime, corporate users, credit card fraud, credit card transactions, Credit cards, credit transactions, cyber-threats, Cybercrime, cybersecurity, cyberspace-low entry barriers, digital forensics, E-Governance, E-Government, electronic commerce, Electronic government, financial fraud, fraud, fraudulent transactions, genetic algorithms, Government, government data processing, governments, identity theft, Internet, Law, malicious online activity, Neural networks, policy-based governance, product reviews, pubcrawl, resilience, Resiliency, system intrusions, time 13.0 month, user anonymity |
Abstract | In the context of the rapid technological progress, the cyber-threats become a serious challenge that requires immediate and continuous action. As cybercrime poses a permanent and increasing threat, governments, corporate and individual users of the cyber-space are constantly struggling to ensure an acceptable level of security over their assets. Maliciousness on the cyber-space spans identity theft, fraud, and system intrusions. This is due to the benefits of cyberspace-low entry barriers, user anonymity, and spatial and temporal separation between users, make it a fertile field for deception and fraud. Numerous, supervised and unsupervised, techniques have been proposed and used to identify fraudulent transactions and activities that deviate from regular patterns of behaviour. For instance, neural networks and genetic algorithms were used to detect credit card fraud in a dataset covering 13 months and 50 million credit card transactions. Unsupervised methods, such as clustering analysis, have been used to identify financial fraud or to filter fake online product reviews and ratings on e-commerce websites. Blockchain technology has demonstrated its feasibility and relevance in e-commerce. Its use is now being extended to new areas, related to electronic government. The technology appears to be the most appropriate in areas that require storage and processing of large amounts of protected data. The question is what can blockchain technology do and not do to fight malicious online activity? |
URL | https://ieeexplore.ieee.org/document/8378961/ |
DOI | 10.1109/ISPS.2018.8378961 |
Citation Key | al-nemrat_identity_2018 |
- Neural networks
- fraudulent transactions
- genetic algorithms
- Government
- government data processing
- governments
- identity theft
- internet
- Law
- malicious online activity
- fraud
- policy-based governance
- product reviews
- pubcrawl
- resilience
- Resiliency
- system intrusions
- time 13.0 month
- user anonymity
- Cybercrime
- collaboration
- Computer crime
- corporate users
- credit card fraud
- credit card transactions
- Credit cards
- credit transactions
- cyber-threats
- blockchain technology
- Cybersecurity
- cyberspace-low entry barriers
- Digital Forensics
- E-Governance
- E-Government
- electronic commerce
- Electronic government
- financial fraud