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Credit card fraud detection is a critical challenge in the financial sector, demanding sophisticated approaches to accurately identify fraudulent transactions. This research proposes an innovative methodology combining Neural Networks (NN)…
Large-scale online service platforms face severe challenges from organized platform abuse: multiple forms such as credit card fraud and promotion abuse continually emerge, characterized by large numbers of involved accounts, rapid…
Machine learning has opened up new tools for financial fraud detection. Using a sample of annotated transactions, a machine learning classification algorithm learns to detect frauds. With growing credit card transaction volumes and rising…
Vulnerable individuals have a limited ability to make reasonable financial decisions and choices and, thus, the level of care that is appropriate to be provided to them by financial institutions may be different from that required for other…
Financial fraud detection is an important problem with a number of design aspects to consider. Issues such as algorithm selection and performance analysis will affect the perceived ability of proposed solutions, so for auditors and…
Machine learning has automated much of financial fraud detection, notifying firms of, or even blocking, questionable transactions instantly. However, data imbalance starves traditionally trained models of the content necessary to detect…
Data Distribution Service (DDS) is an innovative approach towards communication in ICS/IoT infrastructure and robotics. Being based on the cross-platform and cross-language API to be applicable in any computerised device, it offers the…
Information security in Process-aware Information System (PAIS) relies on many factors, including security of business process and the underlying system and technologies. Moreover, humans can be the weakest link that creates pathway to…
Cashback reward programs now serve as central instruments in the competitive landscape of cards, digital wallets, and payment platforms. Despite their financial significance, the business logic governing these programs is seldom treated as…
Provenance-based Intrusion Detection Systems (PIDSes) have been widely used to detect Advanced Persistent Threats (APTs). Although many studies achieve high performance in the evaluations of their original papers, their performance in…
The increase reliance on information systems has created unprecedented challenges for organizations to protect their critical information from different security threats that have direct consequences on the corporate liability, loss of…
As institutions increasingly depend on Information Systems (ISs), ensuring compliance with Information Systems Security Policies (ISSPs) is critical, especially among contingent employees, whose engagement differs from that of permanent…
The recent decade witnessed a surge of increase in financial crimes across the public and private sectors, with an average cost of scams of $102m to financial institutions in 2022. Developing a mechanism for battling financial crimes is an…
The Department of Homeland Security in the United States estimates that 90% of software vulnerabilities can be traced back to defects in design and software coding. The financial impact of these vulnerabilities has been shown to exceed 380…
California's consumer privacy law is widely deemed to be the most protected in the United States, one of the few to expressly regulate third party entities that buy and sell consumer data (data brokers). We offer the first empirical…
The EU General Data Protection Regulation (GDPR), enforced from 25th May 2018, aims to reform how organisations view and control the personal data of private EU citizens. The scope of GDPR is somewhat unprecedented: it regulates every…
Credit card fraud remains a significant challenge due to class imbalance and fraudsters mimicking legitimate behavior. This study evaluates five machine learning models - Logistic Regression, Random Forest, XGBoost, K-Nearest Neighbors…
With the escalating threats posed by cyberattacks on Industrial Control Systems (ICSs), the development of customized Industrial Intrusion Detection Systems (IIDSs) received significant attention in research. While existing literature…
Privacy risk assessments have been touted as an objective, principled way to encourage organizations to implement privacy-by-design. They are central to a new regulatory model of collaborative governance, as embodied by the GDPR. However,…
This paper provides an overview of how crypto currency and blockchain engineering interacts with the law enforcement. We point out that a large proportion of crypto users are amateur investors and the dominant and the largest segment in…