Problem statement
The proliferation of fraudulent apps on both the Apple Store and PlayStore
poses a significant threat to users’ smartphones. Malicious apps not only disrupt the
normal functioning of phones but also compromise sensitive data, leading to potential
privacy breaches and financial losses. Traditional app stores struggle to keep up with the
evolving techniques used by fraudsters, making it imperative to enhance fraud app
detection software for 2024.
Abstract
In the dynamic landscape of mobile applications, the need for robust fraud
app detection software has never been more crucial. The current scenario sees a surge
in fraudulent apps, exploiting vulnerabilities to compromise user data and device
integrity. The challenge lies in developing an advanced solution that can preemptively
identify and mitigate the risks posed by these malicious applications.
Outcome
Behavioral Analysis:
Employ real-time algorithms to scrutinize app behavior.
ML and AI Integration:
Utilize machine learning to continuously enhance detection accuracy.
Reputation Scanning:
Implement a comprehensive system analyzing developer history and user reviews.
Security Audits:
Conduct regular infrastructure audits to patch vulnerabilities.
User Education:
Empower users to report and identify suspicious apps. The enhanced fraud app detection software for 2024 will result in a safer and more secure mobile app ecosystem. Users can confidently explore and download applications, knowing that the advanced detection mechanisms are actively safeguarding their
devices and sensitive data. This solution aims to significantly reduce the risk of fraudulent apps, providing a seamless and secure app experience for users worldwide.
Reference
Fraud detection applications become an important part for companies, banks are one of the companies that have confidential data assets that need to be protected because they contain financial information. In the digital era, the use of mobile banking is a utility function for the need to perform daily financial activities such as bill payment and fund transfer. Addressing potential fraud in mobile banking services is a challenge for banks to make IT security systems remain confident, integrity, and available. Potential attacks on IT security will occur from the internal side of the organization as well as from external parties. In maintaining the level of security and convenience of customers in using e-banking services, banks try to make a tool to be able to prevent the occurrence of a large risk of loss in future. The most potential that will become an attack is social engineering and data theft by internal employees, in this research the focus is to discuss the two potential attacks on accounts that have long been dormant and deal with them with an application with the SOA approach.
- A. Bănărescu, “Detecting and Preventing Fraud with Data Analytics,” Procedia Economics and Finance, vol. 32, no. 15, pp. 1827-1836, 2015, [online] Available: https://doi.org/10.1016/s2212-5671(15)01485-9.
- S. H. Li, D. C. Yen, W. H. Lu and C. Wang, “Identifying the signs of fraudulent accounts using data mining techniques,” Computers in Human Behavior, vol. 28, no. 3, pp. 1002-1013, 2012, [online] Available: https://doi.org/10.1016/j.chb.2012.01.002.
- Internal Fraud – The Threat from Within Contents, London, 2014.
https://ieeexplore.ieee.org/document/8969848/