Cyber Defense in the Age of Artificial Intelligence and Machine Learning for Financial Fraud Detection Application
نویسندگان
چکیده
Cyber security comes with a combination of various policies, AI techniques, network technologies that work together to protect computing resources like networks, intelligent programs, and sensitive data from attacks. Nowadays, the shift digital freedom had led opened many new challenges for financial services. Cybercriminals have found ability leverage e- currency exchanges other transactions perform their fraudulent activities. The unregulated channel makes it essential banks institutions deploy advanced & ML (DL) techniques fight cybercrime. This can be implemented by deploying techniques. Customers are experiencing an increase in fraud-hit rate banking operations. It is difficult defend against dynamic cyber-attacks using conventional non- algorithms. Therefore, machine learning has been set up cyber build models malware categorization intelligently sensing fraught danger. paper introduces defense mechanism artificial intelligence (AI), (ML)) current Feedzai model identifying transaction. We given preface popular random forest algorithm Feedzai’s Open fraud detection software tool, which provides automatic fraud-recognition framework solving Financial Fraud Detection.
منابع مشابه
A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements
Financial statement fraud has increasingly become a serious problem for business, government, and investors. In fact, this threatens the reliability of capital markets, corporate heads, and even the audit profession. Auditors in particular face their apparent inability to detect large-scale fraud, and there are various ways to identify this problem. In order to identify this problem, the majori...
متن کاملFinancial Accounting Fraud Detection Using Business Intelligence
The paper investigates the inherent problems of financial fraud detection and proposes a forensic accounting framework using business intelligence as a plausible means of addressing them. The paper adopts an empirical case study approach to present how business intelligence could be used effectively in the detection of financial accounting fraud. The proposed forensic accounting framework using...
متن کاملUsing Machine Learning Algorithms for Automatic Cyber Bullying Detection in Arabic Social Media
Social media allows people interact to express their thoughts or feelings about different subjects. However, some of users may write offensive twits to other via social media which known as cyber bullying. Successful prevention depends on automatically detecting malicious messages. Automatic detection of bullying in the text of social media by analyzing the text "twits" via one of the machine l...
متن کاملBypass Fraud Detection: Artificial Intelligence Approach
Telecom companies are severely damaged by bypass fraud (SIMboxing). However, There is a shortage of published research to tackle this problem. The traditional method of Test Call Generators (TCG) is easily overcome by fraudsters and the need for more sophisticated ways is inevitable. In this work, we are developing intelligent algorithms that mine a huge amount of mobile operator’s data and det...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International journal of electrical & electronics research
سال: 2022
ISSN: ['2347-470X']
DOI: https://doi.org/10.37391/ijeer.100206