Mitigating Cyber Attack With Ai Driven Identity And Access Management In Modern Networks

Authors

Ranga Premsai

Abstract

In the realm of financial transactions, ensuring the security and integrity of sensitive data is of paramount importance. The rapid digitization of financial services has led to an increased risk of malicious attacks, including data breaches, fraud, and unauthorized access. Detecting and mitigating these attacks in real time is a critical challenge. This paper introduces a comprehensive Identity and Access Control (IAC) framework designed to safeguard financial data in the context of online transactions. The framework combines mutual authentication, secure communication protocols, and advanced data analysis techniques to create a robust defense against malicious activities. In this proposed solution, two entities—typically a user and a financial institution—first authenticate each other to establish a secure communication channel. This mutual authentication serves as the foundation for exchanging a secret key used to encrypt and decrypt sensitive financial data. The process of securely processing transaction data occurs at nearby cloud servers, ensuring that sensitive financial information is never exposed during transmission or processing. To enhance security, the Double Twist Encryption Standard (DTES) is employed to encrypt financial data. DTES is a hybrid encryption mechanism that strengthens data confidentiality by employing two encryption rounds with alternating encryption schemes, ensuring that the encrypted data is resistant to various forms of cryptanalysis. This added layer of encryption provides robust protection against unauthorized data access, ensuring that sensitive financial data is securely stored by the financial organization. Simultaneously, the Trust Cyber Ant Identity and Access Mechanism is utilized to assess the legitimacy of users accessing financial services. This mechanism evaluates the user's trustworthiness based on their interaction history, behavior patterns, and other relevant factors, allowing only authorized users with sufficient trust levels to access real-time financial data. The Access Control mechanism enforces these trust policies, ensuring that only verified users can perform transactions or retrieve sensitive data. Moreover, malicious attack detection and mitigation are achieved through the Proof Traverse Parse Tree (PTPT) Algorithm, which analyzestransaction data for signs of anomalies and malicious activity. The PTPT algorithm builds a parse tree of transaction data and traverses it to identify suspicious patterns. If malicious or inconsistent data is detected, the system "drops out" or rejects the data, preventing attacks such as fraudulent transactions, data manipulation, or unauthorized access. By combining these mechanisms—mutual authentication, DTES encryption, the Trust Cyber Ant Identity and Access Mechanism, and the PTPT algorithm—this paper provides a comprehensive solution to enhance the security, integrity, and trustworthiness of financial transactions. The proposed framework effectively detects and mitigates malicious activities, ensuring secure processing and storage of financial data while maintaining real-time access for authorized users

Keywords

Identity and Access Control, Double Twist Encryption Standard, Trust Cyber Ant Identity and Access Mechanism, Proof Traverse Parse Tree

Mitigating Cyber Attack With Ai Driven Identity And Access Management In Modern Networks. Ranga Premsai. 2022. IJIRCT, Volume 8, Issue 3. Pages 1-12. https://www.ijirct.org/viewPaper.php?paperId=2412004