International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
•
Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
Home
Research Paper
Submit Research Paper
Publication Guidelines
Publication Charges
Upload Documents
Track Status / Pay Fees / Download Publication Certi.
Editors & Reviewers
View All
Join as a Reviewer
Reviewer Referral Program
Get Membership Certificate
Current Issue
Publication Archive
Conference
Publishing Conf. with IJFMR
Upcoming Conference(s) ↓
WSMCDD-2025
GSMCDD-2025
Conferences Published ↓
RBS:RH-COVID-19 (2023)
ICMRS'23
PIPRDA-2023
Contact Us
Plagiarism is checked by the leading plagiarism checker
Call for Paper
Volume 6 Issue 6
November-December 2024
Indexing Partners
Securing Automated Intelligence: Challenges and Solutions in RPA and Generative AI Integration
Author(s) | Saranya Balaguru |
---|---|
Country | United States |
Abstract | Integrating Robotic Process Automation (RPA) and Generative AI can revolutionize business processes, enabling greater efficiency, scalability, and intelligent decision-making. However, this powerful combination also introduces various security challenges and impacts to governance that organizations must address to protect sensitive data and maintain trust in automation systems. As RPA bots increasingly interact with AI models, vulnerabilities such as unauthorized data access, malicious model manipulation, and improper handling of sensitive information become more pronounced. These risks can lead to cyberattacks, data breaches, and regulatory compliance violations. This paper examines the security challenges inherent in RPA and Generative AI integration, focusing on three key areas: data privacy, model integrity, and automation governance. We assess how improper configurations and lack of security oversight can expose these systems to exploitation. Furthermore, we explore solutions such as implementing robust encryption protocols, secure data access controls, and continuous monitoring of AI model behavior to detect anomalies. By presenting case studies and evaluating emerging best practices, we offer a framework for safeguarding RPA and AI systems, ensuring that automation remains a trusted and secure tool for organizations. The paper also discusses aligning security strategies with regulatory requirements and industry standards. This approach enables organizations to unlock the full potential of RPA and Generative AI while mitigating risks and protecting against evolving cyber threats. |
Keywords | Access Control, AI Integration, Automation Governance, Compliance, Cybersecurity, Data Privacy, Encryption, Generative AI, Model Integrity, Risk Mitigation, RPA, Security |
Field | Computer > Automation / Robotics |
Published In | Volume 6, Issue 5, September-October 2024 |
Published On | 2024-09-26 |
Cite This | Securing Automated Intelligence: Challenges and Solutions in RPA and Generative AI Integration - Saranya Balaguru - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27900 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i05.27900 |
Short DOI | https://doi.org/g59zvz |
Share this
E-ISSN 2582-2160
doi
CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
10.36948/ijfmr
Downloads
All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.