ENHANCING INFORMATION SECURITY IN MULTIMEDIA STREAMS THROUGH LOGIC LEARNING MACHINE ASSISTED MOTH-FLAME OPTIMIZATION

ICTACT Journal on Communication Technology ( Volume: 14 , Issue: 3 )

Abstract

Enhancing information security in multimedia streams is a critical endeavor in the digital age, where data breaches and cyber threats loom large. This research proposes a novel approach by integrating Logic Learning Machines (LLMs) with Moth-Flame Optimization (MFO) to fortify the defenses of multimedia data against potential vulnerabilities. Logic Learning Machines, known for their ability to make decisions based on logical reasoning, form the foundational intelligence of our proposed system. Leveraging their capacity to process complex patterns and relationships within data, LLMs become the cognitive backbone of our security enhancement model. Moth-Flame Optimization, inspired by the navigational behavior of moths around artificial lights, serves as the optimization engine in this framework. MFO mimics the natural attraction of moths to flames, translating it into an algorithmic strategy to optimize parameters and configurations for heightened security measures. By applying MFO, the system dynamically adapts and refines its security protocols in response to evolving threats. The synergy between LLMs and MFO creates a resilient defense mechanism for multimedia streams. The logic-driven decision-making of LLMs is augmented by the adaptive optimization capabilities of MFO, resulting in a robust and dynamic security infrastructure. This fusion not only enhances the detection of potential threats but also enables proactive adjustments to security parameters, thereby fortifying the system against emerging risks. The proposed framework is validated through extensive simulations and experiments, demonstrating its efficacy in real-world scenarios. The outcomes showcase improved information security for multimedia streams, providing a versatile solution for safeguarding sensitive data in diverse digital environments.

Authors

Bhushankumar Nemade1, Sujata S. Alegavi2, Namdeo Baban Badhe3, Aaditya Desai4
Mukesh Patel School of Technology Management and Engineering, India1, Thakur College of Engineering and Technology, India2, Thakur College of Engineering and Technology, India3, Welingkars Institute of Management and Research, India4

Keywords

Logic Learning Machines, Moth-Flame Optimization, Multimedia Security, Adaptive Defense, Cyber Threats

Published By
ICTACT
Published In
ICTACT Journal on Communication Technology
( Volume: 14 , Issue: 3 )
Date of Publication
September 2023
Pages
3019 - 3023

ICT Academy is an initiative of the Government of India in collaboration with the state Governments and Industries. ICT Academy is a not-for-profit society, the first of its kind pioneer venture under the Public-Private-Partnership (PPP) model

Contact Us

ICT Academy
Module No E6 -03, 6th floor Block - E
IIT Madras Research Park
Kanagam Road, Taramani,
Chennai 600 113,
Tamil Nadu, India

For Journal Subscription: journalsales@ictacademy.in

For further Queries and Assistance, write to us at: ictacademy.journal@ictacademy.in