Developing an Optimal Strategy to Address the Vulnerability of Image Tampering

Abstract

Image tampering is a growing concern in numerous fields, necessitating robust solutions. This study investigates the creation of an optimal strategy to resolve the vulnerability of image tampering (manipulation). Beginning with a survey of contemporary alteration detection techniques, their strengths and limitations in identifying manipulated image regions are evaluated. The complexity of both global and local manipulation is highlighted, highlighting the need for multifaceted analysis. Combining conventional image forensics techniques with advanced machine learning algorithms, the devised strategy forms a comprehensive framework. This synthesis seeks to produce a robust and adaptable method capable of detecting corruption even in the presence of sophisticated manipulation techniques. The significance of a diverse training dataset is highlighted, lending credibility to the evaluation of the strategy. Real-world interference scenarios and diverse image formats enhance its dependability and generalization capabilities. Ethical considerations are interwoven to ensure a balanced approach that protects both the privacy rights of individuals and the authenticity of images. The paper concludes with empirical evidence demonstrating the effectiveness of the proposed strategy. Comparisons with extant techniques highlight its prowess, revealing improvements in precision, efficiency, and resiliency. The road ahead entails continuous improvement via learning mechanisms and adaptation to oppose emergent tampering methods. This research represents a significant advance in the field of image forensics. It strengthens digital image security, authenticity, and trustworthiness by presenting the optimal strategy. In turn, this enables more informed decision-making across various sectors, paving the way for a more reliable digital landscape.

Country : Sri Lanka

1 Isuranga Nipun Kumara2 Umal Anuraga Nanumura3 Theneth Sanjuka4 Kanishka Yapa

  1. Cybersecurity Researcher, Department of Computer Systems Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  2. Cybersecurity Researcher, Department of Computer Engineering, University of South Wales, South Wales, United Kingdom
  3. Cybersecurity Undergraduate, Department of Computer Systems Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
  4. Lecturer, Department of Computer Systems Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka

IRJIET, Volume 7, Issue 11, November 2023 pp. 511-519

doi.org/10.47001/IRJIET/2023.711067

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