Litcius/Paper detail

Image steganography technique based on bald eagle search optimal pixel selection with chaotic encryption

Adel A. Bahaddad, Khalid Ali Almarhabi, S. Abdel‐Khalek

2023Alexandria Engineering Journal24 citationsDOIOpen Access PDF

Abstract

In the digital era, information security becomes a challenging process that can be mitigated by the utilization of cryptography and steganography techniques. Earlier studies on steganography have the risk of exposing confidential data by an anonymous user. For resolving, the limitations related to the existing algorithms, one of the efficient solutions in encryption-based steganography. Encryption techniques act as an important part in protect actual data from illegal access. This study focuses on the design of Bald Eagle Search Optimal Pixel Selection with Chaotic Encryption (BESOPS-CE) based image steganography technique. The presented BESOPS-CE technique effectively hides the secret image in its encrypted version to the cover image. For accomplishing this, the BESOPS-CE technique employs a BES for optimal pixel selection (OPS) procedure. Besides, chaotic encryption was executed for encrypting the secret image, which is then embedded to choose pixel points of the cover image. Finally, embedding and extraction processes are carried out. The inclusion of the encryption process aids in accomplishing an added layer of security. A comprehensive simulation study was used to report on the BESOPS-CE approach's increased performance, and the results are examined from many angles. A thorough comparative analysis revealed that the BESOPS-CE model outperformed more contemporary methods.

Topics & Concepts

EncryptionSteganographyComputer scienceCryptographySteganography toolsCover (algebra)PixelCHAOS (operating system)ChaoticData miningSelection (genetic algorithm)Theoretical computer scienceEmbeddingComputer securityArtificial intelligenceEngineeringMechanical engineeringAdvanced Steganography and Watermarking TechniquesChaos-based Image/Signal EncryptionDigital Media Forensic Detection