Search Results (3)

The swift advancement of information and communication technology has made it increasingly difficult to guarantee the security of transmitted data. Traditional encryption techniques, particularly in multimedia applications, frequently fail to defend against sophisticated attacks, such as chosen-plaintext, differential, and statistical analysis attacks. More often than not, traditional cryptographic methods lack proper diffusion and sufficient randomness, which is why they are vulnerable to these types of attacks. By combining multi-level chaotic maps with Least Significant Bit (LSB) steganography and Advanced Encryption Standard (AES) encryption, this study proposes an improved security approach for picture transmission. A hybrid chaotic system dynamically creates the encryption keys, guaranteeing high unpredictability and resistance to brute-force attacks. Next, it incorporates the encrypted images into video frames, making it challenging to find the secret data. The suggested method demonstrates its resilience to statistical attacks by achieving entropy values over 7.99 and number of pixels change rate (NPCR) values above 99.63% in contrast to traditional encryption techniques, showing how resilient it is to statistical attacks. Our hybrid approach improves data secrecy and resistance to various cryptographic attacks. Experimental results confirm the efficiency of the suggested technique by achieving entropy values around 7.99, number of pixels change rate (NPCR) values above 99.63%, and unified average changing intensity (UACI) values over 31.98%, ensuring the secure transmission of sensitive images while maintaining video imperceptibility. Full article

The Internet of Things (IoT) is being applied in multiple domains, including smart homes and energy management. This work aims to tighten security in IoTs using fingerprint authentications and avoid unauthorized access to systems for safeguarding user privacy. Captured fingerprints can jeopardize the security and privacy of personal information. To solve privacy- and security-related problems in IoT-based environments, Biometric Authentication Frameworks (BAFs) are proposed to enable authentications in IoTs coupled with fingerprint authentications on edge consumer devices and to ensure biometric security in transmissions and databases. The Honeywell Advanced Encryption Security-Cryptography Measure (HAES-CM) scheme combined with Hybrid Advanced Encryption Standards with Chaotic Map Encryptions is proposed. BAFs enable private and secure communications between Industry 4.0’s edge devices and IoT. This work’s suggested scheme’s evaluations with other encryption methods reveal that the suggested HAES-CM encryption strategy outperforms others in terms of processing speeds. Full article

Secure image transmission is one of the most challenging problems in the age of communication technology. Millions of people use and transfer images for either personal or commercial purposes over the internet. One way of achieving secure image transmission over the network is encryption techniques that convert the original image into a non-understandable or scrambled form, called a cipher image, so that even if the attacker gets access to the cipher they would not be able to retrieve the original image. In this study, chaos-based image encryption and block cipher techniques are implemented and analyzed for image encryption. Arnold cat map in combination with a logistic map are used as native chaotic and hybrid chaotic approaches respectively whereas advanced encryption standard (AES) is used as a block cipher approach. The chaotic and AES methods are applied to encrypt images and are subjected to measures of different performance parameters such as peak signal to noise ratio (PSNR), number of pixels change rate (NPCR), unified average changing intensity (UACI), and histogram and computation time analysis to measure the strength of each algorithm. The results show that the hybrid chaotic map has better NPCR and UACI values which makes it more robust to differential attacks or chosen plain text attacks. The Arnold cat map is computationally efficient in comparison to the other two approaches. However, AES has a lower PSNR value (7.53 to 11.93) and has more variation between histograms of original and cipher images, thereby indicating that it is more resistant to statistical attacks than the other two approaches. Full article