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The widespread use of digital images, driven by low-cost, handheld acquisition devices, has increased the need for robust security measures to safeguard privacy. This demand is further underscored by rising identity theft and other image-related crimes. This study presents a chaos-based experimental evaluation of contemporary image encryption algorithms. Owing to intrinsic properties such as sensitivity to initial conditions and pseudo-randomness, chaos theory has become increasingly prominent in image encryption. Five chaos-based image encryption schemes were selected and applied to a dataset of 26 color images. The evaluation covers both encryption performance and cryptographic security. Decryption quality is measured using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and DeepEns. Cryptographic security is assessed using entropy, correlation coefficient, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), average and maximum deviation, and histogram analysis. Experimental results indicate that all evaluated schemes demonstrate strong cryptographic security and comparable encryption performance, with broadly similar effectiveness across methods.

Relational databases, an essential component in modern information systems, are vulnerable to various security threats, both internal such as abuse of access rights, and external such as SQL injection, malware, and hacking. Given these conditions, how can relevant mitigation strategies be implemented to protect data security in relational databases? This article aims to identify the main threats to relational database security and map out relevant mitigation strategies. The method used is a literature review of various recent scientific journals that discuss aspects of data security in the context of relational databases. The results of the review indicate that threats such as SQL injection can be overcome by strict input validation, abuse of access rights can be prevented through role-based access control (RBAC), malware attacks can be detected using an intrusion detection system (IDS), and hacking actions can be minimized through the implementation of data encryption. This study is expected to be a reference in designing effective security strategies to protect data in relational databases.