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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.

Software testing is a critical phase in information system development to ensure the system's quality and reliability. This study aims to evaluate the reliability and functionality of PT Perta Sakti Abadi's financial information system using the black-box testing method with the Equivalence Partitioning (EP) technique. This technique allows input data to be grouped into valid and invalid categories, minimizing test cases without reducing testing coverage. The testing focuses on the login feature as the system's primary component by evaluating various input combinations. The testing scenarios include boundary conditions to ensure the system handles inputs correctly in various situations.The results indicate that the system successfully verifies valid credentials, rejects access with invalid data, and provides informative error messages. Additionally, the system demonstrates resilience in handling testing scenarios, including inputs with special characters and empty fields. Input validation mechanisms function optimally, supporting secure user access and ensuring the login feature aligns with functional specifications. This successful testing forms a strong foundation for testing other modules, such as multi-level authentication and data encryption. Thus, the Equivalence Partitioning technique within the black-box testing method proves effective in enhancing the quality of web-based financial information systems.

This research focuses on the design and implementation of the Caesar Cipher method to improve the security of an Android-based School Academic Information System. In this digital era, data security is a major concern, especially in school academic information systems that manage important data. The Caesar Cipher method, as a simple and easy to implement encryption technique, is used in this research. The research results show that the implementation of Caesar Cipher has succeeded in increasing data security in the system. While this method does not provide a very high level of security, it can be part of a more complex security approach. Overall, this research shows that the design and implementation of Caesar Cipher is an effective step in improving the security of Android-based school academic information systems.

This research proposes a combination of Quantum Key Distribution (QKD) based on the BB84 protocol with Improved Logistic Map (ILM) to improve data transmission security. This method integrates quantum key formation from BB84 with ILM encryption. This combination creates an additional layer of security, where by default, the operation on BB84 is only XOR-substitution, with the addition of ILM creating a permutation operation on quantum keys. Experiments are measured with several quantum measurements such as Quantum Bit Error Rate (QBER), Polarization Error Rate (PER), Quantum Fidelity (QF), Eavesdropping Detection (ED), and Entanglement-based detection (EDB), as well as classical cryptographic analysis such as Bit Error Ratio (BER), Entropy, Histogram Analysis, and Normalized Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI). As a result, the proposed method obtained satisfactory results, especially perfect QF and BER, and EBD, which reached 0.999.