An efficient and compromise-resilient image encryption scheme for resource-constrained environments.

The secret keys produced by current image cryptosystems, which rely on chaotic sequences, exhibit a direct correlation with the size of the image. As the image dimensions expand, the generation of extensive chaotic sequences in the encryption and decryption procedures becomes more computationally intensive. Secondly, a common problem in existing image encryption schemes is the compromise between privacy and efficiency. Some existing lightweight schemes reveal patterns in encrypted images, while others impose heavy computational burdens during encryption/decryption due to the need for large chaotic sequences. In this study, we introduce a lightweight image encryption scheme that involves partitioning the image into uniformly sized tiles and generating a chaotic sequence accordingly. This approach diminishes the necessity to create extensive chaotic sequences equal to the tile size, which is significantly smaller than the original image. As a result, it alleviates the processing burden associated with generating sequences equivalent to the original image size. The results confirm that our proposed scheme is lightweight and secure compared to the latest state-of-the-art image encryption schemes. Additionally, sensitivity analysis demonstrates that the proposed image encryption technique, with a UACI value of 33.48 and NPRC value of 99.96, affirms its resistance to differential attacks.

Energy-efficient routing protocol for reliable low-latency Internet of Things in oil and gas pipeline monitoring.

The oil and gas industries (OGI) are the primary global energy source, with pipelines as vital components for OGI transportation. However, pipeline leaks pose significant risks, including fires, injuries, environmental harm, and property damage. Therefore, maintaining an effective pipeline maintenance system is critical for ensuring a safe and sustainable energy supply. The Internet of Things (IoT) has emerged as a cutting-edge technology for efficient OGI pipeline leak detection. However, deploying IoT in OGI monitoring faces significant challenges due to hazardous environments and limited communication infrastructure. Energy efficiency and fault tolerance, typical IoT concerns, gain heightened importance in the OGI context. In OGI monitoring, IoT devices are linearly deployed with no alternative communication mechanism available along OGI pipelines. Thus, the absence of both communication routes can disrupt crucial data transmission. Therefore, ensuring energy-efficient and fault-tolerant communication for OGI data is paramount. Critical data needs to reach the control center on time for faster actions to avoid loss. Low latency communication for critical data is another challenge of the OGI monitoring environment. Moreover, IoT devices gather a plethora of OGI parameter data including redundant values that hold no relevance for transmission to the control center. Thus, optimizing data transmission is essential to conserve energy in OGI monitoring. This article presents the Priority-Based, Energy-Efficient, and Optimal Data Routing Protocol (PO-IMRP) to tackle these challenges. The energy model and congestion control mechanism optimize data packets for an energy-efficient and congestion-free network. In PO-IMRP, nodes are aware of their energy status and communicate node's depletion status timely for network robustness. Priority-based routing selects low-latency routes for critical data to avoid OGI losses. Comparative analysis against linear LEACH highlights PO-IMRP's superior performance in terms of total packet transmission by completing fewer rounds with more packet's transmissions, attributed to the packet optimization technique implemented at each hop, which helps mitigate network congestion. MATLAB simulations affirm the effectiveness of the protocol in terms of energy efficiency, fault-tolerance, and low latency communication.

Touch or click friendly: Towards adaptive user interfaces for complex applications.

This study evaluated the usability of a direct manipulation device (touchscreen) vs. indirect manipulation devices (mouse and touchpad) on the selected Microsoft (MS) Word tasks as per ISO-9241-11 standard. MS Word was taken as an example of a complex application. The tasks were evaluated in terms of touch-friendly or click-friendly using efficiency, effectiveness, and satisfaction parameters to propose a customized task menu. The experiment was conducted with fifty-four participants, divided into three MS Word usage-based expertise groups. Each participant performed fifty-six tasks using a mouse, a touchpad, and a touchscreen. To assess task-level usability, individual one-way ANOVAs were performed for each task to gauge both efficiency and effectiveness. It's worth noting that the touchscreen significantly outperformed other input methods in just one specific task regarding effectiveness. Consequently, an ANCOVA was employed, with task completion time as the independent variable and the number of errors as a covariate, to further investigate effectiveness. A total of 19 (34%) of the total tasks were found to be significantly efficient with a mouse, while 21 (37.5%) were significantly efficient with a touchscreen. Based on the results, a customized menu is recommended for MS Word-like applications that combine actions in touch-friendly tasks and mouse-friendly tasks separately.