Real-Time Session Control Using Temporal Logic Enforcement presents a formal system of checking and enforcing the secure behaviors of the session in dynamically computing environments. The suggested model models session states and events as formal transitions between states and uses the Linear Temporal Logic (LTL) rules to check safety and liveness property in the execution. Temporal constraints allow a violated policy, an illegal transition, and an abnormal session activity to be identified early which enhances reliability, the assurance of security, and compliance in real time in a distributed system.
Accurate and prompt prediction of PM2.5 concentration is crucial to reduce the impacts of air pollution on human health and city ecosystems. In this study, a hybrid ensemble learning model for hourly PM2.5 predictions is proposed, combining advanced data preprocessing, temporal f…
Strawberry quality grading is a critical task in post-harvest management due to the fruit's highly perishable nature and significant economic value. While deep learning-based computer vision systems have demonstrated promising performance for automated grading, deploying highly a…
Traditionally, cybersecurity anomaly detection systems rely on only one source of data. However, these systems are no longer effective because modern cyber infrastructures are complex and versatile. This paper introduces a new technique called UMS, DLF: Unified Multi, Source Deep…
Water distribution systems (WDSs) are critical public infrastructures increasingly controlled through cyber-physical layers, making them attractive targets for malicious intrusions. Real-time detection is difficult: confirmed attack data is scarce, sensor readings co-vary across…
India’s economy is primarily based on agriculture. Agriculture has significant contribution in nation’s GDP. Food security and employment significantly influenced by agriculture. However factors like uncertain weather conditions, poor quality of seeds and plant diseases impact on…
- Enhancing agricultural productivity and attaining sustainable crop management depend on the early and precise identification of leaf disease. Using state-of-the-art technologies in precision agriculture like machine learning (ML) and image processing greatly increases the effec…