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Smart parking systems are a crucial component of the "smart city" concept, especially in the age of the Internet of Things (IoT). They aim to take the stress out of finding a vacant parking spot in city centers, due to the increasing number of cars, especially during peak hours. To realize the concept of smart parking, IoT-enabling technologies must be utilized, as the traditional way of developing smart parking solutions entails a lack of scalability, compatibility with IoT-constrained devices, security, and privacy awareness. In this paper, we propose a secure and privacy-preserving framework for smart parking systems. The framework relies on the publish/subscribe communication model for exchanging a huge volume of data with a large number of clients. On one hand, it provides functional services, including parking vacancy detection, real-time information for drivers about parking availability, driver guidance, and parking reservation. On the other hand, it provides security approaches on both the network and application layers. In addition, it supports mutual authentication mechanisms between entities to ensure device/data authenticity, and provide security protection for users. That makes our proposed framework resilient to various types of security attacks, such as replay, phishing, and man-in-the-middle attacks. Finally, we analyze the performance of our framework, which is suitable for IoT devices, in terms of computation and network overhead.

Revolution in healthcare can be experienced with the advancement of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Medical Things (IoMT), and edge analytics with the integration of cloud computing. Connected healthcare is receiving extraordinary contemplation from the industry, government, and the healthcare communities. In this study, several studies published in the last 6 years, from 2016 to 2021, have been selected. The selection process is represented through the Prisma flow chart. It has been identified that these increasing challenges of healthcare can be overcome by the implication of AI, ML, DL, Edge AI, IoMT, 6G, and cloud computing. Still, limited areas have implemented these latest advancements and also experienced improvements in the outcomes. These implications have shown successful results not only in resolving the issues from the perspective of the patient but also from the perspective of healthcare professionals. It has been recommended that the different models that have been proposed in several studies must be validated further and implemented in different domains, to validate the effectiveness of these models and to ensure that these models can be implemented in several regions effectively.

Strong security in web applications is critical to the success of your online presence. Security importance has grown massively, especially among web applications. Dealing with web application or website security issues requires deep insight and planning, not only because of the many tools that are available but also because of the industry immaturity. Thus, finding the proper tools requires deep understanding and several steps, including analyzing the development environment, business needs, and the web applications' complexity. In this paper, we demonstrate the architecture of web applications then list and evaluate the widespread security vulnerabilities. Those vulnerabilities are: Fingerprinting, Insufficient Transport Layer Protection, Information Leakage, Cross-Site Scripting, SQL Injection, and HTTP Splitting. In addition, this paper analyzes the tools that are used to scan for these widespread vulnerabilities in web applications. Finally, it evaluates tools due to security vulnerabilities and gives recommendations to the web applications' users and administrators aiming to educate them.