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Coronavirus disease 2019 (COVID-19

Location Based Services (LBS) expose user data to malicious attacks. Approaches, evolved, so far, for preserving privacy and security, suffer from one or more anomalies, and hence the problem of securing LBS data is far from being resolved. In particular, accuracy of results vs. privacy degree, privacy vs. performance, and trust between users are open problems. In this article, we present a novel approach by integration of peer-to-peer (P2P) with the caching technique and dummies from real queries. Our approach increases efficiency, leads to improved performance, and provides solutions to many problems that have existed in the past. In addition, we offer an improved way of managing cache. Simulation demonstrates superiority of our approach over earlier ones dealing with both the ratio of privacy and that of performance.

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Thousands of people have lost their lives in stampedes and other crowd related disasters in recent years. Most of these fatalities seem to have been caused by poor control and management of crowds, which is discussed in this article. An efficient and effective crowd management system must also have a plan to deal with the ongoing threat of terrorism and outbreak of various kinds of communicable diseases. In this article, we present a framework of a Crowd Control and Health Management System specially designed to prevent and manage stampedes and other disasters. The system has two subsystems; one for dealing with the management of stampedes and other disasters and the other with healthcare management. As part of the proposed system, an algorithm for an early detection of stampedes, with proof and simulation of implementation, is provided. As part of the healthcare management subsystem, we integrate several mobile applications and develop four of them dealing with relief issues, blood donations, complaints and alerts, and utilizing mobile phones as a sensor device. Our system makes use of various kinds of wireless, mobile, and other technologies and tools including Fog Computing, Smart Phones, Smart Digital Street, IP-Cameras, Radio Frequency Identification (RFID), Voice Alarm, Light Alarm, and Global Positioning System (GPS). We compare merits and effectiveness of RFID and Wireless Sensor Networks (WSNs), as well as those of Cloud and Fog with a view of using them as part of the proposed framework. We also discuss applications of our systems in real-life cases of Hajj, an annual pilgrimage of millions of people to Mecca, and Kumbh Mela, a periodic gathering of tens of millions of people in India, both of which have accounted for the majority of fatalities in stampedes and other disasters.

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The rapid growth of the Internet of Things (IoT) and its attributes of constrained devices and a distributed environment make it difficult to manage such a huge and growing network of devices on a global scale. Existing traditional access-control systems provide security and management to the IoT system. However, these mechanisms are based on central authority management, which introduces issues such as a single point of failure, low scalability, and a lack of privacy. In order to address these problems, many researchers have proposed using blockchain technology to achieve decentralized access control. However, such models are still faced with problems such as a lack of scalability and high computational complexity. In this paper, we propose a light-weight hierarchical blockchain-based multi-chaincode access control to protect the security and privacy of IoT systems. A clustering concept with BC managers enables the extended scalability of the proposed system. The architecture of the proposed solution contains three main components: an Edge Blockchain Manager (EBCM), which is responsible for authenticating and authorizing constrained devices locally; an Aggregated Edge Blockchain Manager (AEBCM), which contains various EBCMs to control different clusters and manage ABAC policies, and a Cloud Consortium Blockchain Manager (CCBCM), which ensures that only authorized users access the resources. In our solution, smart contracts are used to self-enforce decentralized AC policies. We implement a proof of concept for our proposed system using the permissioned Hyperledger Fabric. The simulation results and the security analysis show the efficiency and effectiveness of the proposed solution.