Fortifying Public Safety: A Dynamic Role-Based Access Control Paradigm for Cloud-Centric IoT

The evolution of communication technologies, exemplified by the Internet of Things (IoT) and cloud computing, has significantly enhanced the speed and accessibility of Public Safety (PS) services, critical to ensuring the safety and security of our environment. However, these advancements also introduce inherent security and privacy challenges. In response, this research presents a novel and adaptable access control scheme tailored to PS services in cloud-supported IoT environments. Our proposed access control protocol leverages the strengths of Key Policy Attribute Based Encryption (KP-ABE) and Identity-Based Broadcast Encryption (IDBB), combining them to establish a robust security framework for cloud-supported IoT in the context of PS services. Through the implementation of an Elliptic Curve Diffie-Hellman (ECDH) scheme between entities, we ensure entity authentication, data confidentiality, and integrity, addressing fundamental security requirements. A noteworthy aspect of our lightweight protocol is the delegation of user private key generation within the KP-ABE scheme to an untrusted cloud entity. This strategic offloading of computational and communication overhead preserves data privacy, as the cloud is precluded from accessing sensitive information. To achieve this, we employ an IDBB scheme to generate secret private keys for system users based on their roles, requiring the logical conjunction ('AND') of user attributes to access data. This architecture effectively conceals user identities from the cloud service provider. Comprehensive analysis validates the efficacy of the proposed protocol, confirming its ability to ensure system security and availability within acceptable parameters

Weathering the Nest: Privacy Implications of Home Monitoring for the Aging American Population

The research in this paper will seek to ascertain the extent of personal data entry and collection required to enjoy at least the minimal promised benefits of distributed intelligence and monitoring in the home. Particular attention will be given to the abilities and sensitivities of the population most likely to need these devices, notably the elderly and disabled. The paper will then evaluate whether existing legal limitations on the collection, maintenance, and use of such data are applicable to devices currently in use in the home environment and whether such regulations effectively protect privacy. Finally, given appropriate policy parameters, the paper will offer proposals to effectuate reasonable and practical privacy-protective solutions for developers and consumers

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research