Abstract
Due to the recent advancements in the Internet of Things (IoT) and Edge-Fog-Cloud Computing technologies, the Smart Public Safety (SPS) system has become a more realistic solution for seamless public safety services that are enabled by integrating machine learning (ML) into heterogeneous edge computing networks. While SPS facilitates convenient exchanges of surveillance data streams among device owners and third-party applications, the existing monolithic service-oriented architecture (SOA) is unable to provide scalable and extensible services in a large-scale heterogeneous network environment. Moreover, traditional security solutions rely on a centralized trusted third-party authority, which not only can be a performance bottleneck or the single point of failure, but it also incurs privacy concerns on improperly use of private information. Inspired by blockchain and microservices technologies, this paper proposed a BLockchain-ENabled Decentralized Smart Public Safety (BlendSPS) system. Leveraging the hybrid blockchain fabric, a microservices based security mechanism is implemented to enable decentralized security architecture, and it supports immutability, auditability, and traceability for secure data sharing and operations among participants of the SPS system. An extensive experimental study verified the feasibility of the proposed BlendSPS that possesses security and privacy proprieties with limited overhead on IoT based edge networks.
Highlights
Advancement in artificial intelligence (AI) and Internet of Things (IoT) technology makes the concept of Smart Cities become realistic, and these IoT based smart applications have greatly improved the citizen’s quality of live and build a safe and sustainable urban environment
The Docker is adopted to develop microservices framework, and those containerized microservices units can be deployed both on the edge (Raspberry Pi) devices and fog server
This paper introduces BlendSPS, a blockchain-enabled decentralized smart public safety system, to enhance security and privacy-preserving proprieties in distributed Smart Public Safety (SPS) network
Summary
Advancement in artificial intelligence (AI) and Internet of Things (IoT) technology makes the concept of Smart Cities become realistic, and these IoT based smart applications have greatly improved the citizen’s quality of live and build a safe and sustainable urban environment. The resource constraint IoT devices need a lightweight application mechanism to perform service tasks, while distributed and heterogeneous network requires a scalable and flexible system infrastructure to support complicated and cooperative operations among participants in smart cities. Being considered among the top concerns in the development of smart cities, smart public safety (SPS) facilitates the easy exchanges of surveillance data streams among data owners and third-party service providers. It brings new challenges in architecture, performance, and security. Researchers have proposed to improve the efficiency and throughput of the communication networks with better detection rates, such as reconfiguring the networked cameras [16], utilizing event-driven visualization [17], and mapping conventional real-time images to 3D camera images [18]
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