Abstract
The rapid advancement in artificial intelligence (AI) and wide deployment of Internet of Video Things (IoVT) enable situation awareness (SAW). The robustness and security of IoVT systems are essential for a sustainable urban environment. While blockchain technology has shown great potential in enabling trust-free and decentralized security mechanisms, directly embedding cryptocurrency oriented blockchain schemes into resource-constrained Internet of Video Things (IoVT) networks at the edge is not feasible. By leveraging Electrical Network Frequency (ENF) signals extracted from multimedia recordings as region-of-recording proofs, this paper proposes EconLedger, an ENF-based consensus mechanism that enables secure and lightweight distributed ledgers for small-scale IoVT edge networks. The proposed consensus mechanism relies on a novel Proof-of-ENF (PoENF) algorithm where a validator is qualified to generate a new block if and only if a proper ENF-containing multimedia signal proof is produced within the current round. The decentralized database (DDB) is adopted in order to guarantee efficiency and resilience of raw ENF proofs on the off-chain storage. A proof-of-concept prototype is developed and tested in a physical IoVT network environment. The experimental results validated the feasibility of the proposed EconLedger to provide a trust-free and partially decentralized security infrastructure for IoVT edge networks.
Highlights
Thanks to the rapid advancements in artificial intelligence (AI) and Internet of Things (IoT) technologies, the concept of Smart Cites becomes realistic
Inspired by spatio-temporal sensitive Electrical Network Frequency (ENF) contained in multimedia signals, this paper proposes EconLedger, a novel Proof-of-ENF (PoENF) consensus algorithm based lightweight
Optiplex-7010 functions as a monitor server to collect data from scattered Internet of Video Things (IoVT) services deployed at different locations of the building, while all Raspberry Pi (RPi) boards play the role of edge devices that process raw video streams from separate cameras
Summary
Thanks to the rapid advancements in artificial intelligence (AI) and Internet of Things (IoT) technologies, the concept of Smart Cites becomes realistic. Online video streams and other offline data, such as situation contextual features, are shared among participants using high-end cloud servers, which are under the control of third-party entities Such a centralized architecture raises severe privacy and security concerns that data in storage can be misused or tampered with by dishonest entities. The storage overhead is prohibitively high if raw data generated by IoVT transacting networks are stored in the blockchain. In contrast to existing solutions that directly collect ENF fluctuations from power grids and stores audio/video recordings in a centralized location-dependent ENF database [10,11], EconLedger uses Swarm [12], which is a decentralized database (DDB) technology, to archive raw ENF-containing multimedia proofs and transactions over IoVT networks.
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