Real-Time Index Authentication for Event-Oriented Surveillance Video Query using Blockchain

Nikouei, Seyed Yahya; Xu, Rui‐hua; Nagothu, Deeraj; Chen, Yu; Aved, Alexander; Blasch, Erik

doi:10.48550/arxiv.1807.06179

Cited by 8 publications

(15 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Through exposing public functions or application binary interfaces (ABIs), a smart contract interacts with users to offer the predefined business logic or contract agreement. The blockchain and smart contract enabled security mechanism for applications has been a hot topic and some efforts have been reported recently, for example, smart surveillance system [18], [25], social security system [36], space situation awareness [35], identification authentication [14] and access control [33], [34]. Blockchain and smart contract together are promising to provide a solution to enable a secured data sharing and access authorization in decentralized SPS systems.…”

Section: Blockchain and Smart Contractmentioning

confidence: 99%

BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety

Nikouei

Chen

et al. 2019

2019 IEEE International Conference on Blockchain (Blockchain)

Self Cite

View full text Add to dashboard Cite

Thanks to rapid technological advances in the Internet of Things (IoT), a smart public safety (SPS) system has become feasible by integrating heterogeneous computing devices to collaboratively provide public protection services. While a service oriented architecture (SOA) has been adopted by IoT and cyberphysical systems (CPS), it is difficult for a monolithic architecture to provide scalable and extensible services for a distributed IoT based SPS system. Furthermore, traditional security solutions rely on a centralized authority, which can be a performance bottleneck or single point failure. Inspired by microservices architecture and blockchain technology, this paper proposes a BLockchain-ENabled Decentralized Microservices Architecture for Smart public safety (BlendMAS). Within a permissioned blockchain network, a microservices based security mechanism is introduced to secure data access control in a SPS system. The functionality of security services are decoupled into separate containerized microservices that are built using a smart contract, and deployed on edge and fog computing nodes. An extensive experimental study verified that the proposed BlendMAS is able to offer a decentralized, scalable and secured data sharing and access control to distributed IoT based SPS system.

show abstract

Section: Blockchain and Smart Contractmentioning

confidence: 99%

BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety

Nikouei

Chen

et al. 2019

2019 IEEE International Conference on Blockchain (Blockchain)

Self Cite

View full text Add to dashboard Cite

show abstract

“…45 Through exposing public functions or application binary interfaces (ABI), a smart contract interacts with users to offer the predefined business logic or contract agreement. The blockchain and smart contract enabled security mechanism for applications has been a hot topic and some efforts have been reported recently, for example, smart surveillance system, 24,46 social security system, 47 space situation awareness, 48 identification authentication 49 and access control. 50,51 Blockchain and smart contract together are promising to provide a solution to enable a secured data sharing and access authorization in decentralized public safety systems.…”

Section: Blockchain-enabled Securitymentioning

confidence: 99%

Decentralized Smart Surveillance through Microservices Platform

Nikouei¹,

Xu²,

Chen³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Connected societies require reliable measures to assure the safety, privacy, and security of members. Public safety technology has made fundamental improvements since the first generation of surveillance cameras were introduced, which aims to reduce the role of observer agents so that no abnormality goes unnoticed. While the edge computing paradigm promises solutions to address the shortcomings of cloud computing, e.g., the extra communication delay and network security issues, it also introduces new challenges. One of the main concerns is the limited computing power at the edge to meet the on-site dynamic data processing. In this paper, a Lightweight IoT (Internet of Things) based Smart Public Safety (LISPS) framework is proposed on top of microservices architecture. As a computing hierarchy at the edge, the LISPS system possesses high flexibility in the design process, loose coupling to add new services or update existing functions without interrupting the normal operations, and efficient power balancing. A real-world public safety monitoring scenario is selected to verify the effectiveness of LISPS, which detects, tracks human objects and identify suspicious activities. The experimental results demonstrate the feasibility of the approach.

show abstract

“…The edge device that hosts the data extraction from the video and prepares the feature list for each frame, cannot handle the contextualization of features due to the resource constraints. The video processing task makes use of most of the computational power [35] while the rest is allocated to the transmission and security modules. Moreover, the context, such as spatiotemporal and geo-location are usually repeated data that sending them with each frame creates overhead.…”

Section: Feature Contextualizationmentioning

confidence: 99%

I-SAFE: Instant Suspicious Activity identiFication at the Edge using Fuzzy Decision Making

Nikouei¹,

Chen²,

Aved³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Urban imagery usually serves as forensic analysis and by design is available for incident mitigation. As more imagery collected, it is harder to narrow down to certain frames among thousands of video clips to a specific incident. A real-time, proactive surveillance system is desirable, which could instantly detect dubious personnel, identify suspicious activities, or raise momentous alerts. The recent proliferation of the edge computing paradigm allows more data-intensive tasks to be accomplished by smart edge devices with lightweight but powerful algorithms. This paper presents a forensic surveillance strategy by introducing an Instant Suspicious Activity identiFication at the Edge (I-SAFE) using fuzzy decision making. A fuzzy control system is proposed to mimic the decision-making process of a security officer. Decisions are made based on video features extracted by a lightweight Deep Machine Learning (DML) model. Based on the requirements from the first-line law enforcement officers, several features are selected and fuzzified to cope with the state of uncertainty that exists in the officers decision-making process. Using features in the edge hierarchy minimizes the communication delay such that instant alerting is achieved. Additionally, leveraging the Microservices architecture, the I-SAFE scheme possesses good scalability given the increasing complexities at the network edge. Implemented as an edgebased application and tested using exemplary and various labeled dataset surveillance videos, the I-SAFE scheme raises alerts by identifying the suspicious activity in an average of 0.002 seconds. Compared to four other state-of-the-art methods over two other data sets, the experimental study verified the superiority of the I-SAFE decentralized method.

show abstract

Real-Time Index Authentication for Event-Oriented Surveillance Video Query using Blockchain

Cited by 8 publications

References 29 publications

BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety

BlendMAS: A Blockchain-Enabled Decentralized Microservices Architecture for Smart Public Safety

Decentralized Smart Surveillance through Microservices Platform

I-SAFE: Instant Suspicious Activity identiFication at the Edge using Fuzzy Decision Making

Contact Info

Product

Resources

About