Federated Blockchain-Based Tracking and Liability Attribution Framework for Employees and Cyber-Physical Objects in a Smart Workplace

Abstract

The systematic integration of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) into the supply chain to increase operational efficiency and quality has also introduced new complexities to the threat landscape. The myriad of sensors could increase data collection capabilities for businesses to facilitate process automation aided by Artificial Intelligence (AI) but without adopting an appropriate Securityby-Design framework, threat detection and response are destined to fail. The emerging concept of Smart Workplace incorporates many CPS (e.g. Robots and Drones) to execute tasks alongside Employees both of which can be exploited as Insider Threats. We introduce and discuss forensic-readiness, liability attribution and the ability to track moving Smart SPS Objects to support modern Digital Forensics and Incident Response (DFIR) within a defence-in-depth strategy. We present a framework to facilitate the tracking of object behaviour within Smart Controlled Business Environments (SCBE) to support resilience by enabling proactive insider threat detection. Several components of the framework were piloted in a company to discuss a real-life case study and demonstrate anomaly detection and the emerging of behavioural patterns according to objects' movement with relation to their job role, workspace position and nearest entry or exit. The empirical data was collected from a Bluetooth-based Proximity Monitoring Solution. Furthermore, a key strength of the framework is a federated Blockchain (BC) model to achieve forensic-readiness by establishing a digital Chain-of-Custody (CoC) and a collaborative environment for CPS to qualify as Digital Witnesses (DW) to support post-incident investigations.

Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature Review

“…For example, image-based evidence can be gained through closed-circuit television (CCTV) surveillance or from social media. Behavioural anomaly detection can be used to detect unauthorised vehicle use through driver profiling [152], detect attacks on smart water systems [104] or unauthorised access within smart workplaces [24].…”

“…Furthermore, these complex and growing networks of connected objects incorporate human-users and form complex cyber-physical-natural (CPN) ecosystems interrelating systems, software, people and services. As such, a problem within this complex cyberspace, including cybersecurity challenges, can have a cascading effect on the entirety of the ecosystem [24,25].…”

Blockchain Based Information Sharing Mechanism for Cyber Threat Intelligence

“…These risks should be considered in the system to be developed and should be minimized. Besides, blockchain can also be used for cybersecurity such as visualization for security management [22], cyber insurance for cyber risk management [23], and cyber forensics analysis [24].…”

Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study

“…The four requirements for adding a block are (i) it must be a transaction, (ii) it must be verified, (iii) it must be stored, and (iv) it must receive a hash. For a more detailed classification, a blockchain requires a distributed ledger, a consensus mechanism, and associated cryptographic means [44].…”