Biblio

Blockchain has the potential to enhance supply chain management systems by providing stronger assurance in transparency and traceability of traded commodities. However, blockchain does not overcome the inherent issues of data trust in IoT enabled supply chains. Recent proposals attempt to tackle these issues by incorporating generic trust and reputation management methods, which do not entirely address the complex challenges of supply chain operations and suffers from significant drawbacks. In this paper, we propose DeTRM, a decentralised trust and reputation management solution for supply chains, which considers complex supply chain operations, such as splitting or merging of product lots, to provide a coherent trust management solution. We resolve data trust by correlating empirical data from adjacent sensor nodes, using which the authenticity of data can be assessed. We design a consortium blockchain, where smart contracts play a significant role in quantifying trustworthiness as a numerical score from different perspectives. A proof-of-concept implementation in Hyperledger Fabric shows that DeTRM is feasible and only incurs relatively small overheads compared to the baseline.

There is increased interest in smart vehicles acting as both data consumers and producers in smart cities. Vehicles can use smart city data for decision-making, such as dynamic routing based on traffic conditions. Moreover, the multitude of embedded sensors in vehicles can collectively produce a rich data set of the urban landscape that can be used to provide a range of services. Key to the success of this vision is a scalable and private architecture for trusted data sharing. This paper proposes a framework called SpeedyChain, that leverages blockchain technology to allow smart vehicles to share their data while maintaining privacy, integrity, resilience, and non-repudiation in a decentralized and tamper-resistant manner. Differently from traditional blockchain usage (e.g., Bitcoin and Ethereum), the proposed framework uses a blockchain design that decouples the data stored in the transactions from the block header, thus allowing fast addition of data to the blocks. Furthermore, an expiration time for each block is proposed to avoid large sized blocks. This paper also presents an evaluation of the proposed framework in a network emulator to demonstrate its benefits.

Most two-factor authentication (2FA) implementations rely on the user possessing and interacting with a secondary device (e.g. mobile phone) which has contributed to the lack of widespread uptake. We present a 2FA system, called Wi-Sign that does not rely on a secondary device for establishing the second factor. The user is required to sign at a designated place on the primary device with his finger following a successful first step of authentication (i.e. username + password). Wi-Sign captures the unique perturbations in the WiFi signals incurred due to the hand motion while signing and uses these to establish the second factor. Wi-Sign detects these perturbations by measuring the fine-grained Channel State Information (CSI) of the ambient WiFi signals at the device from which log-in attempt is being made. The logic is that, the user's hand geometry and the way he moves his hand while signing cause unique perturbations in CSI time-series. After filtering noise from the CSI data, principal component analysis is employed for compressing the CSI data. For segmentation of sign related perturbations, Wi-Sign utilizes the thresholding approach based on the variance of the first-order difference of the selected principal component. Finally, the authentication decision is made by feeding scrupulously selected features to a One-Class SVM classifier. We implement Wi-Sign using commodity off-the-shelf 802.11n devices and evaluate its performance by recruiting 14 volunteers. Our evaluation shows that Wi-Sign can on average achieve 79% TPR. Moreover, Wi-Sign can detect attacks with an average TNR of 86%.

There has been increasing interest in adopting BlockChain (BC), that underpins the crypto-currency Bitcoin, in Internet of Things (IoT) for security and privacy. However, BCs are computationally expensive and involve high bandwidth overhead and delays, which are not suitable for most IoT devices. This paper proposes a lightweight BC-based architecture for IoT that virtually eliminates the overheads of classic BC, while maintaining most of its security and privacy benefits. IoT devices benefit from a private immutable ledger, that acts similar to BC but is managed centrally, to optimize energy consumption. High resource devices create an overlay network to implement a publicly accessible distributed BC that ensures end-to-end security and privacy. The proposed architecture uses distributed trust to reduce the block validation processing time. We explore our approach in a smart home setting as a representative case study for broader IoT applications. Qualitative evaluation of the architecture under common threat models highlights its effectiveness in providing security and privacy for IoT applications. Simulations demonstrate that our method decreases packet and processing overhead significantly compared to the BC implementation used in Bitcoin.