666 research outputs found

    PRIVACY PRESERVATION FOR TRANSACTION INITIATORS: STRONGER KEY IMAGE RING SIGNATURE AND SMART CONTRACT-BASED FRAMEWORK

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    Recently, blockchain technology has garnered support. However, an attenuating factor to its global adoption in certain use cases is privacy-preservation owing to its inherent transparency. A widely explored cryptographic option to address this challenge has been ring signature which aside its privacy guarantee must be double spending resistant. In this paper, we identify and prove a catastrophic flaw for double-spending attack in a Lightweight Ring Signature scheme and proceed to construct a new, fortified commitment scheme using the signer’s entire private key. Subsequently, we compute a stronger key image to yield a double-spending-resistant signature scheme solidly backed by formal proof. Inherent in our solution is a novel, zero-knowledge-based, secured and cost-effective smart contract for public key aggregation. We test our solution on a private blockchain as well as Kovan testnet along with performance analysis attesting to efficiency and usability and make the code publicly available on GitHub

    Enhancing the Privacy of Decentralized Identifiers with Ring Signatures

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    Most identifiers used today, such as OpenID Connect, are controlled by third parties, which can track how the identifier is used. To overcome this, self-sovereign identifiers, such as Decentralized Identifiers (DIDs), which are entirely owned and managed by the user, have been developed. However, in some cases even DIDs alone do not sufficiently protect the user's privacy. For example, if a service can be accessed at multiple fixed locations, using the same identifier repeatedly for each location may over time also reveal the user's location. One of the techniques to hide the exact service identifiers are ring signatures, which enable the generation of anonymous signatures where the real signer's identity is hidden in a set of possible signers. This thesis takes the use case of electric vehicle charging, where the electric vehicle location may be revealed if static identifiers are used by the electric vehicles and charging stations. A previous solution uses a new ephemeral DID for every interaction, but this requires the creation of a large number of DIDs. This thesis examines an alternative approach of using ring signatures to achieve better privacy with a lower number of DIDs. The major outcomes of this thesis include how to implement ring signatures for anonymous authentication, comparison of resource consumption with respect to the previous solution, and the applicability of ring signature technology on a broader scale such as in constrained devices. The performance of the new solution was compared with the existing solution by implementing prototypes on Android phones, which communicate over Bluetooth. An assumption on the number of charging events was made based on real data for the country of Norway. The results show that ring signatures are easy to implement and provide slightly better privacy but they are significantly more resource-intensive in terms of storage (about 2 times more) and processing (about 9 times slower). Therefore, large scale implementation of ring signatures on the constrained devices is challenging

    A patient agent controlled customized blockchain based framework for internet of things

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    Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

    Identity-based edge computing anonymous authentication protocol

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    With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based edge computing anonymous authentication protocol. The protocol realizes mutual authentication and obtains a shared key by encrypting the mutual information. The encryption algorithm is implemented through a thresholded identity-based proxy ring signature. When a large number of terminals offload computing, MEC can set the priority of offloading tasks according to the user’s identity and permissions, thereby improving offloading efficiency. Security analysis shows that the scheme can guarantee the anonymity and unforgeability of signatures. The probability of a malicious node forging a signature is equivalent to cracking the discrete logarithm puzzle. According to the efficiency analysis, in the case of MEC offloading, the computational complexity is significantly reduced, the computing power of edge devices is liberated, and the signature efficiency is improved
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