133 research outputs found

    A survey of secure middleware for the Internet of Things

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    The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area

    A survey of secure middleware for the Internet of Things

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    SoK: Distributed Computing in ICN

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    Information-Centric Networking (ICN), with its data-oriented operation and generally more powerful forwarding layer, provides an attractive platform for distributed computing. This paper provides a systematic overview and categorization of different distributed computing approaches in ICN encompassing fundamental design principles, frameworks and orchestration, protocols, enablers, and applications. We discuss current pain points in legacy distributed computing, attractive ICN features, and how different systems use them. This paper also provides a discussion of potential future work for distributed computing in ICN.Comment: 10 pages, 3 figures, 1 table. Accepted by ACM ICN 202

    BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models

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    In recent years, artificial intelligence (AI) and machine learning (ML) are reshaping society's production methods and productivity, and also changing the paradigm of scientific research. Among them, the AI language model represented by ChatGPT has made great progress. Such large language models (LLMs) serve people in the form of AI-generated content (AIGC) and are widely used in consulting, healthcare, and education. However, it is difficult to guarantee the authenticity and reliability of AIGC learning data. In addition, there are also hidden dangers of privacy disclosure in distributed AI training. Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition. The above information security issues in the coming era of AI powered by LLMs will be infinitely amplified and affect everyone's life. Therefore, we consider empowering LLMs using blockchain technology with superior security features to propose a vision for trusted AI. This paper mainly introduces the motivation and technical route of blockchain for LLM (BC4LLM), including reliable learning corpus, secure training process, and identifiable generated content. Meanwhile, this paper also reviews the potential applications and future challenges, especially in the frontier communication networks field, including network resource allocation, dynamic spectrum sharing, and semantic communication. Based on the above work combined and the prospect of blockchain and LLMs, it is expected to help the early realization of trusted AI and provide guidance for the academic community

    Blockchain in construction industry for improved material information

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    Towards an auditable cryptographic access control to high-value sensitive data

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    We discuss the challenge of achieving an auditable key management for cryptographic access control to high-value sensitive data. In such settings it is important to be able to audit the key management process - and in particular to be able to provide verifiable proofs of key generation. The auditable key management has several possible use cases in both civilian and military world. In particular, the new regulations for protection of sensitive personal data, such as GDPR, introduce strict requirements for handling of personal data and apply a very restrictive definition of what can be considered a personal data. Cryptographic access control for personal data has a potential to become extremely important for preserving industrial ability to innovate, while protecting subject's privacy, especially in the context of widely deployed modern monitoring, tracking and profiling capabilities, that are used by both governmental institutions and high-tech companies. However, in general, an encrypted data is still considered as personal under GDPR and therefore cannot be, e.g., stored or processed in a public cloud or distributed ledger. In our work we propose an identity-based cryptographic framework that ensures confidentiality, availability, integrity of data while potentially remaining compliant with the GDPR framework

    Internet of Things From Hype to Reality

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    The Internet of Things (IoT) has gained significant mindshare, let alone attention, in academia and the industry especially over the past few years. The reasons behind this interest are the potential capabilities that IoT promises to offer. On the personal level, it paints a picture of a future world where all the things in our ambient environment are connected to the Internet and seamlessly communicate with each other to operate intelligently. The ultimate goal is to enable objects around us to efficiently sense our surroundings, inexpensively communicate, and ultimately create a better environment for us: one where everyday objects act based on what we need and like without explicit instructions
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