50 research outputs found

    Cryptographic Tools for Privacy Preservation

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    Data permeates every aspect of our daily life and it is the backbone of our digitalized society. Smartphones, smartwatches and many more smart devices measure, collect, modify and share data in what is known as the Internet of Things.Often, these devices don’t have enough computation power/storage space thus out-sourcing some aspects of the data management to the Cloud. Outsourcing computation/storage to a third party poses natural questions regarding the security and privacy of the shared sensitive data.Intuitively, Cryptography is a toolset of primitives/protocols of which security prop- erties are formally proven while Privacy typically captures additional social/legislative requirements that relate more to the concept of “trust” between people, “how” data is used and/or “who” has access to data. This thesis separates the concepts by introducing an abstract model that classifies data leaks into different types of breaches. Each class represents a specific requirement/goal related to cryptography, e.g. confidentiality or integrity, or related to privacy, e.g. liability, sensitive data management and more.The thesis contains cryptographic tools designed to provide privacy guarantees for different application scenarios. In more details, the thesis:(a) defines new encryption schemes that provide formal privacy guarantees such as theoretical privacy definitions like Differential Privacy (DP), or concrete privacy-oriented applications covered by existing regulations such as the European General Data Protection Regulation (GDPR);(b) proposes new tools and procedures for providing verifiable computation’s guarantees in concrete scenarios for post-quantum cryptography or generalisation of signature schemes;(c) proposes a methodology for utilising Machine Learning (ML) for analysing the effective security and privacy of a crypto-tool and, dually, proposes a secure primitive that allows computing specific ML algorithm in a privacy-preserving way;(d) provides an alternative protocol for secure communication between two parties, based on the idea of communicating in a periodically timed fashion

    Secure Computation over Lattices and Elliptic Curves

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    Traditional threshold cryptosystems have decentralized core cryptographic primitives like key generation, decryption and signatures. Most threshold cryptosystems, however, rely on special purpose protocols that cannot easily be integrated into more complex multiparty protocols. In this work, we design and implement decentralized versions of lattice-based and elliptic-curve-based public-key cryptoystems using generic secure multiparty computation (MPC) protocols. These are standard cryptosystems, so we introduce no additional work for encrypting devices and no new assumptions beyond those of the generic MPC framework. Both cryptosystems are also additively homomorphic, which allows for secure additions directly on ciphertexts. By using generic MPC techniques, our multiparty decryption protocols compute secret-shares of the plaintext, whereas most special-purpose cryptosystems either do not support decryption or must reveal the decryptions in the clear. Our method allows complex functions to be securely evaluated after decryption, revealing only the results of the functions and not the plaintexts themselves. To improve performance, we present a novel oblivious elliptic curve multiplication protocol and a new noise-masking technique which may be of independent interest. We implemented our protocols using the SCALE-MAMBA secure multiparty computation platform, which provides security against malicious adversaries and supports arbitrary numbers of participants

    Edge Intelligence : Empowering Intelligence to the Edge of Network

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    Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.Peer reviewe

    Internet of Things for system integrity: a comprehensive survey on security, attacks and countermeasures for industrial applications

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    The growth of the Internet of Things (IoT) offers numerous opportunities for developing industrial applications such as smart grids, smart cities, smart manufacturers, etc. By utilising these opportunities, businesses engage in creating the Industrial Internet of Things (IIoT). IoT is vulnerable to hacks and, therefore, requires various techniques to achieve the level of security required. Furthermore, the wider implementation of IIoT causes an even greater security risk than its benefits. To provide a roadmap for researchers, this survey discusses the integrity of industrial IoT systems and highlights the existing security approaches for the most significant industrial applications. This paper mainly classifies the attacks and possible security solutions regarding IoT layers architecture. Consequently, each attack is connected to one or more layers of the architecture accompanied by a literature analysis on the various IoT security countermeasures. It further provides a critical analysis of the existing IoT/IIoT solutions based on different security mechanisms, including communications protocols, networking, cryptography and intrusion detection systems. Additionally, there is a discussion of the emerging tools and simulations used for testing and evaluating security mechanisms in IoT applications. Last, this survey outlines several other relevant research issues and challenges for IoT/IIoT security
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