96 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Flexible Long-Term Secure Archiving

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    Privacy and data protection have always been basic human needs in any society that makes use of written language. From simple personal correspondence over military communication to trade secrets or medical information, confidentiality has been of utmost importance. The implications of a leak of such sensitive information may prove devastating, as the previous examples illustrate perfectly. Furthermore reliability, that is, integrity and authenticitiy of information, is critical with risks reaching from annoying to lethal as can again be seen in the previous examples. This need for data protection has carried over from the analogue to the digital age seamlessly with the amount of data being generated, transmitted and stored increasing steadily and containing more and more personal details. And in regard of the developments in computational technology that recent years have seen, such as the ongoing improvements with respect to quantum computing as well as cryptoanalytical advances, the capabilities of attackers on the security of private information have never been more distinct. Thus the need for privacy and data protection has rarely been more dire

    A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

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    Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

    Homomorphic Trapdoors for Identity-based and Group Signatures

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    Group signature (GS) schemes are an important primitive in cryptography that provides anonymity and traceability for a group of users. In this paper, we propose a new approach to constructing GS schemes using the homomorphic trapdoor function (HTDF). We focus on constructing an identity-based homomorphic signature (IBHS) scheme using the trapdoor, providing a simpler scheme that has no zero-knowledge proofs. Our scheme allows packing more data into the signatures by elevating the existing homomorphic trapdoor from the SIS assumption to the MSIS assumption to enable packing techniques. Compared to the existing group signature schemes, we provide a straightforward and alternate construction that is efficient and secure under the standard model. Overall, our proposed scheme provides an efficient and secure solution for GS schemes using HTDF

    Compact: Approximating Complex Activation Functions for Secure Computation

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    Secure multi-party computation (MPC) techniques can be used to provide data privacy when users query deep neural network (DNN) models hosted on a public cloud. State-of-the-art MPC techniques can be directly leveraged for DNN models that use simple activation functions (AFs) such as ReLU. However, DNN model architectures designed for cutting-edge applications often use complex and highly non-linear AFs. Designing efficient MPC techniques for such complex AFs is an open problem. Towards this, we propose Compact, which produces piece-wise polynomial approximations of complex AFs to enable their efficient use with state-of-the-art MPC techniques. Compact neither requires nor imposes any restriction on model training and results in near-identical model accuracy. We extensively evaluate Compact on four different machine-learning tasks with DNN architectures that use popular complex AFs SiLU, GeLU, and Mish. Our experimental results show that Compact incurs negligible accuracy loss compared to DNN-specific approaches for handling complex non-linear AFs. We also incorporate Compact in two state-of-the-art MPC libraries for privacy-preserving inference and demonstrate that Compact provides 2x-5x speedup in computation compared to the state-of-the-art approximation approach for non-linear functions -- while providing similar or better accuracy for DNN models with large number of hidden layer

    Imbalanced Cryptographic Protocols

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    Efficiency is paramount when designing cryptographic protocols, heavy mathematical operations often increase computation time, even for modern computers. Moreover, they produce large amounts of data that need to be sent through (often limited) network connections. Therefore, many research efforts are invested in improving efficiency, sometimes leading to imbalanced cryptographic protocols. We define three types of imbalanced protocols, computationally, communicationally, and functionally imbalanced protocols. Computationally imbalanced cryptographic protocols appear when optimizing a protocol for one party having significantly more computing power. In communicationally imbalanced cryptographic protocols the messages mainly flow from one party to the others. Finally, in functionally imbalanced cryptographic protocols the functional requirements of one party strongly differ from the other parties. We start our study by looking into laconic cryptography, which fits both the computational and communicational category. The emerging area of laconic cryptography involves the design of two-party protocols involving a sender and a receiver, where the receiver’s input is large. The key efficiency requirement is that the protocol communication complexity must be independent of the receiver’s input size. We show a new way to build laconic OT based on the new notion of Set Membership Encryption (SME) – a new member in the area of laconic cryptography. SME allows a sender to encrypt to one recipient from a universe of receivers, while using a small digest from a large subset of receivers. A recipient is only able to decrypt the message if and only if it is part of the large subset. As another example of a communicationally imbalanced protocol we will look at NIZKs. We consider the problem of proving in zero-knowledge the existence of exploits in executables compiled to run on real-world processors. Finally, we investigate the problem of constructing law enforcement access systems that mitigate the possibility of unauthorized surveillance, as a functionally imbalanced cryptographic protocol. We present two main constructions. The first construction enables prospective access, allowing surveillance only if encryption occurs after a warrant has been issued and activated. The second allows retrospective access to communications that occurred prior to a warrant’s issuance

    Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

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    Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida
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