Ensuring fairness in blockchain-based data trading presents significant challenges, as the transparency of blockchain can expose sensitive details and compromise fairness. Fairness ensures that the seller receives payment only if they provide the correct data, and the buyer gains access to the data only after making the payment. Existing approaches face limitations in efficiency, particularly when applied to large-scale data. Moreover, preserving privacy has also been a significant challenge in blockchain. In this paper, we introduce zkMarket, a privacy-preserving fair trade system on the blockchain. We ensure fairness by integrating encryption with zk-SNARKs, enabling verifiable proofs for fair trading. However, applying zk-SNARKs directly can be computationally expensive for the prover. To address this, we improve efficiency by leveraging our novel matrix-formed PRG (MatPRG) and commit-and-prove SNARK (CP-SNARK), making the data registration process more concise and significantly reducing the seller's proving time. To ensure transaction privacy, zkMarket is built upon an anonymous transfer protocol. Experimental results demonstrate that zkMarket significantly reduces the computational overhead associated with traditional blockchain solutions while maintaining robust security and privacy. Specifically, our evaluation quantifies this high efficiency: the seller can register 1 MB of data in 2.8 seconds, the buyer can generate the trade transaction in 0.2 seconds, and the seller can finalize the trade within 0.4 seconds.

Decentralized blockchain systems have provided a significant leap in autonomous logistics practices by enabling accurate product authentication through the tracking of ownership changes. Although public blockchains could provide open access to stored information, privacy and security concerns lead most existing logistics implementations to rely on private or consortium blockchains. This, however, limits or regulates the end-customer's ability to independently verify product provenance.

It is becoming important for the client to be able to check whether the AI inference services have been correctly calculated. Since the weight values in a CNN model are assets of service providers, the client should be able to check the correctness of the result without them. The Zero-knowledge Succinct Non-interactive Argument of Knowledge (zk-SNARK) allows verifying the result without input and weight values. However, the proving time in zk-SNARK is too slow to be applied to real AI applications. This article proposes a new efficient verifiable convolutional neural network (vCNN) framework that greatly accelerates the proving performance. We introduce a new efficient relation representation for convolution equations, reducing the proving complexity of convolution from O(ln) to O(l+n) compared to existing zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) approaches, where l and n denote the size of the kernel and the data in CNNs. Experimental results show that the proposed vCNN improves proving performance by 20-fold for a simple MNIST and 18,000-fold for VGG16. The security of the proposed scheme is formally proven.

Cryptographic accumulators are a common solution to proving information about a large set S. They allow one to compute a short digest of S and short certificates of some of its basic properties, notably membership of an element. Accumulators also allow one to track set updates: a new accumulator is obtained by inserting/deleting a given element. In this work we consider the problem of generating membership and update proofs for \em batches of elements so that we can succinctly prove additional properties of the elements (i.e., proofs are of constant size regardless of the batch size), and we can preserve privacy. Solving this problem would allow obtaining blockchain systems with improved privacy and scalability.

Image is a visual representation of a certain fact and can be used as proof of events. As the utilization of the image increases, it is required to prove its authenticity with the protection of its sensitive personal information. In this paper, we propose a new efficient verifiable image redacting scheme based on zk-SNARKs, a commitment, and a digital signature scheme. We adopt a commit-and-prove SNARK scheme which takes commitments as inputs, in which the authenticity can be quickly verified outside the circuit. We also specify relations between the original and redacted images to guarantee the redacting correctness. Our experimental results show that the proposed scheme is superior to the existing works in terms of the key size and proving time without sacrificing the other parameters. The security of the proposed scheme is proven formally.

Scratchpad memories (SPM) are often used to boost the performance of application-specific embedded systems. In embedded systems, main memories are vulnerable to external attacks such as bus snooping or memory extraction. Therefore it is desirable to guarantee the security of data in a main memory. In software-managed SPM, it is possible to provide security in main memory by performing software-assistant encryption.

As surveillance systems are popular, the privacy of the recorded video becomes more important. On the other hand, the authenticity of video images should be guaranteed when used as evidence in court. It is challenging to satisfy both (personal) privacy and authenticity of a video simultaneously, since the privacy requires modifications (e.g., partial deletions) of an original video image while the authenticity does not allow any modifications of the original image. This paper proposes a novel method to convert an encryption scheme to support partial decryption with a constant number of keys and construct a privacy-aware authentication scheme by combining with a signature scheme. The security of our proposed scheme is implied by the security of the underlying encryption and signature schemes. Experimental results show that the proposed scheme can handle the UHD video stream with more than 17 fps on a real embedded system, which validates the practicality of the proposed scheme.

In a surveillance system, the privacy becomes important since those who are not relevant to an event may be recorded by many surveillance systems. On the other hand, the authenticity of video frames in surveillance systems should be guaranteed if a video is used as evidence. Hence a signature is attached for each frame. However, it is contradictory to provide both privacy and authenticity of a video since the privacy requires deletion of objects in an original video image while the authenticity disallows any modification of the original image. This paper devises a new novel privacy aware secure signature scheme for the surveillance system. In the proposed scheme, deletion (or masking) of objects in an image is allowed while a signature still remains valid for the modified image. The proposed scheme utilizes a chameleon hash so that deletion of objects in an image does not invalidate the signature. The proposed scheme provides forward security minimizing the damage from the secret key exposure. The deletion is executed in an authorized way. Experimental results show that the proposed scheme is practical in a real-time video surveillance system due to the high performance of signature generation (40ms per frame) and a small signature size overhead (1%).

This paper defines a non-linear cost compression problem, proposes an efficient algorithm, and applies it to a real application of multi level cell memory to minimize energy consumption and latency. The non-linear cost compression problem extends the traditional cost compression problem to allow a non-linear cost function of symbol frequencies, while it is a weighted linear combination of symbol frequencies in the cost compression problem. In order to solve the non-linear cost compression problem efficiently, we propose an encoding symbol frequency based approach. We first compute frequencies of encoding symbols to minimize a cost function. To achieve the computed frequencies of a cost-compressed message, we deploy existing size-decompression algorithms. The proposed algorithm is optimal and as fast as the existing size compression algorithms. Our experimental results show that it reduces the energy consumption and latency by 70 percent for a text file in multi level cell memory. Furthermore, it increases the lifetime of endurance limited memory.

A robust group key agreement protocol (GKA) allows a set of players to establish a shared secret key, regardless of network/node failures. Current constant-round GKA protocols are either efficient and nonrobust or robust but not efficient; assuming a reliable broadcast communication medium, the standard encryption-based group key agreement protocol can be robust against arbitrary number of node faults, but the size of the messages broadcast by every player is proportional to the number of players. In contrast, nonrobust group key agreement can be achieved with each player broadcasting just constant-sized messages. We propose a novel 2-round group key agreement protocol, which tolerates up to T node failures, using O(T)-sized messages for any T. We show that the new protocol implies a fully-robust group key agreement with logarithmic-sized messages and expected round complexity close to 2, assuming random node faults. The protocol can be extended to withstand malicious insiders at small constant factor increases in bandwidth and computation. The proposed protocol is secure under the (standard) Decisional Square Diffie-Hellman assumption.

A group key agreement protocol (GKA) allows a set of players to establish a shared secret key which can be used to secure a subsequent communication. Several efficient constant-round GKA's have been proposed. However, their performance degrades if some players fail during protocol execution. This is a problem in practice, e.g. for mobile nodes communicating over wireless media, which can loose connectivity during the protocol execution. Current constant-round GKA protocols are either efficient and non-robust or robust but not efficient: Assuming a reliable broadcast communication medium, the standard encryption-based group key agreement protocol can be robust against arbitrary number of node faults, but the size of the messages broadcast by every player is proportional to the number of players. In contrast, non-robust group key agreement can be achieved with each player broadcasting just constant-sized messages.

Routing is a critical function in multi-hop mobile ad hoc networks (MANETs). A number of MANET-oriented routing protocols have been proposed, of which DSR is widely considered both the simplest and the most effective. At the same time, security in MANETs-especially, routing security-presents a number of new and interesting challenges. Many security techniques geared for MANETs have been developed, among which Ariadne is the flagship protocol for securing DSR. The focus of this work is on securing the route discovery process in DSR. Our goal is to explore a range of suitable cryptographic techniques with varying flavors of security, efficiency and robustness. The Ariadne approach (with TESLA), while very efficient, assumes loose time synchronization among MANET nodes and does not offer non-repudiation. If the fanner is not possible or the latter is desired, an alternative approach is necessary. To this end, we construct a secure route discovery protocol (SRDP) which allows the source to securely discover an authenticated route to the destination using either aggregated message authentication codes (MACs) or multi-signatures. Several concrete techniques are presented and their efficiency and security are compared and evaluated.