Abstract Non-Fungible Token (NFT) creators use digital signatures to ensure the ownership, authenticity, integrity, and nonrepudiation of their digital works. However, if the private key is compromised, an attacker can generate unauthorized NFTs by using the creator’s private key to issue valid signatures. These valid but unauthorized signatures will be accepted in the NFT market and cannot be revoked. Even if the NFT creators update their private-public key pairs, they cannot deny the NFTs generated by the attacker. To mitigate these risks, we propose revocable signature by introducing commitment mechanism and an Auxiliary Embedded Key ( AEK ) into the signature, while the regular verification process does not involve this AEK . If a valid but unauthorized signature is detected and needs to be revoked, AEK will be disclosed to perform the revocation operation. To illustrate the application of revocable signatures in NFT, we design and implement a revocable Elliptic Curve Digital Signature Algorithm (ECDSA) scheme with provable security. Experimental evaluations on the FIPS-recommended elliptic curves show that the performance of revocable ECDSA is comparable to the basic ECDSA, with additional 0.0303 s (P-256 curve) and 0.15 USD gas fee in Remix VM for revoking a signature.

The mobilization of Internet of Things (IoT) data is currently stifled by a fundamental market friction: the inherent value uncertainty of data assets. Economically, data functions as an experience good; its true utility is highly context-dependent and verifiable only after consumption. In dynamic environments, this opacity creates High-Entropy characteristics, where the variance of realized utility, stemming from factors ranging from sensor noise to model incompatibility, renders traditional exante pricing inefficient. Risk-averse buyers, unable to assess quality prior to purchase, rationally exit the market, leading to a “Market for Lemons.” To resolve this deadlock, we propose Trustworthy Data Equity, a decentralized protocol that shifts the transaction paradigm from static pricing to retrospective risk-hedging. We model the trading process as a Stackelberg game in a bilateral setting (single buyer–single seller) and derive a closed-form equilibrium for an optimal equity share (α∗), which achieves the Pareto-efficient risk allocation between participants based on their relative risk aversion. While α∗is invariant to the estimated variance, as in classical insurance theory, the base fee (p∗) adapts directly to market risk conditions, governing both value capture and market feasibility. To implement this trustlessly, we introduce a hybrid architecture leveraging Blockchain for immutable settlement and Trusted Execution Environments for privacy-preserving, ex-post utility verification. Our empirical evaluation highlights three core contributions. First, the protocol exhibits strong Economic Robustness by significantly extending market viability under extreme uncertainty, effectively preventing market collapse where traditional mechanisms fail. Second, we identify and mitigate the “Scarcity Multiplier,” a structural inequity that penalizes data-scarce small and medium-sized enterprises, thereby promoting Market Fairness and Inclusivity. Finally, our prototype confirms System Feasibility, achieving constant-time (O(1)) on-chain settlement complexity and sub-second latency, proving the architecture’s scalability for high-frequency IoT data markets.

Effective management of private keys is crucial to ensure the security and ownership of users’ data and digital assets in the Web3 environment. However, existing solutions often fail to adequately address private key management from the user’s perspective. Private key leakage and loss incidents occur frequently, resulting in significant losses of digital assets. Moreover, the conventional approach of revoking both the private and public keys after a leakage or loss accident is inconvenient in Web3, where the public key serves as the user’s wallet address or digital identity. To tackle the issue of user-side private key management in Web3, this paper presents KeyShield which is a leakage-and-loss-resilient private key protection scheme. KeyShield divides the user’s private key into three shares, securely stored across a primary device and a secondary device owned by the user, and a third storage module owned by the user or a semi-trusted service provider. For daily use of the private key, the user only needs to connect the primary and secondary devices. In the event of a leakage or loss, such as device theft or attack, an update process will be triggered to update the three shares, immediately invalidating the leaked or lost share while causing no changes to the public key. As a demonstration of KeyShield, we developed KeyShieldECC accessible on both Android and iOS platforms for managing Elliptic Curve Cryptography (ECC) private keys. The testing results show that for a 256-bit ECC private key, the daily use only needs 0.05 seconds and update needs 0.25 to 0.3 seconds on an ordinary smart phone.

Data trading has become a fundamental category of commerce in the current digital era, bringing along substantial opportunities for economic activities. The emergence of blockchain facilitates decentralized data trading, empowering users to maintain complete control over their own data and enabling direct peer-to-peer transactions. However, while users possess complete control over their data product and asset in a decentralized trading environment, they must take responsibility for their behaviors and face the consequences of dishonest behaviors either from themselves or counterparties. Therefore, behavior fairness problems arise, such as the seller refusing to deliver the correct data product after receiving the money and the buyer failing to pay the outstanding balance after receiving the data product. This article addresses these issues by proposing a decentralized fair data trading ecosystem leveraging the capability of cryptography and smart contracts. A novel verifiable proxy re-encryption (VPRE) scheme is designed, which introduces the verifiability of re-encryption keys into the original PRE schemes. The scheme is implemented using smart contracts, which ensures that trading can succeed if and only if the data seller provides a valid re-encryption key and the buyer pays the correct amount of money. Furthermore, experiments are conducted to evaluate the proposed ecosystem in terms of trading fairness, security, and cost. The results show that the proposed scheme can effectively terminate transactions involving fairness violations with affordable costs ranging from 39 276 Gwei to 296 983 Gwei. Without our solution, these unfair transactions will proceed and consume 77 301 Gwei to 754 447 Gwei gas fees.

Motivated by the needs of power distribution as well as private key protection, the theory and implementation techniques of threshold public-key cryptography (PKC) have been being developed for a long time. However, researches in this field mainly focus on the needs and constraints in distributed environments which consist of nodes with computing capabilities and connected via peer-to-peer and broadcasting communication channels. The resulting schemes are theoretically helpful for private key security but inconvenient for individual users as their implementation requires distributed computing and networking system with broadcasting channels. To address the private key security issue of PKC schemes for individual users, this paper proposes the concept and general construction of sequentially threshold PKC under a communication model consisting of a computing device and several offline storages where broadcasting channels are not required. To illustrate the new paradigm, we design and realize a sequentially threshold Schnorr signature schemeSTSS. The security proofs forSTSSindicate its effectiveness of achieving unforeability under traditional attacks as well as security incidents caused by human faults and system failures. The experiments on FIPS recommended curves P-256, P-384, and P-521 show thatSTSSis comparable with the original Schnorr scheme in terms of time consumed for generating a signature. The construction of sequentially threshold ElGamal decrtyption scheme is also presented. Finally, we illustrate the application ofSTSSin the Blockchain ecosystem.

This research introduces a cutting-edge Web3 literary analysis platform, harnessing the power of blockchain and deep learning technologies. By employing the immutable and transparent nature of blockchain, the platform ensures robust copyright protection while offering readers enhanced interactive features. It applies deep learning techniques for comprehensive analyses of sentiment, topic, and stylistic elements, which are instrumental in predicting potential Nobel Prize laureates. This methodology not only enhances the accuracy of predictions but also sheds light on the evaluation criteria and historical trends associated with the Nobel Prize. Moreover, the platform adopts a directed graph model alongside the struc2vec algorithm to create text vectors for comparative studies, uncovering similarities between works that have won awards and those that have been nominated. Utilizing the LESS model for detailed content examination, the platform delves into sequence relationships within semantic networks, thus improving interpretability and visualization. The integration of blockchain technology guarantees access to unbiased datasets, enabling more precise literary analyses and predictions. This innovative approach has been validated using works that have either won or been nominated for the Nobel Prize, proving its efficacy in identifying the textual characteristics favored by the Nobel Prize committee.

The nonfungible tokens (NFTs) are unique cryptocurrencies that exist on a blockchain and cannot be replicated. However, today's NFT market lacks a sensible pricing framework, which causes NFT price fluctuations to interfere with the investment market. The purpose of this research is to build a dynamic pricing mechanism for NFT based on NFT features, validate the improvement of factor analysis on the pricing model, and integrate the rarity-based model with market factors in an online market. We presented and implemented a prototype pricing algorithm through a designed NFT market. This implementation shows that this advanced pricing mechanism could be used in a real-world pricing scenario and could provide a reasonable price change when market factors change. Furthermore, the experimental results demonstrated that the rarity scores of the features and market factors can potentially induce price fluctuations within the range of negative 0.4 to positive 0.4.

A significant feature of smart door lock systems is the Temporary Key Function (TKF) for visitors. However, existing TKFs in smart door lock systems in use are either vulnerable to attacks or inconvenient for use. This paper thereby proposes elliptic curve cryptography (ECC)-based innovative authentication module for smart door lock systems which enables highly secure and convenient TKF. Based on the authentication module, two protocols are designed for the host and visitor respectively to unlock the door lock system. Security features for the two protocols are verified via Gong Needham Yahalom (GNY) logic. Besides, the proposed prototypes are realized, and the simulation experiments are carried out to study the performance of the protocols. The results show that our scheme is secure and efficient.

In the new paradigm of blockchain-powered intelligent edge, the key agreement is a significant problem that has not been extensively studied so far. Existing key agreement protocols in the traditional public-key setting are usually too complicated and heavy for edge and end devices. Besides, most protocols in use do not have effective measures to resist side-channel attacks, which are increasingly threatening cloud servers, edge devices, and end devices. Identity (ID)-based protocols can be conveniently implemented in the blockchain-powered intelligent edge. Several leakage-resilient ID-based protocols, which can resist side-channel attacks, have been proposed. However, they all involve time-consuming pairing computations. Besides, none of them address side-channel attacks to the key generation center (KGC). This article designs and realizes two novel ID-based key agreement protocols for the blockchain-powered intelligent edge, including an extended Canetti-Krawczyk (eCK) secure ID-based authenticated key agreement (AKA) protocol and a continuous after-the-fact leakage-resilient eCK (CAFL-eCK) secure ID-based AKA protocol. Both protocols do not involve any heavy pairing computation. Besides, the second one can resist side-channel attacks to the KGC and the communicating parties. A hybrid implementation of the two protocols can achieve high efficiency and strong security at the same time in blockchain-powered intelligent edge environments. This is demonstrated via a use case of a blockchain-powered smart home.

The recent surge in the prosperity of the Internet of Things (IoT) has been attracting an increasing number of researchers and experts with great attention due to its significant economic and social values. The IoT brings appealing opportunities and new challenges for both the current and future Internet. In practice, various IoT smart devices are generally pre-programmed and deployed specifically in the proper place to fulfill corresponding functions according to divergent requirements. However, lately, these pre-stored functions tend to be upgraded or reprogrammed more frequently on account of the increment of dynamic needs or urgent situations. Inspired by Software Defined Networking (SDN), the authors propose a framework in this work: Software Defined Function (SDF) for IoT, enabling IoT smart devices to be upgraded or reprogrammed securely and remotely. The authors further present a protocol named as OpenFunction stemmed from OpenFlow. Moreover, the security properties of this protocol are analyzed. Finally, the authors implement a preliminary SDF system and evaluate its performance. Experimental results indicate that OpenFunction allows a controller to update or rewrite functions in IoT devices, as well as to obtain flexibility and security. Accordingly, this work contributes to the future fusion of SDN and IoT technologies.

Edge Artificial Intelligence (AI) is a timely complement of cloud-based AI. By introducing intelligence to the edge, it alleviates privacy concerns of streaming and storing data to the cloud, enables real-time operations where milliseconds matter, and brings AI services to remote areas with poor networking infrastructures. Security is a significant problem in Edge AI applications such as self-driving cars and intelligent healthcare. Since the edge devices are empowered to process data and take actions, attacking and compromising them can cause serious damage. However, the wide deployment of computationally limited devices in edge environments and the increasing happening of side-channel (or leakage) attacks pose critical challenges to security. This article thereby aims to enhance the security for Edge AI by designing and developing lightweight and leakage-resilient authenticated key exchange (LRAKE) protocols. Compared with available LRAKE protocols, the proposed protocols in this article can be effortless applied in some mainstreaming security and communication standards. Moreover, this article realizes prototypes and presents implementation details; and a use case of applying the proposed protocol in Bluetooth 5.0 is illustrated. The theoretical design and implementation details will provide a guidance of applying the LRAKE protocols in Edge AI applications.

Bluetooth wireless technology is widely deployed in consumer electronics such as mobile phones, headsets, medical wearables and so on. Security is a significant concern of users, since such devices collect and store personal data. Security schemes are provided in the Bluetooth Core Specification version 5.0, but they cannot resist the emerging side-channel attacks which can leak long-term secrets through physical manners. In this paper, the security of Bluetooth under side-channel attacks is studied. Specifically, we improved the security of Secure Simple Pairing (SSP) protocol in Bluetooth 5.0 by developing two leakage-resilient methods to resist side-channel attacks. The leakage-resilient SSP protocols are designed using exponent splitting and multiplicative mask leakage-resilient methods respectively to prevent the long-term secrets from being leaked to side-channel attackers. Prototypes of the new and original protocols are realized, and we simulate a set of experiences to evaluate and compare their performance. We find the increased computation cost of the new protocols is slight and acceptable.

In disaster scenarios, such as an area after a terrorist attack, security is a significant problem since communications involve information for the rescue officers, such as polices, militaries, emergency medical technicians, and the survivors. Such information is critically important for the rescue organizations; and protecting the privacy of the survivors is required. Normally, authenticated key exchange (AKE) is an underlying approach for security. However, available AKE protocols are either inconvenient or infeasible in disaster areas due to the very nature of disasters. To address the security problem in disaster scenarios, we propose two pairing-free identity-based AKE (ID-AKE) protocols that have unbalanced computational requirements on the two parties. Compared with existing AKE protocols, the proposed protocols have a number of advantages in disaster scenarios: 1) they are more convenient than symmetric cryptography-based AKE protocols since they do not require any preshared secret between the parties; 2) they are more feasible than asymmetric cryptography-based AKE protocols since they do not require any online server; and 3) they are more friendly to battery-powered and computationally limited devices than pairing-based and pairing-free ID-AKE protocols since they do not involve any bilinear pairing (a time-consuming operation), and have lower computational requirement on the limited party. Security of the proposed protocols are analyzed in detail; and prototypes of them are implemented to evaluate the performance. We also illustrate the application of the protocols through a vivid use case in a terrorist attack scenario.

The networks of intelligent building are usually consist of a great number of smart devices. Since many smart devices only support on-site configuration and upgrade, and communication between devices could be observed and even altered by attackers, efficiency and security are two key concerns in maintaining and managing the devices used in intelligent building networks. In this paper, the authors apply the technology of software defined networking to satisfy the requirement for efficiency in intelligent building networks. More specific, a protocol stack in smart devices that support OpenFlow is designed. In addition, the authors designed the lightweight security mechanism with two foundation protocols and a full protocol that uses the foundation protocols as example. Performance and session key establishment for the security mechanism are also discussed.