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.

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.

This article presents a new simulator able to generate raw data for ocean wave radar spectrometer (OWRS). Data simulation involves three key procedures: generating 2-D sea wave height, velocity, and acceleration fields by use of a prescribed ocean wave height spectrum; calculating the 2-D sea surface normalized radar cross section (NRCS) field using a quasi-specular backscatter model; and incorporating the generated sea wave height, velocity, and acceleration fields into the radar instantaneous range equation (IRE). Our simulator’s reliability in replicating real-world ocean wave spectra has been confirmed by comparing retrieved wave spectra from simulated OWRS raw data with input reference wave spectra and real-measured radar data. The proposed simulator has several advantages over conventional simulators. Notably, OWRS data generated by the proposed simulator are complex in-phase/quadrature-phase (I/Q) raw data, instead of backscattered power modulation data as simulated by conventional simulators. Our simulator’s other advantages include its ability to reflect the effect of Doppler modulation induced by the motions of the radar platform and the sea waves in the speckle noise spectrum after processing OWRS raw data simulated by the proposed simulator, as well as its ability to embody the effect of range modulation caused by the sea surface topography, including both linear and higher order range modulation effects, in retrieved wave slope spectra. Our simulator offers a powerful tool for understanding complicated interactions between ocean wave dynamics and radar signals. Furthermore, it also provides radar engineers with a cost-effective way to evaluate potential designs for future spaceborne OWRS.