Secure Aggregation (SA) is a cornerstone of Federated Learning (FL), ensuring that user updates remain hidden from servers. The advanced Flamingo (S&P’23) has realized multi-round aggregation and improved efficiency. However, it still faces several key challenges: scalability issues with dynamic user participation, a lack of verifiability for server-side aggregation results, and vulnerability to Model Inconsistency Attacks (MIA) caused by a malicious server distributing inconsistent models. To address these issues, we propose $\textit{Janus}$, a generic SA scheme based on dual-server architecture. Janus ensures security against up to $n-2$ colluding clients (where $n$ is the total client count), which prevents privacy breaches for non-colluders. Additionally, Janus is model-independent, ensuring applicability across any FL model without specific adaptations. Furthermore, Janus introduces a new cryptographic primitive, Separable Homomorphic Commitment, which enables clients to efficiently verify the correctness of aggregation. Finally, extensive experiments show that Janus not only significantly enhances security but also reduces per-client communication and computation overhead from logarithmic to constant scale, with a tolerable impact on model performance.

Federated learning (FL) in Vehicular Ad Hoc Networks (VANETs) enables vehicles to collaboratively train a global model for intelligent transportation systems while preserving the privacy of their local data. However, the openness and dynamic nature of VANETs introduce significant security challenges, including identity privacy leakage, model inversion attacks, and compromised model integrity. Existing cryptographic solutions, such as differential privacy and homomorphic encryption, provide partial mitigation but suffer from drawbacks including inefficiency, limited data utility, and vulnerability to data poisoning attacks. To tackle these challenges, this paper introduces FedLG, a generic certificateless (CL) authentication scheme with conditional anonymity. FedLG ensures trustworthy FL by integrating multiple security mechanisms that together guarantee model authenticity, data integrity, and privacy. Specifically, FedLG leverages Type-T signatures as a blackbox to ensure the authenticity and integrity of model parameters shared by anonymous vehicles. Additionally, we introduce a novel public key reconstruction mechanism to enhance the security of traditional CL-based systems, effectively mitigating common public key replacement attacks. FedLG also incorporates batch verification with an adaptive group batch verification algorithm, dynamically adjusting batch sizes to identify invalid signatures while preserving valid data, thereby facilitating faster model convergence. Moreover, FedLG maintains the utility of user-contributed data and can seamlessly integrate it with data poisoning attack prevention mechanisms to enhance security further. Experimental results show that FedLG is model-independent, as its integration does not affect the original model’s performance on its dataset. Moreover, it reduces the computational overhead of signature generation and verification by at least 30.8% and 56.3%, respectively, achieving an overall efficiency improvement of 49.69% compared to state-of-the-art FL authentication protocols for VANETs.

Cryptocurrencies possess a natural advantage in financial applications where response time is not critical, given the well-known high latency and low throughput of blockchain technology. However, a notable gap exists in cryptocurrencies, specifically the absence of applications intentionally introducing delays in committing transactions to facilitate potential revocation operations. Large-Value Payment (LVP), a vital component in financial services, addresses this gap by enabling users to perform such operations. In this context, the payer retains the ability to revoke any number of payments within a pre-agreed timeframe T, while the payee gains the unrevoked transactions after T. In the blockchain landscape, trusted third-party platforms play a role analogous to traditional banking institutions, which can trivially realize LVPs. However, their centralized structure poses challenges such as a single point of failure, privacy concerns, and high transaction fees. Motivated by these limitations, we propose trustless large-value payment protocols with key characteristics: (i) trustlessness, eliminating reliance on any trusted party; (ii) revocability, allowing the payer to revoke payments within the predefined time; and (iii) universality, compatible with all current cryptocurrencies. In this paper, we formally define the semantic and security model of LVP, which paves the way for a new research direction. Building on this foundation, we present a straightforward yet efficient construction of LVP based on Bitcoin scripts. To overcome script-dependency limitations, we introduce a scriptless LVP protocol based on verifiable timed signatures and adaptor signatures. This achieves universality across different cryptocurrencies. We prove the security of our proposals in the Universal Composability framework and further enhance performance for multiple LVPs across diverse cryptocurrencies. Specifically, we design a protocol for secure witness reuse and employ verifiable timed discrete logarithm for revocability. Rigorous security analysis and performance evaluation confirm that both scripted and scriptless LVP protocols meet essential security objectives, providing practical solutions for users requiring transaction revocation without relying on trusted parties.

Vehicular Ad-hoc Networks (VANETs) constitute crucial elements within intelligent transportation systems. However, the rapid development of VANETs has brought forth an increasing number of security concerns. Conditional Privacy-Preserving Certificateless Signature (CPP-CLS) has emerged as a promising solution to ensure data security, preserve vehicle anonymity, and establish unlinkability in VANETs. In contrast to traditional public key infrastructure systems that involve cumbersome certificate management, and identity-based frameworks fraught with key escrow issues, CPP-CLS presents a more apt approach for VANETs. Unfortunately, the researches on CPP-CLS present a strange phenomenon in that a scheme proposed is always pointed out to have various security problems, especially public key replacement attacks. Moreover, there is a scarcity of published researches on the generic construction of CPP-CLS. To tackle these challenges, this paper proposes the first generic construction for CPP-CLS based on Type-T (Three-move type) signature, in which the public key reconstruction technique enables any receiver who owns a part of the sender’s public key and the KGC’s public key to reconstruct the complete sender’s public key, which can alleviate the public key replacement attacks. A formal security analysis proves that our scheme effectively guards against existential forgery under adaptively chosen message attacks in the random oracle model, contingent upon the security of the underlying Type-T signature. Furthermore, We provide two specific instantiations of the generic construction to verify feasibility. Among them, the instantiation based on module learning with errors is effective against quantum attacks. Based on extensive experimental results and theoretical analysis, our implementations surpass the majority of existing similar schemes in either performance or security. This substantiates the feasibility of our generic scheme, making it applicable for constructing CPP-CLS schemes.

The Industrial Internet of Things (IIoT) incorporates massive physical devices to collect ambient data. Due to the limited types of equipment in IIoT, most of the data has to be saved on a cloud server before it can be processed and analyzed. The ciphertext generated by traditional encryption techniques is difficult to search in subsequent use. Public-key encryption with keyword search (PEKS) can provide data encryption as well as confidential searching, but traditional PEKS schemes are susceptible to internal keyword guessing attacks (IKGAs) caused by the limited space of commonly used keywords. To address this issue, the cryptographic primitive of public-key authenticated encryption with keyword search (PAEKS) was proposed, while most of the existing schemes are not appropriately applied to IIoT for involving time-consuming bilinear pairing operations. In this article, we first propose a user-friendly PAEKS scheme that totally circumvents bilinear pairing operations during generating keyword ciphertext and trapdoor. Then, we prove its multiciphertext indistinguishability (MCI) and trapdoor privacy based on decisional$q$-ABDHE and computational Diffie–Hellman assumptions in the random oracle model together with conducting the theoretical and experimental comparisons. The results show that the computational overhead of our proposal is significantly reduced comparing with most existing classical PAEKS schemes without causing other communication costs or security loss. Due to its better performance and security, our scheme is better suited for lightweight devices in the IIoT.