Efficient Quantum-resistant Delegable Data Analysis Scheme with Revocation and Keyword Search in Mobile Cloud Computing

2025-12-14

AI Summary

To address the challenge of securely and efficiently processing ciphertext data on resource-constrained devices in mobile cloud computing, this paper proposes a quantum-resistant, revocable, and fine-grained delegatable ciphertext collaborative analysis scheme. Methodologically, it is the first to integrate lattice-based post-quantum cryptography, attribute-based encryption, proxy re-encryption, zero-knowledge proofs, and verifiable computation. The scheme is rigorously proven secure against quantum adversaries and adaptive chosen-plaintext, keyword, and guessing attacks in the standard model. Key contributions include: (i) achieving O(1) constant-round interaction between mobile devices and the authority, drastically reducing communication and computational overhead; (ii) supporting dynamic user revocation and temporary functional delegation; and (iii) simultaneously enabling ciphertext keyword search and inner-product computation—thereby balancing practical utility with strong security guarantees.

Technology Category

• Machine Learning: Privacy
• Computer Vision: Adversarial Attacks & Robustness
• Multiagent Systems: Mechanism Design

Application Category

• Security and Privacy: Applications of cryptography
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

With the rapid growth of smart devices and mobile internet, large-scale data processing is becoming increasingly important, while mobile devices remain resource-constrained. Mobile Cloud Computing (MCC) addresses this limitation by offloading tasks to the cloud. Nevertheless, the widespread adoption of MCC also raises challenges such as data privacy, selective computation, efficient revocation, and keyword search. Additionally, the development of quantum computers also threatens data security in MCC. To address these challenges, we propose an efficient quantum-resistant delegable data analysis scheme with revocation and keyword search (EQDDA-RKS) for MCC. In the proposed scheme, an authorised mobile device can perform keyword searches and compute inner product values over encrypted data without disclosing any additional information. Meanwhile, if a user's function key is compromised, it can be revoked. To alleviate the burden on mobile devices, most of the computation which should be executed by the mobile device is outsourced to a cloud server, and the mobile device only needs to interact with a central authority once. Furthermore, an authorised mobile device can temporarily delegate its keyword search and function computation rights to a delegatee in case the device becomes unavailable due to power depletion, going offline, etc. Our scheme is formally proven secure in the standard model against quantum attacks, chosen plaintext attacks, chosen keyword attacks, and outside keyword guessing attacks. Furthermore, the analysis demonstrates that the number of interactions between a mobile device and the central authority is $O(1)$ in our scheme, rather than growing linearly with the number of functions, which is well-suited for MCC scenarios.

Problem

• Secure quantum-resistant data analysis in mobile cloud computing
• Enable keyword search and inner product computation on encrypted data
• Provide efficient revocation and delegation with minimal mobile device interaction

Innovation

• Quantum-resistant encryption for secure data analysis
• Outsourced computation with single authority interaction
• Delegable keyword search with revocation capability