Range query in cloud-based outsourcing applications is an important data search service, but it can suffer from privacy disclosure. In this paper, we generalize and redefine privacy-preserving range query in edge-based Internet of Things (IoT). Furthermore, to enhance security and privacy of sensitive data, we introduce quantum cryptographic technologies and present a novel quantum approach to solve the problem. First, we present a feasible protocol for Quantum Secret Permutating (QSP) with single photons, which will be later utilized in the final scheme as a basic block. Second, we generalize traditional privacy-preserving range query to a secure one-sided two-party computation, i.e., specific dot product. Third, we present a synchronously grouping strategy based on Quantum Key Distribution (QKD) to reduce the complexity and improve the efficiency of solving this two-party computation, so that it can easily get the desired result by repeatedly using feasible quantum privacy query group by group. Finally, adopting our previously proposed quantum protocols, we design privacy-preserving range query quantum scheme in edge-based IoT. Compared with the classical related schemes, our proposed quantum scheme has higher security, because the security of our proposed protocols is based on the basic physical principles of quantum mechanics, instead of unproven computational difficulty assumptions.
Range query in cloud-based outsourcing applications is an important data search service, but it can suffer from privacy disclosure. In this paper, we generalize and redefine privacy-preserving range query in edge-based Internet of Things (IoT). Furthermore, to enhance security and privacy of sensitive data, we introduce quantum cryptographic technologies and present a novel quantum approach to solve the problem. First, we present a feasible protocol for Quantum Secret Permutating (QSP) with single photons, which will be later utilized in the final scheme as a basic block. Second, we generalize traditional privacy-preserving range query to a secure one-sided two-party computation, i.e., specific dot product. Third, we present a synchronously grouping strategy based on Quantum Key Distribution (QKD) to reduce the complexity and improve the efficiency of solving this two-party computation, so that it can easily get the desired result by repeatedly using feasible quantum privacy query group by group. Finally, adopting our previously proposed quantum protocols, we design privacy-preserving range query quantum scheme in edge-based IoT. Compared with the classical related schemes, our proposed quantum scheme has higher security, because the security of our proposed protocols is based on the basic physical principles of quantum mechanics, instead of unproven computational difficulty assumptions.
Range query in cloud-based outsourcing applications is an important data search service, but it can suffer from privacy disclosure. In this paper, to enhance the security and privacy of sensitive data, we introduce quantum cryptographic technologies and present a feasible quantum approach to address an important range query, i.e., privacy-preserving range MAX/MIN query. First, we define a primitive protocol of secure multiparty computations, called Oblivious Set Inclusion Decision (OSID), in which two parties jointly decide whether a private set includes another private set in an oblivious way, and present an efficient OSID quantum protocol. Especially, in order to efficiently implement OSID quantum protocol, we design a single-photon-based quantum protocol for computing XOR of two private bits, which can achieve the information-theoretical security with the help of a non-colluding quantum cloud. Finally, we propose a novel quantum scheme for privacy-preserving range MAX/MIN query in edge-based Internet of Things by using OSID quantum protocols. Compared with the classical related schemes, our proposed quantum scheme has higher security (i.e., quantum security), because the security of our proposed protocols is based on the basic physical principles of quantum mechanics, instead of unproven computational difficulty assumptions.
The development of the Internet of Things (IoT) has brought various IoT services, which facilitate and enrich human life. All these services are at risk of privacy leakage. The privacy-preserving issue of IoT query, which is a typical service, has attracted much attention. A superior candidate for solving the above issue is classical cryptographic schemes based on the computational difficulty. With the advent of quantum computation, the security of such schemes may be broken by the strong ability of some advanced quantum algorithms. How to design a secure scheme for privacy-preserving query under the threat of quantum computation is crucial. To this end, we construct a general architecture of privacy-preserving query in IoT scenarios. Besides trust or honesty-but-curious models, we present a scheme for privacy-preserving query which is also valid in the scenario of untrusted devices. We provide a detailed security analysis. The result shows our scheme achieves private preservation of both service providers and clients.
Abstract Cloud computing, as a popular technology in recent years, has greatly facilitated the development of data outsourcing services. However, when users access sensitive data stored in the cloud, ensuring the security of data remains a pressing challenge. In this paper, we present a privacy-preserving keyword query scheme for outsourced data in cloud environment. Furthermore, to implement this scheme, we propose a series of quantum basic protocols with single qubits. The proposed basic protocols do not require the execution of quantum gate operations, and the necessary measurements are only Bell measurements based on measurement-device-independence. Therefore, it is practical and feasible under current technology. Moreover, compared with classical schemes, our scheme has higher security (i.e., quantum security). Finally, we conduct simulation experiments in IBM Qiskit to verify the correctness and feasibility of the critical parts of the scheme.
Cloud computing is a powerful and popular information technology paradigm that enables data service outsourcing and provides higher-level services with minimal management effort. However, it is still a key challenge to protect data privacy when a user accesses the sensitive cloud data. Privacy-preserving database query allows the user to retrieve a data item from the cloud database without revealing the information of the queried data item, meanwhile limiting user’s ability to access other ones. In this study, in order to achieve the privacy preservation and reduce the communication complexity, a quantum-based database query scheme for privacy preservation in cloud environment is developed. Specifically, all the data items of the database are firstly encrypted by different keys for protecting server’s privacy, and in order to guarantee the clients’ privacy, the server is required to transmit all these encrypted data items to the client with the oblivious transfer strategy. Besides, two oracle operations, a modified Grover iteration, and a special offset encryption mechanism are combined together to ensure that the client can correctly query the desirable data item. Finally, performance evaluation is conducted to validate the correctness, privacy, and efficiency of our proposed scheme.
With the rapid development of IoT technology, securely querying sensitive data collected by devices within a specific range has become a focal concern for users. This paper proposes a privacy-preserving range query scheme based on quantum encryption, along with circuit simulations and performance analysis. We first propose a quantum private set similarity comparison protocol and then construct a privacy-preserving range query scheme for IoT environments. By leveraging the properties of quantum homomorphic encryption, the proposed scheme enables encrypted data comparisons, effectively preventing the leakage of sensitive data. The correctness and security analysis demonstrates that the designed protocol guarantees users receive the correct query results while resisting both external and internal attacks. Moreover, the protocol requires only simple quantum states and operations, and does not require users to bear the cost of complex quantum resources, making it feasible under current technological conditions.
Abstract With the rapid development of distributed collaborative computing, privacy leakage risks in multi-source data joint analysis are increasing, and classical secure scalar product (SSP) protocols are vulnerable to quantum attacks. Existing quantum secure scalar product schemes mostly rely on complex quantum resources or third parties, only support two-party computation, and have poor scalability. To address these issues, this paper proposes a secure multi-party quantum scalar product protocol based on single-photon resources without a third party. The protocol adopts a two-layer architectural design, integrating pairwise secure product operation and privacy-preserving aggregation mechanism. It realizes result blinding via data splitting and reconstruction to fully guarantee data confidentiality. By adopting ring interaction structure and lightweight secure computing modes, it completes collaborative computation of multi-party private data and effectively prevents information leakage in interactive processes. Performance analysis shows that the protocol requires no more than single-photon and single-particle measurements, with complexity within a reasonable range, making it feasible with current quantum technology. This protocol provides an efficient and secure primitive for multi-party privacy-preserving collaborative computing in quantum-resistant scenarios.