We study non-linear bandit optimization where the learner maximizes a black-box function with zeroth order function oracle, which has been successfully applied in many critical applications such as drug discovery and materials design. Existing works have showed that with the aid of quantum computing, it is possible to break the classical Ω(√T) regret lower bound and achieve the new O(poly log T) upper bound. However, they usually assume that the objective function sits within the reproducing kernel Hilbert space and their algorithms suffer from the curse of dimensionality. In this paper, we propose the new Q-NLB-UCB algorithm which enjoys an input dimension-free O(poly log T) upper bound, making it applicable for high-dimensional tasks. At the heart of our algorithm design are quantum Monte Carlo mean estimator, parametric function approximation technique, and a new quantum non-linear regression oracle, which can be of independent interests in more quantum machine learning problems. Our algorithm is also validated for its efficiency compared with other quantum algorithms on both high-dimensional synthetic and real-world tasks.

This paper considers the problem for finding the $(\delta,\epsilon)$-Goldstein stationary point of Lipschitz continuous objective, which is a rich function class to cover a great number of important applications. We construct a novel zeroth-order quantum estimator for the gradient of the smoothed surrogate. Based on such estimator, we propose a novel quantum algorithm that achieves a query complexity of $\tilde{\mathcal{O}}(d^{3/2}\delta^{-1}\epsilon^{-3})$ on the stochastic function value oracle, where $d$ is the dimension of the problem. We also enhance the query complexity to $\tilde{\mathcal{O}}(d^{3/2}\delta^{-1}\epsilon^{-7/3})$ by introducing a variance reduction variant. Our findings demonstrate the clear advantages of utilizing quantum techniques for non-convex non-smooth optimization, as they outperform the optimal classical methods on the dependency of $\epsilon$ by a factor of $\epsilon^{-2/3}$.

Over the past two decades, advances in materials science and electronics have greatly supported the progress of the communication industry, and the emergence of new materials has made it possible to design higher performance communication modules. As a potential key technology for future 6G networks, the standardisation and industrialisation of visible light communication (VLC) cannot be separated from the improvement of the communication devices. In this paper, we first analyse and summarise the performance enhancement of new materials and designs of VLC devices. Then the support of improved capabilities of novel VLC devices for 6G new services is prospected. As device performance improves, VLC is expected to support more scenarios in 6G.

Dynamic spectrum sharing techniques applied in the UHF TV band have been developed to allow secondary WiFi transmission in areas with active TV users. This technique of dynamically controlling the exclusion zone enables vastly increasing secondary spectrum re-use, compared to the "TV white space" model where TV transmitters determine the exclusion zone and only "idle" channels can be re-purposed. However, in current such dynamic spectrum sharing systems, the sensitive operation parameters of both primary TV users (PUs) and secondary users (SUs) need to be shared with the spectrum database controller (SDC) for the purpose of realizing efficient spectrum allocation. Since such SDC server is not necessarily operated by a trusted third party, those current systems might cause essential threatens to the privacy requirement from both PUs and SUs. To address this privacy issue, this paper proposes a privacy-preserving spectrum sharing system between PUs and SUs, which realizes the spectrum allocation decision process using efficient multi-party computation (MPC) technique. In this design, the SDC only performs secure computation over encrypted input from PUs and SUs such that none of the PU or SU operation parameters will be revealed to SDC. The evaluation of its performance illustrates that our proposed system based on efficient MPC techniques can perform dynamic spectrum allocation process between PUs and SUs efficiently while preserving users' privacy.

Network Function Virtualization (NFV) is a promising technique to greatly improve the effectiveness and flexibility of network services through a process named Service Function Chain (SFC) mapping, with which different network services are deployed over virtualized and shared platforms in data centers. However, such an evolution towards software-defined network functions introduces new challenges to network services which require high availability. One effective way of protecting the network services is to use sufficient redundancy. By doing so, however, the efficiency of physical resources may be greatly decreased. To address such an issue, this paper defines an optimal availability-aware SFC mapping problem and presents a novel online algorithm that can minimize the physical resources consumption while guaranteeing the required high availability within a polynomial time. Simulation results show that our proposed algorithm can significantly improve SFC mapping request acceptance ratio and reduce resource consumption.

Widely used over the Internet to encrypt traffic, HTTPS provides secure and private data communication between clients and servers. However, to cope with rapidly changing and sophisticated security attacks, network operators often deploy middleboxes to perform deep packet inspection (DPI) to detect attacks and potential security breaches, using techniques ranging from simple keyword matching to more advanced machine learning and data mining analysis. But this creates a problem: how can middleboxes, which employ DPI, work over HTTPS connections with encrypted traffic while preserving privacy? In this paper, we present SPABox, a middlebox-based system that supports both keyword-based and data analysis-based DPI functions over encrypted traffic. SPABox preserves privacy by using a novel protocol with a limited connection setup overhead. We implement SPABox on a standard server and show that SPABox is practical for both long-lived and short-lived connection. Compared with the state-of-the-art Blindbox system, SPABox is more than five orders of magnitude faster and requires seven orders of magnitude less bandwidth for connection setup while SPABox can achieve a higher security level.

To secure cloud storage and enforce access control, data encryption has become essential, given the ever increasing cyber threat everywhere. Attribute-based Encryption (ABE) crypto systems are widely considered as a promising solution under such a context for its security strength, scalability and control flexibility. One major challenge, however, for applying ABE-based techniques in real world applications is its high overhead in various aspects. In this research, we are particularly concerned with the storage size expansion in existing ABE schemes. This combined with the vast-size nature of the cloud data poses an enormous challenge to the effective usage of the cloud data storage space and affects the utility of data deduplication. Normally, data deduplication is carried out based on identifying similar and even identical contents both within and between data files, however, these patterns will be destroyed after performing data encryption using any semantically secure encryption scheme including ABE. In this research, we focus on ciphertexts deduplication under ABE, which to our best knowledge is the first of such an effort. Our fundamental observation stems from the structure of ABE ciphertexts and the possible similarities among different access structures. We show how to design a secure ciphertext deduplication scheme based on a classical CP-ABE scheme by innovatively modifying the construction with a recursive algorithm, eliminating the duplicated secrets and adding additional randomness to some certain ciphertext. We then give a detailed analysis on the proposed scheme with respect to both efficiency and security. To thoroughly assess the performance of the proposed scheme, we also implement a prototype system and conduct comprehensive experiments, which shows that our ciphertext reduplication scheme could reduce up to 80% computation and storage cost in the best case.

Centralized spectrum management is one of the key dynamic spectrum access (DSA) mechanisms proposed to govern the spectrum sharing between government incumbent users (IUs) and commercial secondary users (SUs). In the current centralized DSA designs, the operation data of both government IUs and commercial SUs needs to be shared with a central server. However, the operation data of government IUs is often classified information and the SU operation data may also be commercial secret. The current system design dissatisfies the privacy requirement of both IUs and SUs since the central server is not necessarily trust-worthy for holding such sensitive operation data. To address the privacy issue, this paper presents a privacy-preserving centralized DSA system (P2-SAS), which realizes the complex spectrum allocation process of DSA through efficient secure multi-party computation. In P2-SAS, none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. We formally prove the correctness and privacy-preserving property of P2-SAS and evaluate its scalability and practicality using experiments based on real-world data. Experiment results show that P2-SAS can respond an SU's spectrum request in 6.96 seconds with communication overhead of less than 4 MB.

Keyword-based search over encrypted outsourced data has become an important tool in the current cloud computing scenario. The majority of the existing techniques are focusing on multi-keyword exact match or single keyword fuzzy search. However, those existing techniques find less practical significance in real-world applications compared with the multi-keyword fuzzy search technique over encrypted data. The first attempt to construct such a multi-keyword fuzzy search scheme was reported by Wang et al., who used locality-sensitive hashing functions and Bloom filtering to meet the goal of multi-keyword fuzzy search. Nevertheless, Wang's scheme was only effective for a one letter mistake in keyword but was not effective for other common spelling mistakes. Moreover, Wang's scheme was vulnerable to server out-of-order problems during the ranking process and did not consider the keyword weight. In this paper, based on Wang et al.'s scheme, we propose an efficient multi-keyword fuzzy ranked search scheme based on Wang et al.'s scheme that is able to address the aforementioned problems. First, we develop a new method of keyword transformation based on the uni-gram, which will simultaneously improve the accuracy and creates the ability to handle other spelling mistakes. In addition, keywords with the same root can be queried using the stemming algorithm. Furthermore, we consider the keyword weight when selecting an adequate matching file set. Experiments using real-world data show that our scheme is practically efficient and achieve high accuracy.

Searchable symmetric encryption (SSE) allows a client to encrypt his data in such a manner that the data can be efficiently searched. SSE has practical application in cloud storage, where a client outsources his encrypted data to a cloud server while maintaining the searchable ability over his data. Most of the current SSE schemes assume that the cloud server is honest-but-curious. However, the cloud may actively cheat on the search process to keep its cost low. In this paper, we focus on the malicious cloud model and propose a new verifiable searchable symmetric encryption scheme. Our scheme is built on the secure indistinguishability obfuscation (iO) and can be considered as the first step to apply iO in the SSE field. Moreover, our scheme can be easily extended to multiple functionalities, such as conjunctive and boolean queries. Furthermore, it can be extended to realize a publicly verifiable SSE. Thorough analysis shows that our scheme is secure and achieves a better performance.

Proofs-of-Retrievability enables a client to store his data on a cloud server so that he executes an efficient auditing protocol to check that the server possesses all of his data in the future. During an audit, the server must maintain full knowledge of the client’s data to pass, even though only a few blocks of the data need to be accessed. Since the first work by Juels and Kaliski, many PoR schemes have been proposed and some of them can support dynamic updates. However, all the existing works that achieve public verifiability are built upon traditional public-key cryptosystems which imposes a relatively high computational burden on low-power clients (e.g., mobile devices). In this work we explore indistinguishability obfuscation for building a Proof-of-Retrievability scheme that provides public verification while the encryption is based on symmetric key primitives. The resulting scheme offers light-weight storing and proving at the expense of longer verification. This could be useful in apations where outsourcing files is usually done by low-power client and verifications can be done by well equipped machines (e.g., a third party server). We also show that the proposed scheme can support dynamic updates. At last, for better assessing our proposed scheme, we give a performance analysis of our scheme and a comparison with several other existing schemes which demonstrates that our scheme achieves better performance on the data owner side and the server side.

Certificateless signature is an interesting cryptographic primitive which does not suffer from the inherent key escrow problem of identity‐based cryptography and the costly certificate management problem of traditional public key cryptography. Since security proofs in the random oracle model can only be viewed as heuristic arguments and cannot ensure the security in the real implementation, certificateless signature schemes with security proofs in the standard model (i.e. without random oracles) is more desirable. Some attempts have been devoted to propose certificateless signature schemes in the standard model, whereas all of these schemes are later shown to be either insecure or flawed in the security proofs. Recently, a new certificateless signature scheme in the standard model has been proposed. However, in this study the authors show that this scheme cannot resist the key replacement attack, and hence it is not existentially unforgeable.

Attribute-based encryption (ABE) is a public-key-based one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and ciphertexts. One of the main efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. Recently, Greenproposed an ABE system with outsourced decryption that largely eliminates the decryption overhead for users. In such a system, a user provides an untrusted server, say a cloud service provider, with a transformation key that allows the cloud to translate any ABE ciphertext satisfied by that user's attributes or access policy into a simple ciphertext, and it only incurs a small computational overhead for the user to recover the plaintext from the transformed ciphertext. Security of an ABE system with outsourced decryption ensures that an adversary (including a malicious cloud) will not be able to learn anything about the encrypted message; however, it does not guarantee the correctness of the transformation done by the cloud. In this paper, we consider a new requirement of ABE with outsourced decryption: verifiability. Informally, verifiability guarantees that a user can efficiently check if the transformation is done correctly. We give the formal model of ABE with verifiable outsourced decryption and propose a concrete scheme. We prove that our new scheme is both secure and verifiable, without relying on random oracles. Finally, we show an implementation of our scheme and result of performance measurements, which indicates a significant reduction on computing resources imposed on users.