Deep learning is a powerful technique for data-driven learning in the era of Big Data. However, most deep learning models are deterministic models that ignore the uncertainty of data. Fuzzy neural networks are proposed to tackle this type of problem. In this article, we proposed a novel quantum assisted hierarchical fuzzy neural network (QA-HFNN). Different from classical fuzzy neural networks, QA-HFNN uses quantum neural networks (QNNs) to learn fuzzy membership functions. The model is a multifeature fusion learning algorithm with a parallel structural design that integrates quantum and classical neural networks. The classical network is used to capture high-dimensional neural features, the QNNs are designed to capture fuzzy logic features of the data, then, the two features are fused to form the final features to be classified. The experiment is performed on a classical computer, and the quantum circuit is built through a simulated quantum environment. The results indicate that the accuracy of QA-HFNN can equal to or even surpass classical methods in image classification tasks. The quantum circuit utilizes only a single qubit which is easy to implement. In addition, the fidelity of quantum circuit in a quantum noise environment is assessed, demonstrating that QA-HFNN has strong robustness. The time and computational complexity of QNNs was analyzed, further proving the effectiveness of the model.

Rust is designed as a systems programming language that aims to provide safety guarantees and performance efficiency. In practice, programmers usually use atomic correlations to share data across threads. For example, by using atomic operations to correlate with non-atomic addresses, they can design lock-free data structures for efficient concurrency. Although atomic operations are used in safe code, memory ordering misuses can still lead to atomic concurrency bugs and performance loss.In this paper, we conduct the first empirical study of atomic operations and memory ordering usage in Rust, manual inspection of 2883 atomic usages in real-world applications, including 15 thread bugs and 150 performance issues. We also study their usage scenarios, performance comparisons and issue fixes to provide a better understanding on Rust’s memory ordering misuses and guide better code practices in the future.We design AtomVChecker, an automated static analyzer to detect memory ordering misuses. we evaluate our tool on four widely-used concurrent libraries, it can automatically analyze 228 atomic correlations with 80% accuracy. Based on the atomic correlation analysis, AtomVChecker finds a total of 51 performance loss issues in 9 Rust packages, with all of them recently confirmed by the project maintainer based on our reports.

Abstract By introducing the BHT algorithm into the slide attack on 1K-AES and the related-key attack on PRINCE, we present the corresponding quantum attacks in this paper. In the proposed quantum attacks, we generalize the BHT algorithm to the situation where the number of marked items is unknown ahead of time. Moreover, we give an implementation scheme of classifier oracle based on Quantum Phase Estimation algorithm in presented quantum attacks. The complexity analysis shows that the query complexity, time complexity and memory complexity of the presented quantum attacks are all $\mathcal{O}(2^{n/3})$ when the success probability is about $63\%$, where $n$ is the block size. Compared with the corresponding classical attacks, the proposed quantum attacks can achieve subquadratic speed-up under the same success probability no matter on query complexity, time complexity or memory complexity. Furthermore, the query complexity of the proposed quantum slide attack on 1K-AES is less than Grover search on 1K-AES by a factor of $2^{n/6}.$ When compared with the Grover search on PRINCE, the query complexity of the presented quantum attack on PRINCE is reduced from $\mathcal{O}(2^{n})$ to $\mathcal{O}(2^{n/2}).$ When compared with the combination of Grover and Simon’s algorithms on PRINCE, the query complexity of our quantum attack on PRINCE is reduced from $\mathcal{O}(n\cdot 2^{n/2})$ to $\mathcal{O}(2^{n/2}).$ Besides, the proposed quantum slide attack on 1K-AES indicates that the quantum slide attack could also be applied on Substitution-Permutation Network construction, apart from the iterated Even-Mansour cipher and Feistel constructions.

Nowadays, DNS channel attacks on mobile devices have become a challenging threat. Attackers usually attack mobile devices and steal information with the help of DNS channel. It is difficult for users to detect this kind of attack, especially when attackers covert sensitive information in the DNS response. In this paper, we proposed a method for DNS tunnel detection based on isolated forest for Android. We constructed a framework for mobile devices to collect DNS tunnel traffic. Based on the analysis of DNS tunnel traffic generated on mobile devices, we extracted features based on DNS request and response and constructed the feature set. We proposed a DNS tunnel detector, KRTunnel, for mobile devices. Experiments showed that KRTunnel can identify unseen DNS tunnel traffic with the accuracy of 98.1%.

Nowadays, cryptographic ransomware on Android has become one of the most serious threat. They extort users by means of encrypting private data on their devices. Even worse, there exists little files protection solution on IoT devices without ROOT. In light of this, there is an urgent need for countermeasure solutions on IoT devices without ROOT. In this article, we analyze characteristics of cryptographic ransomware. We propose the strategy of files protection against ransomware based on decoys. In order to satisfy the need of files protection on devices without root, we design and implement KRProtector to detect ransomware and protect files based on decoys.

Cloud storage attracts a lot of clients to join the paradise. For a high data availability, some clients require their files to be replicated and stored on multiple servers. Because clients are generally charged based on the redundancy level required by them, it is critical for clients to obtain convincing evidence that all replicas are stored correctly and are updated to the up-to-date version. In this article, we propose a dynamic proof of data possession and replication (DPDPR) scheme, which is proved to be secure in the defined security model. Our scheme shares a single authenticated tree across multiple replicas, which reduces the tree's storage cost significantly. Our scheme allows for batch verification for multiple challenged leaves and can verify multiple replicas in a single batch way, which considerably save bandwidth and computation resources during audit process. We also evaluate the DPDPR's performance and compare it with the most related scheme. The evaluation results show that our scheme saves almost 66 percent tree's storage cost for three replicas, and obtains almost 60 and 80 percent efficiency improvements in terms of the overall bandwidth and computation costs, respectively, when three replicas are checked and each challenged with 460 blocks.

Abstract For a high level of data availability and reliability, a common strategy for cloud service providers is to rely on replication, i.e. storing several replicas onto different servers. To provide cloud users with a strong guarantee that all replicas required by them are actually stored, many multi-replica integrity auditing schemes were proposed. However, most existing solutions are not resource economical since users need to create and upload replicas of their files by themselves. A multi-replica solution called Mirror is presented to overcome the problems, but we find that it is vulnerable to storage saving attack, by which a dishonest provider can considerably save storage costs compared to the costs of storing all the replicas honestly—while still can pass any challenge successfully. In addition, we also find that Mirror is easily subject to substitution attack and forgery attack, which pose new security risks for cloud users. To address the problems, we propose some simple yet effective countermeasures and an improved proofs of retrievability and replication scheme, which can resist the aforesaid attacks and maintain the advantages of Mirror, such as economical bandwidth and efficient verification. Experimental results show that our scheme exhibits comparable performance with Mirror while achieving high security.

Self-testing refers to a device-independent way to uniquely identify an unknown quantum device based only on the observed statistics. Earlier results on self-testing of multipartite state were restricted either to Dicke states or Graph states. In this paper, we propose self-testing schemes for a large family of symmetric three-qubit states, namely the superposition of W state and GHZ state. We first propose and analytically prove a self-testing criterion for the special symmetric state with equal coefficients of the canonical bases, by designing subsystem self-testing of partially and maximally entangled state simultaneously. Then we demonstrate for the general case, the states can be self-tested numerically by the swap method combining semidefinite programming (SDP) in high precision.

Most existing quantum private query (QPQ) protocols can hardly work in the presence of noise. The user Alice may obtain a false database item in noisy environments and both participants may cheat under the disguise of noise, so dealing with the noise needs an overall consideration of error correction, user privacy and database security. However, the only two existing protocols aiming to correct errors in QPQ lack such an overall consideration (at least one party's privacy can be revealed), and they did not estimate what extent of errors can be tolerated (actually, noise is seldom discussed in quantum two-party secure computations, and to the best of our knowledge, relevant bounds on tolerable errors remain unattainable so far). To solve this problem, we first exemplify how one participant reveals the other party's privacy in the existing QPQ protocols aiming to correct errors. Then we propose a practical protocol which can really work via noisy channel, that is, the error rate of the retrieved database item is reduced significantly and both parties' privacy are well protected. Besides, we deduce that the final error rate, user privacy and database security are pairwise in a “trade-off” relationship. By balancing them according to the required level of security and reliability, we obtain an upper bound on tolerable errors.

Replication is a fundamental solution for the cloud service provider (CSP) to guarantee data availability. To provide users with convincing evidence that the copies required by them are all stored correctly, a number of multi-copy integrity auditing schemes were presented. Recently, Barsoum and Hasan proposed a map-based provable multi-copy dynamic data possession scheme (IEEE Transactions on Information Forensics and Security, vol. 10, no. 3, pp. 485-497, 2015), which was claimed to be secure and can ensure that the CSP possesses all copies required by the contract. However, in this letter, we show that the scheme is easily subject to a copy-summation attack and a single-copy attack, by which a cheating CSP only needs to invest a storage cost of a single copy-while can still pass the verifier's challenge at all times. Therefore, the scheme is no longer secure in this case. Furthermore, we propose some simple but effective countermeasures and give a repaired scheme which is free from the above two attacks.