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Background: The prediction of RNA secondary structure using optimization algorithms is key to understand the real structure of an RNA. Evolutionary algorithms (EAs) are popular strategies for RNA secondary structure prediction. However, compared to most state-of-the-art software based on DPAs, the performances of EAs are a bit far from satisfactory. Objective: Therefore, a more powerful strategy is required to improve the performances of EAs when applied to the prediciton of RNA secondary structures. Methods: The idea of quantum computing is introduced here yielding a new strategy to find all possible legal paired-bases with the constraint of minimum free energy. The sate of a stem pool with size N is encoded as a population of QGA, which is represented by N quantum bits but not classical bits. The updating of populations is accomplished by so-called quantum crossover operations, quantum mutation operations and quantum rotation operations. Results: The numerical results show that the performances of traditional EAs are significantly improved by using QGA with regard to not only prediction accuracy and sensitivity but also complexity. Moreover, for RNA sequences with middle-short length, QGA even improves the state-of-art software based on DPAs in terms of both prediction accuracy and sensitivity. Conclusion: This work sheds an interesting light on the applications of quantum computing on RNA structure prediction.

So far, all existing quantum oblivious transfer protocols focused on realization of the oblivious transfer of a classical bit or classical bit-string. In this paper, p-Rabin quantum oblivious transfer of a qubit protocol is achieved by using a probabilistic teleportation protocol. As the probabilistic teleportation protocol is able to transfer an (un)known pure state with a certain probability, this feature makes the probabilistic teleportation protocol well fit for Rabin oblivious transfer. Here, this is the first time that the concept of qubit oblivious transfer is presented. Furthermore, p-Rabin quantum oblivious transfer of a qubit protocol can also be used for oblivious of a bit by encoding classical bit with two pre-agreed orthogonal states. Finally, security analysis shows that the protocol satisfies the security requirements of oblivious transfer, and what’s more, the discussion of relationship with no-go theorem demonstrates that the probabilistic teleportation protocol is able to evade the no-go theorem.

Quantum-inspired genetic algorithms (QGAs) were recently introduced for the prediction of RNA secondary structures, and they showed some superiority over the existing popular strategies. In this paper, for RNA secondary structure prediction, we introduce a new QGA named multi-population assisted quantum genetic algorithm (MAQGA). In contrast to the existing QGAs, our strategy involves multi-populations which evolve together in a cooperative way in each iteration, and the genetic exchange between various populations is performed by an operator transfer operation. The numerical results show that the performances of existing genetic algorithms (evolutionary algorithms [EAs]), including traditional EAs and QGAs, can be significantly improved by using our approach. Moreover, for RNA sequences with middle-short length, the MAQGA improves even this state-of-the-art software in terms of both prediction accuracy and sensitivity.

In parallel with the rapid developments of cloud-assisted IoT, the corresponding security and privacy issue emerges as a challenge. Biometric recognition technologies are interesting and promising to reinforce traditional cryptographic and personal authentication systems for cloud-assisted IoT. However, the biometric information, if compromised, cannot be canceled and substituted easily. In this paper, based on fuzzy commitment protocol, a fingerprint recognition scheme using minutiae-based sector coding strategy is proposed for cloud-assisted IoT. In our approach, the minutiae of a fingerprint are classified into many designed sectors and then encoded according to their features. With the idea of fuzzy commitment, the key encryption process is accomplished by using BCH codes and Hash mappings. Our scheme, not only provides a flexible way to realize the fingerprint recognition between the complexity and security by designing error-correcting codes with different parameters, but also offers a good balance between the genuine accept rate (GAR) and the false acceptance rate (FAR) with customized sector coding strategies.

Data clustering is the unsupervised classification of data records into groups. As one of the steps in data analysis, it has been widely researched and applied in practical life, such as pattern recognition, image processing, information retrieval, geography, and marketing. In addition, the rapid increase of data volume in recent years poses a huge challenge for resource-constrained data owners to perform computation on their data. This leads to a trend that users authorize the cloud to perform computation on stored data, such as keyword search, equality test, and outsourced data clustering. In outsourced data clustering, the cloud classifies users’ data into groups according to their similarities. Considering the sensitive information in outsourced data and multiple data owners in practical application, it is necessary to develop a privacy-preserving outsourced clustering scheme under multiple keys. Recently, Rong et al. proposed a privacy-preserving outsourced k-means clustering scheme under multiple keys. However, in their scheme, the assistant server (AS) is able to extract the ratio of two underlying data records, and key management server (KMS) can decrypt the ciphertexts of owners’ data records, which break the privacy security. AS can even reduce all data records if it knows one of the data records. To solve the aforementioned problem, we propose a highly secure privacy-preserving outsourced k-means clustering scheme under multiple keys in cloud computing. In this paper, noncolluded cloud computing service (CCS) and KMS jointly perform clustering over the encrypted data records without exposing data privacy. Specifically, we use BCP encryption which has additive homomorphic property and AES encryption to double encrypt data records, where the former cryptosystem prevents CCS from obtaining any useful information from received ciphertexts and the latter one protects data records from being decrypted by KMS. We first define five protocols to realize different functions and then present our scheme based on these protocols. Finally, we give the security and performance analyses which show that our scheme is comparable with the existing schemes on functionality and security.

Due to the transparency of the wireless channel, users in multiple-key environment are vulnerable to eavesdropping during the process of uploading personal data and re-encryption keys. Besides, there is additional burden of key management arising from multiple keys of users. In addition, profile matching using inner product between vectors cannot effectively filter out users with ulterior motives. To tackle the above challenges, we first improve a homomorphic re-encryption system (HRES) to support a single homomorphic multiplication and arbitrarily many homomorphic additions. The public key negotiated by the clouds is used to encrypt the users’ data, thereby avoiding the issues of key leakage and key management, and the privacy of users’ data is also protected. Furthermore, our scheme utilizes the homomorphic multiplication property of the improved HRES algorithm to compute the cosine result between the normalized vectors as the standard for measuring the users’ proximity. Thus, we can effectively improve the social experience of users.

Polar codes can be efficiently decoded by the successive cancellation list (SCL) algorithm in which the sorter plays an important role. The sorter, however, is time-consuming. We significantly improve this decoding scheme by developing a new non-sorting direct selection method for the SCL algorithm. In the non-sorting strategy, we design a new selector for choosing the $L$ best surviving paths, which is achieved by exploiting the bitwise comparison of the candidate path metrics. The analysis and simulation results show that, for $M$ -bit length path metrics, our direct selection method with time complexity $O(ML)$ ) is superior to the latest simplified bubble sorter and the quick sorting strategy whose time complexity is $O(ML^{2})$ and $O(ML \log L)$ , respectively. In the scenario of short codeword length and large list size, our selector can remarkably reduce the latency and the hardware resource consumption while not assuming that the metrics in the decoding are sorted.

Similarity computing of ontological concept has made rapid progress in the field of data mining, information processing and artificial intelligence and becoming one of the hot research field of information technology, particularly the idea of the semantic Web was proposed in 2000, the concept of semantic similarity has gotten more attention, while also facilitating its further development and application in information retrieval. Considering the deficiencies of existing concept similarity algorithm, this paper design the method to reduce the candidate set of domain concept, and put forward a similarity calculation model based on the concept name, instances, properties, and semantic structure of domain ontology. Integrated several main influencing factors, the experiments show the proposed algorithm can express the impact of various factors on the similarity in the calculation concept similarity of domain ontology. By comparing with the traditional similarity method and expertise experience value, the experiment result shows that the effectiveness and correctness of the concept similarity calculation model.

Because the traditional teaching resources management systems are limitations on the description and acquisition of distributed heterogeneous knowledge, domain ontology knowledge base of teaching resources management has been built with the help of experts in the field. A new algorithm of concept similarity has been proposed for calculating the distance between the words, and the ontology has been searched by using Jena API. Finally, the model of system has been implemented. Although the ontology storage method and execution efficiency should be improved, the system has got the initial achievement for the research of ontology in teaching resources management domain.

The 5th generation mobile communication system (5G) is oriented towards a new generation of mobile communication system to the year of 2020 and beyond, and its development is still at the exploratory stage. Combining the latest trends in mobile communication development at home and abroad, in this article, we describe the key technologies of driving the 5G research direction. Furthermore, the technical innovation of 5G comes from both wireless and network technologies. In the field of wireless technologies, massive multiple-input multiple-output (MIMO), ultra-wideband spectral, ultra-dense heterogeneous networks, have already become the focus of global industry. In the field of network technologies, a new network architecture based on software-defined networking (SDN) becomes the prevailing view worldwide. Additionally, there are some other potential technologies for 5G, such as NOMA, FBMC, mm Waves, and Multi-carrier technology aggregation.

Today service fraud in value added service market have turned to be a major problem in the Internet, such as SMS spam, deceiving money using SMS and price fraud. In this paper an enhanced Service Provider (SP) secure management method using Identity-based solution is proposed. In this system, Service subscription, payment and other sensitive information related messages must be signed by a user or SP. So the system obtains non-repudiation of subscription and billing, and the SP forced and reverse subscription can be avoided. By using a special feature of ID-based solution, this method can easily control SP.

In this paper, we address the issue of "distributed steganography" known as many cooperative computations with distributed parties in the covert communication. We present a model of distributed steganography, and give some properties. For the reader's convenience, we consider a scenario in which two senders have their own private data, and wish to carry out a steganographic technique on the union of their private inputs, without revealing any information. The recipient only acquire the union of their inputs. Moreover, they wish to avoid adversaries'attention to the covert communication. We propose a practical scheme to achieve two-party distributed steganography, combining with two different mechanisms: wet paper coding and secure multi-party computation. Detailed correctness, security analysis, and generalization of the scheme are also provided.

This article presents a new solution of portable electronically published materials protection. The solution uses strict data security authentication and strong encryption protocols to improve security features with division of mobile storage device functional domains. And a security protection code to generate a new portable document format is used to prevent the attackers disclose the document information illegally.