This paper propose a new secure oblivious transfer protocol from indistinguishability obfuscation. The main technical tool in this paper is the candidate indistinguishability obfuscation introduced recently and a dual-mode cryptosystem.. Following their steps, a new k-out-of-l oblivious transfer protocol is presented here, and its realization from DDH is described in this paper, in which we combined indistinguishability obfuscation with the dual-mode cryptosystem. The security of our scheme mainly relies on the indistinguishability of the obf-branches(corresponding to the two modes in dual-mode model). Our paper explores a new way for the application of indistinguishability obfuscation.

Ring signature enables the members to sign anonymously without a manager, it has many online applications, such as e-voting, e-money, whistle blowing etc. As a promising post-quantum candidate, lattice-based cryptography attracts much attention recently. Several efficient lattice-based ring signatures have been naturally constructed from lattice basis delegation, but all of them have large verification key sizes. Our observation finds that a new concept called the split- small integer solution (SIS) problem introduced by Nguyen et al. at PKC’15 is excellent in reducing the public key sizes of lattice-based ring signature schemes from basis delegation. In this research, we first define an extended concept called the extended split-SIS problem, and then prove that the hardness of the extended problem is as hard as the approximating shortest independent vectors problem (SIVP) problem within certain polynomial factor. Moreover, we present an improved ring signature and prove that it is anonymous and unforgeable against the insider corruption. Finally, we give two other improved existing ring signature schemes from lattices. In the end, we show the comparison with the original scheme in terms of the verification key sizes. Our research data illustrate that the public key sizes of the proposed schemes are reduced significantly.

For leakage-resilient ciphertext-policy attribute-based encryption (CP-ABE) at present, the size of the ciphertexts in most of them relies on the number of attributes. How to overcome this shortcoming is a challenge problem. Based on the Goldreich-Levin theorem and dual system encryption, an efficient CP-ABE scheme with constant size ciphertexts is proposed in this paper. It can tolerate leakage on master secret key and attribute-based secret keys with auxiliary inputs. Furthermore, the proposed scheme can be realized as resilience against continual leakage if keys are periodically updated. Under some static assumptions instead of other strong assumptions, the introduced scheme achieves adaptively security in the standard model.

It is the premise of accessing and controlling cloud environment to establish the mutual trust relationship between users and clouds. How to identify the credible degree of the user identity and behavior becomes the core problem? This paper proposes a user abnormal behavior analysis method based on neural network clustering to resolve the problems of over-fitting and flooding the feature information, which exists in the process of traditional clustering analysis and calculating similarity. Firstly, singular value decomposition (SVD) is applied to reduce dimension and de-noise for massive data, where Map-Reduce parallel processing is used to accelerate the computation speed, and neural network model is used for softening points. Secondly, information entropy is added to hidden layer of neural network model to calculate the weight of each attribute. Finally, weight factor is used to calculate the similarity to make the cluster more accuracy. For the problem of analyzing the mobile cloud user behaviors, the experimental results show that the scheme has higher detection speed and clustering accuracy than traditional schemes. The proposed method is more suitable for the mobile cloud environment.

We investigate how to cancel interference by using space time code and codeword space alignment for MIMO Y channel consisting of three users and a relay. All the nodes adopt Alamouti code. During the multiple access stage, two codewords within each reciprocal codeword pair are aligned through pre-coding. The relay decodes the elements of each codeword pair using the orthogonal property of effective channel matrix of Alamouti codeword. During the broadcast stage, the interference between codeword pairs at each user is eliminated by the orthogonal property of effective channel matrix of Alamouti codeword, instead of the interference alignment pre-coding. Thus, channel state information is not required during the broadcast stage, which greatly reduce the amount of feedback.

Securing data transmission in future high-capacity high-coverage multi-tier hierarchical networks for which cognitive radio has emerged as an essential recipe, is of utmost importance. This paper investigates the secrecy outage performance of selection combining (SC) in cognitive radio networks (CRNs) over Rayleigh fading channels. We consider the cognitive wiretap system consisting of a single antenna transmitter (Alice) and a multiple antenna receiver (Bob) equipped with ( ) antennas in the presence of a passive eavesdropper (Eve) equipped with ( ) antennas. Compared to the work proposed by Maged Elkashlan et al. in [1], we present an alternative method to derive the closed-form expression for the secrecy outage probability (SOP) and develop a simplified SOP when the maximal transmit power at the secondary user is large enough. Our results reveal the impact of the primary network on the secondary network with a muti-antenna wiretap channel and simulations are conducted to validate the accuracy of our proposed analytical models.

As an effective solution for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted a lot of attention in recent years. This study investigates the resource block (RB) and power allocation in heterogeneous network. Specifically, the concern here is to maximize the signal-to-interference-plus- noise-ratio (SINR) of macrocell and energy efficiency of femtocell while providing the finite interference. In this paper, the network model is divided into two layers, in which the macro base station and clusters constitute the first layer network; femtocells inside cluster make up the second layer. Because of the different model structure, different game theory is used in each layer. Stackelberg Game is used in the first layer, and non-cooperation game is used in the second layer. Meanwhile RB and power levels stand for the actions that are associated with each player in the game. The problem of resource allocation algorithm is formulated as a mixed integer programming problem. In order to minimize the complexity of the proposed algorithm, the resource allocation task is decomposed into two sub problems: a RB allocation and a power allocation. The simulation results are compared with the traditional methods, the analysis illustrates the proposed algorithm has a better performance regarding SINR and energy efficiency of the heterogeneous network.

Increased adoption of smartphones leads to the explosive growth of mobile network traffic. Understanding the traffic characteristics of mobile network is important for Internet Service Providers (ISPs) to optimize network resources. In this paper, we conduct a detailed measurement study on the HTTP traffic characteristics of cellular network among different operating systems (OSs) as well as different device-types. Firstly, we propose a probability-based method to identify the installed OS of each smartphone. Then we analyze the traffic characteristics of these smartphones in terms of OS and device-type based on a dataset across 31 days (a billing cycle). Finally, we identify the installed apps of each smartphone and compare the usage of apps on the dimensions of OS and device-type. Our measurement study provides insights for network operators to strategize pricing and resource allocation for their cellular data networks.

In recent years, with the development of the system integration technology, the outside integrative special vehicles, such as big oil tank, trucks loading with dangerous goods and so on, are becoming more and more important. When the vehicle is under way, it will inevitably encounter the nature environment, including lightning. If the lightning strikes directly or very close to the vehicle, the lightning-induced effects will be very destructive. Therefore, for a better understanding of the lightning-induced effects produced on the special vehicle by the lightning strike, the research on lightning-induced effects of a special vehicle for aerospace system transportation was proposed. In the paper, a numerical simulation model for the special vehicle is established, the lightning-induced effects are analyzed successfully by using TLM algorithm, and the experiment validation example is also implemented. By comparing the numerical simulation with the actual experiment results, the correctness trend of the numerical simulation is validated and a mass of invaluable research data is obtained, which has a deep significance on the lightning research in our country.

Video description aims to automatically generate descriptive natural language for videos. With its successful implementations and a broad range of applications, lots of work based on Deep Neural Network (DNN) models have been put forward by researchers. This paper takes inspiration from an image caption model and develops an end-to-end video description model using Long Short-Term Memory (LSTM). Single video feature is fed to the first unit of LSTM decoder, and subsequent words of sentence are generated on previous predicted words. Experimental results on two publicly available datasets demonstrate that the performance of the proposed model outperforms that of baseline.

In this article, a method for measuring the performance of adaptive optics (AO) systems is designed and validated by experiments. The Strehl ratio (SR) which is based on the target images is used to evaluate the performance quantitatively because it relates to the effect of AO correction directly. In the calculation of the SR, to avoid energy scaling in the diffraction-limited point spread function, an algorithm based on the integral of the optical transfer function is adopted. Then, a 97-element AO system is established to validate this method, and a white-light fiber source is used as a point-like target. To simulate the practical conditions which influence the performance of the AO system, targets of different brightness are simulated in terms of different signal-to-noise ratios (SNR) of the Shack-Hartmann (SH), and atmospheric turbulence is simulated in terms of the Fried's coherence length and the Greenwood's frequency. Finally, two experiments are conducted in which the SR of different simulated conditions are measured. The results of the experiments show that for a moderate SNR of SH the experimenting AO system is capable of wavefront correction when the Fried's coherence length is larger than 5cm and the Greenwood's frequency is lower than 60Hz. The results also show that the performance of AO is susceptible to the SNR of SH. The experiments validates the effectiveness of this method.