While existing solutions can provide authentication services, they are insufficient for a new generation of network coding-based reprogramming protocols in wireless sensor networks. We present a security approach that is able to defend pollution attack against reprogramming protocols based on network coding. It employs a homomorphic hashing function and an identity-based aggregate signature to allow sensor nodes to check packets on-the-fly before they accept incoming encoded packets, and introduces an efficient mechanism to reduce the computation overhead at each node and to eliminate bad packets quickly. Castalia simulations show that when the 5% of the nodes in a network of 100 nodes are rogue, using our approach, the efficiency of the secure reprogramming protocol based on network coding improves almost ten-fold for a checking probability of 2%.

Most of web documents coverage multiple topic. Identifying sentiment of multi-topic documents is a challenge task. In this paper, we proposed a new method to solve this problem. The method firstly reveals the latent topical facets in documents by Parametric Mixture Model. By focusing on modeling the generation process of a document with multiple topics, we can extract specific properties of documents with multiple topics. PMM models documents with multiple topics by mixing model parameters of each single topic. In order to analyze sentiment of each topic, conditional random fields techniques is used to identify sentiment. Empirical experiments on test datasets show that this approach is effective for extracting subtopics and revealing sentiments of each topic. Moreover, this method is quite general and can be applied to any kinds of text collections.

The design of mechanism is used to calculate node reliability of incredible P2P network. The mechanism through matrix shows the trust relationship between nodes in the network, through matrix operation realizes the trust transfer process fast, and through a trusted server provides calculation service of trust degree for nodes in P2P network. 

A refined energy constrained minimization method is developed for target detection in hyperspectral remote sensing images captured by unmanned aerial vehicles (UAVs) during their surveillance missions, which has been tested in the experiment under this paper. The experiment result proves, in the detection process, this method can effectively restrain noises so far as the spectral characteristics of any potential target are known, and find sub-pixel targets out effectively from the hyperspectral remote sensing image in unknown background spectrum.

The drawback of the present various forms of digital program audience statistical method is that only the traditional phone questionnaire survey, the diary method or the artificial equipment is applied to counting the situation of watching program. By means of combining the timely recognized operation property of various digital terminals and automatic return viewing program feature, a new scheme is proposed to count audience situation for program in two-way digital television network. The main technologies and functions of the scheme are described by introducing audience information gathering mechanisms, security return protocol stack based on openSSL, fusion and automatic transmission and its appropriate statistical methods. Meanwhile, the development of the audience rating statistical system is provided, which is used by some program providers according to this scheme. The experiment and users’ feedback show that this scheme in the lower hardware configuration digital terminals can promptly and accurately count the subscribers watching program and effectively protect audience view information.

Wireless Sensor Network is an open self-organized network, which faces serious challenge. Whole network can be split up into many separate subnets which cannot communicate with each other because some vital sensor nodes are attacked. A defense scheme which based on frequency hopping and fast network integration was proposed to react against split-network attack. Frequency hopping makes the communication frequency of the network escape from attack frequency while fast network integration makes the separate subnets reintegrate into a whole network in new communication frequency. Simulation results show the proposed scheme significantly reduces the success rate of attack and increases the lifetime of network.

In network system, network coding allows intermediate nodes to encode the received messages before forwarding them, thus network coding is vulnerable to pollution attacks. Besides, the attacks are amplified by the network coding process with the result that the whole network maybe pollutes. In this paper, we proposed a novel unconditionally secure authentication code for multi-source network coding, which is robust against pollution attacks. For the authentication scheme based on theoretic strength, it is robust against those attackers that have unlimited computational resources, and the intermediate nodes therein can verify the integrity and origin of the encoded messages received without having to decode them, and the receiver nodes can check them out and discard the messages that fail the verification. By this way, the pollution is canceled out before reaching the destinations.

As promising as cloud computing is, this paradigm brings forth new security and privacy challenges when operating in the untrusted cloud scenarios. In this paper, we propose a new cryptographic primitive Proxy Re-encryption with Private Searching (PRPS for short). The PRPS scheme enables the data users and owners efficiently query and access files storaged in untrusted cloud, while keeping query privacy and data privacy from the cloud providers. The concrete construction is based on proxy re-encryption, public key encryption with keyword search and the dual receiver cryptosystem. The scheme is semantically secure under the BDH assumption.

At present most practical electrical auction schemes that based on secret sharing, group signature and hash chain assume the existence of a trusted thid party, while the schemes that based on commitment, zero knowledge or homomorphic encryption without the TTP model face the problem of high cost of communication and computation. The double auction scheme proposed by Bogetoft is based on secure multiparty computation without a TTP and get very high efficiency. In this article, we improve the above scheme. Based on secret sharing and constant round safe comparing protocol, we reduce the requirement of honest majority in the original scheme. We improve the security of the scheme while maintain the high efficiency.

This paper presents an adaptive cross-layer resource allocation problem with the fairness in multi-user OFDM-MISO communication systems, and provides two solutions with Hopfield Neural Network (HNN) and Genetic Algorithm (GA) for the problem. We utilized HNN’s characteristics such as parallel processing, fast convergence speed and easy convergence to the optimum, to solve this problem under the conditions of proportional fairness for satisfying system performances and users’ requirements. The method is simplified in the computation by dividing the bit-loading matrix into three matrixes. The simulation results show that HNN and GA can effectively solve optimization problems of resource allocation in such system, and results of selected HNN and GA methods are more effective than that of the traditional method.