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Aiming at the airport apron safety risk evaluation, using a comprehensive integrated view, combining the quantitative method with qualitative method, a grey relative comprehensive evaluation model of apron safety risk based on THEIL index is proposed. First, objective weight is calculated by THEIL index, combined with experience and knowledge of the subjective weight to determine the final comprehensive weight. Then, based on comprehensive weight, the fuzzy evaluation and grey correlation are used to obtain the results of degree of association, and specific risk evaluation order of aprons is achieved. Finally, the validity of the model is verified by an example, and it provides an effective method for the evaluation of airport apron safety risk.

In the cutting edge world, data security has turned into an essential issue furthermore the innovation is going to increment quickly. In this paper, the symmetric key standard for encryption and decoding is propelled Encryption standard (AES). The key stride in the AES is the "S-Box". S Box is an imperative segment for symmetric key calculations. An S-box takes some number of information bits "p" and interprets them in yield bits 'q', where "p" is not as a matter of course equivalent to 'q'. In AES Encryption calculation Sub Bytes change uses S-Box and Inverse S-Box uses Inverse of S-Box. The Sub Bytes substitution is a nonlinear byte substitution that uses substitution table (i.e., S-Box) takes the multiplicative reverse (GF (28)) and infers a relative change to do the Sub Bytes change. Though, converse Sub Bytes Substitution additionally uses gaze upward table (i.e., Reverse S-Box) takes an opposite relative change and after that suggests multiplicative backwards of Galois Field (GF (28)). In this printed material, we investigated substitution table/reverse substitution table, multiplicative opposite and relative change and its converse (i.e. reverse relative change) science in Galois field. A standout amongst the most basic issues in AES is the force utilization. Here, we predominantly centered around the force utilization and in addition security of S-box which is the most power devouring square in the AES. We have executed and reproduced S-Box and Inverse S-Box Lookup table and acquired another improved scrambled Lookup table for more upgraded mystery by utilizing Xilinx Spartan-3 assessment board. The Simulation and execution instruments utilized are Xilinx ISE 14.1i and ModelSim 6.0.

There is an increasing command for anonymity in network. Crowds[1] is an popular anonymity system proposed by Michael K. Reiter and Aviel D. Rubin which main idea behind it is hiding users’ identities by routing their packets randomly within a group of similar users. Crowds can provides sender anonymity and also has an advantage that the computation load of relay nodes is very small but it does not protect the identity of the receiver. This paper presents an overview on Crowds and introduces the development of Crowds from the following aspects: anonymity analysis, application especially the application in P2P and the performance. We summarize the work about anonymity analysis based on Crowds and divide them into receiver analysis, probabilistic behavior, attack and anonymity proof. Crowds is high efficient but it can’t resist the global attack, therefore, to meet the needs of the different levels of anonymity, there is a vast body of anonymity literature concerned with anonymity analysis, for example, Crowds can’t provide receiver anonymity but receiver anonymity is important in many cases, so many work extending the Crowds system from sender anonymity only to sender and receiver anonymity. In addition to the analysis, we also summarize the applications of Crowds. Undoubtedly, it is widely used in P2P. We also give an overlook of the performance of Crowds.

Neural Network (NN) models employed in lots of researches about system call intrusion detection, however, most probably suffer from problems, such as sensitivity to random initialization, local optimum, outlier of training data, etc. A robust supervised relevance neural gas with discriminant analysis, called RSRNG-DA, is firstly proposed. By incorporating several robust strategies, e.g. outlier resistant scheme and building discriminant analysis on dissimilarity spaces of prototypes, into supervised relevance neural gas (SRNG) framework, RSRNG-DA possesses better robust properties. RSRNG-DA can tolerate the influence cased by outlier and random ordering of training data, and present a significant improvement on classification efficiency. Moreover, the relevant degree of each system call as feature that contributes most to classification performance can be determined, such that the relevance of all features can help to prune irrelevant pattern dimensions. Our technique is evaluated on the system call database maintained by NMU. Experimental results are compared with other existing methods in the literature, and have shown the superior performance on detection rate, false positive and computation time aspects.

Data Communication and network have changed the way business and other daily affair works. Now, they rely on computer network and internetwork. Computer network is a telecommunication channel through which we can share our data. It is also called data network. Security for data transmission is one of the important aspects to be considered in modern communication system. In this paper data that is to be transferred is sent in certain pattern which is embedded in the huge amount of data that can be seen by everyone. The effectiveness of the proposed method is described in such a way to increase security of data. To hide data in a binary image, no key is needed here rather this algorithm is based on binary tree traversal through which the bits are plotted in MSB (Most Significant Bit), LSB(Least Significant bit) and MIDDLE bit of a byte. The proposed algorithm assures the data hiding and security.

There is a shortcoming in reversible data-hiding algorithm in encrypted images, it is the low capacity. we put forward a new algorithm oriented security application in cloud computing, in the new algorithm of reversible data-hiding algorithm in encrypted image, we bring in cloud computing service and singular value decomposition based on matrix. Using the powerful computing and storage capacity, compute the singular value decomposition of some selected bit planes of the encrypted image, and store the recovery dictionary that generated in this process, in the end ,we directly embed the information into the singular value matrix. Experimental results show that under the premise of ensured image privacy security and higher image fidelity, the embedding capacity has been significantly improved, and the image can be fully recovered after information extraction. In the same time, the processes of information extraction and image restoration are separable. Compared with other algorithms, it has higher embedding capacity.

The paper is an exploratory research concerning information trust on cyberspace. The research question is presented as, “How do individuals’ perceptions regarding the benefits and risks of the internet affect their trust in cyberspace?” Dependent variables used in the study consisted of trust in online information. Explanatory variables consisted of sociodemographic characteristics (gender, age, education level, income level, employment status), internet usage pattern (frequency of use, online behavior, means of getting online), and perception of the internet (benefits, risks, attitude towards the online environment, internet ethics). Positive perception including perception of the benefits of the internet, positive expectation for online environment, and online ethics contributed more significantly to cyberspace trust than more than negative view of the internet or negative expectation for the internet.

HUGO is the content-based adaptive steganography method for spatial images which can approximately preserve the joint statistic of differences between up to four neighboring pixels in four different directions. But the steganalysis method based on the higher order local model can fail HUGO. In view of the above problem, an improved steganography is proposed. Firstly, by analyzing the higher order local model, the distortion function is defined based on the quantitative MINMAX features. Then, combined with the theoretical framework of the Gibbs construction in steganography, the improved image steganography algorithm is proposed. The experimental results show that the proposed algorithm can not only resist the detection of the steganalysis method based on the quantitative MINMAX features , but also resist the detection of the steganalysis method based on the hybrid quantitative MINMAX features.

The advent of online social network and mobile multimedia communication has made content sharing in social network easier and more efficient. It is very important to combine fingerprinting and encryption for social multimedia content protection. In this paper, a parallel JFE (joint fingerprinting and encryption) framework is proposed. Firstly, the multi-level social fingerprint code is produced using social network analysis, and followed by TSH (tree structure harr) wavelet decomposition for multimedia content. And then, fingerprints are embedded into all the LL, HL and LH subbands parallelly. At last, GoL(Game of Life) are used to for confusion for wavelet coefficients parallelly. The proposed parallel JFE method, to the best of our knowledge, is the first JFE method using GoL in the TSH wavelet domain for security and privacy. Theory analysis and experimental results demonstrate the effectiveness of the proposed JFE scheme.

Certificateless Public Key Cryptography is a scheme that provides security by avoiding the key escrow and eliminating the drawback of identity-based cryptography. Several certificateless models have been proposed to enhance the efficiency and overcome adversaries attacks. In this paper, we survey various public key encryption schemes on certificateless setting with the security model and discuss the performance. Also, we present the generic model of Certificateless Public Key Encryption (CL-PKE) scheme proposed by various authors.

In this paper, a key management and security multi-hop routing scheme based on cross layer (SMRCL) was proposed for wireless sensor networks. The core of SMRCL has two parts as following. Firstly, a key management based on polynomial and time deployment for wireless sensor networks is proposed. In this scheme, the sensor nodes are divided into several deployment groups and deployed the network according to the time. Moreover polynomial is used instead of common key, which the redundant polynomial is deleted when a deployment group has been deployed to the network. Secondly, a multi-hop routing algorithm is proposed based on cross-layer, which can be used in large scale. In the algorithm, we can use the information of the MAC layer, consider the cross-layer design by the ratio of the packet sending/reception rate and queue length to improve the network load ability. Simulation results demonstrate that SMRCL can save energy and balance the network load and improve the network lifetime. Comparison of the probability of the sensor connectivity, performance of resistance to the node capture and the sensor node overheads, show that the scheme can guarantee the high probability of node secure connectivity, improves the performance of resistance to the node capture, reduces the node storage overhead effectively.

In the era of Information technology, Software Piracy and security has become one of the most important issue in world. Numbers of techniques have been proposed and implemented to prevent software piracy and illegal modification. Among all the protection techniques, software watermarking technique which attempts to protect the software by embedding copyright notice or unique identifiers into software to prove the ownership of software. Software Watermarking discourage piracy; as a proof of purchase or authorship; also helps in tracking the source of illegal redistribution of copies of software. We evaluate the existing dynamic watermarking algorithms using them to watermark java bytecode files and then applying distortive attacks to each watermarked program by obfuscating. Our study has shown that some watermarks were removed as results of these transformations.

With the development of electronic commerce, the management mode of enterprises has been changed, E-business enterprises will also create new financial model, suitable for electronic commerce situation. In this paper, the author first put forward the data mining method based on SVM algorithm. Based on the empirical analysis, author research on the influence factors of e-commerce enterprise financial management mode, and makes a detailed analysis of the relationship between the environment, the network and the performance. For the electronic business enterprise, the solvency, development potential, innovation ability and adapt to the environment of the organization flexibility is the important index of E-enterprise performance evaluation index system.

The linear complexity and k-error linear complexity of a sequence have been used as important measures for keystream strength. In order to study k-error linear complexity of binary sequences with period 2n, a new tool called cube theory is developed. In this paper, we first give a general decomposition approach to decompose a binary sequence with period 2n into some disjoint cubes. Second, a counting formula for m-cubes with the same linear complexity is derived, which is equivalent to the counting formula for k-error vectors. The counting formula of 2n-periodic binary sequences which can be decomposed into more than one cube is also investigated, which extends an important result by Etzion et al.. Finally, we study 2n-periodic binary sequences with the given k-error linear complexity profile. Consequently, the complete counting formula of 2n-periodic binary sequences with given k-error linear complexity profile of descent points 2, 4 and 6 is derived. The periodic sequences having the prescribed k-error linear complexity profile with descent points 1, 3, 5 and 7 are also briefly discussed.

Along with the rapid development of network technology and the rich variety of network applications, all kinds of network attacks and abnormal behavior is more and more rampant, which seriously interferes with the normal operation of the Internet. Based on regular expression, this paper studies the method of network intrusion detection, and proposes an improved grouping algorithm (IGA) to improve Yu algorithm based on the concept of expansion coefficient (EC). And we use the modified regular expression grouping algorithm to effectively group the regular expression set. Based on the open source software, we implement the improved regular expression matching engine, and carry out the grouping algorithm experiments and performance testing experiment. The experimental results we obtained is that the overall state number of IGA algorithm number is reduced by an average 27% compared with the overall state number of Yu algorithm under the condition of the same number of clusters, and the compilation time of MRegex 1.5 increases with the increase of the number of rules compared with PCRE. We can draw the following conclusions: (1) the total number of DFA state of the IGA algorithm is reduced in the same number of cases, and it also can reduce the memory space of the memory DFA, and the space complexity of the matching algorithm. 2) It can improve the efficiency of intrusion detection system. 3) Compared with PCRE (Perl Compatible Regular Expressions), the compilation time of MRegex 1.5 increases with the increase of the number of rules, and its matching speed can meet the requirements of the detection of gigabit network traffic.

In order to reduce the eyelash influencing on iris recognition rate, an eyelashes detection algorithm is proposed based on adaptive threshold. Based on the iris localization, gray morphological operation is used to accurately localize eyelids. According to the gray distribution of the parabolic pixel point after the upper eyelid parabolic moving down, the adaptive threshold is used to segment the eyelashes. The experimental results show that compared with the traditional eyelash detection algorithm, it is not necessary for the algorithm to set up more parameters, which embodies the simplicity to maximize the results of eyelash segmentation.

Many companies and governments have been rapidly progressing and expanding their Web services, and have recently invested a lot of time and money for a safer cyber environment to protect implementation and information assets and personal information. However, web hacking techniques to gain knowledge and evolution of web hacking through the web site are still putting a serious threat to Web services. In this paper, OWASP TOP10, NIS 8 vulnerability, Financial Supervisory Service (FSS) designed according to the simulated hacking scenarios 11 vulnerability to attacks based proposes a method for analyzing the vulnerability by check.

Securities analysts' forecast information can effectively reduce the uncertainty of information in securities markets, and can also promote effective allocation in capital market. The personality difference of securities analysts will lead to different analysis results. In order to improve the utilization of analysts' forecast information, evidential reasoning algorithm under two-dimensional progressive framework and grouping method for combining evidence were used in this paper to fuse securities analysts' stock rating information. Based on the forecast earnings information and stock rating information of analysts, we constructed a two-dimensional progressive framework, and then fused stock rating information of multiple analysts into one piece of evidence information. Finally, we empirically verified the model in this paper by using Chinese analysts' forecast information. The analysis on the fusion results have shown that: compared to traditional statistic model, the accuracy, certainty and the discrimination of the fusion results in our model have been improved.

In order to deal with the issue of network attacks and enhance the security of the network environment, intrusion detection is gaining more and more attention all over the world. In this paper, a novel intrusion detection method based on improved triangular matrix factorization is presented. As a type of famous mathematical tool, triangular matrix factorization has a good ability to reduce the large amount of high dimensional data. However, the traditional triangular matrix factorization has its inherent drawbacks such as the difficulty of setting the parameter adaptively, so the model of an improved version of triangular matrix factorization together with its concrete algorithm is proposed in this paper firstly. Then, improved triangular matrix factorization is employed to convert the high dimensional data of the network into low dimensional vectors of several matrices, with which the anomaly detection can be realized. Experimental results indicate that the proposed method is promising, and it does significantly enhance the detection accuracy and computational efficiency compared with other current popular ones.

In-app Billing service in Android enables the application developers sell digital content from inside the applications. To enhancing security of these applications, there have been presented security guidelines and various security techniques. However, recent automated attacks on every application in a device make the user of the device to get valuable content without paying for them. In this paper we present a novel approach to secure Android In-app Billing service against such automated attacks by detecting these attacks. Before completing the purchase, our approach performs a test to check whether there is an attempt to bypass a legitimate payment process. It is simple so as to be applied easily, and it effectively detects attacks by testing the signature verification process. With this approach, known automated attacks could be detected successfully.

This paper construct the predicted model based on support vector machine (SVM) for the Shanghai Composite Index, acquired the model parameters using genetic algorithm optimization was carried out, combined with k-fold cross method. Experiments based on the start date to February 2011 total 4948 trading day data, 10 fold cross circulation experiments of GA optimization; get the most accurate model parameter of SVM. At last, the regression model is used to predict, and the relative error of regression prediction is 0.11, and the accuracy of regression prediction is higher. In conclusion, this model can be used to predict the Shanghai Composite Index.

Through the analysis of the relationship between current intelligence transportation and large data, after the theory of granular computing concepts involved in preliminary studies, For the current data mining of intelligent transportation ,we presents a Data Mining Model Of Intelligent Transportation Based on Granular Computing. Utilizing granular computing in data mining theory advantages, through constructing a new data mining model to solve the tlarge-scale, complexity, uncertainty and ambiguity problems of massive data from intelligent transportation.

The used algorithm in cryptography represents the facts for compution and/or computation costs in general. The motivation for any problem is primitive generators that makes the protocol a big advantage over the technology augmentation. This manuscript presents a methodological approach on session specific challenge-response protocol for a better, improved and stronger security on reduced costs. The basic primitives are applying on Diffie-Hellman and Elliptic Curve Cryptography. The purpose is proving the security properties for protocol compositional logic that focuses on privacy rights in information assessment in multidisciplinary obligations. In addition, we portrats a signcryption approach for password authenticated key exchange protocol for multilayer consensus, which logically combines individual signature and encryption cost in the form of reduced computational cost and communications cost in single stride of operation. The overall computation time potentially reduces for the proposed methodology on key generation and signature. The results for ECC based multilayer consensus key generation approach are testing on Automated Validation of Internet Security Protocol Architecture (AVISPA) tool and SPAN tool. Further, by preserving the definition of signcryption, we enhanced the same scheme in relations to the other proposed schemes.

Automatic proofreading of judgment document can effectively overcome human factors and ensure the quality of proofreading. The outstanding work in this paper includes following two aspects: The first aspect is to proofread the mistakes of legal file name and legal provision reference by establishing the proofreading knowledge base of judgment document. The second aspect is to maximizing identify legal terminology and common name entities, then proofread the collocation mistakes between words, phrases and legalese by using Markov Model. The experiment results show that this method can basically meet the needs of the judgment documents proofreading.

Sentiment polarity analysis on the microblogging hot topic can better understand the Internet user's attitude and tendency toward a specific event, so that government can effectively guide the public opinion. Different from other methods, the sentiment polarity analysis method put forward in this paper gives full consideration to the expression characteristics of microblogging, a particular network media. It particularly considered the network languages and emoticons when calculated the value of sentiment polarity. In this method, we calculate the value of sentiment polarity of each word firstly by combining Pointwise Mutual Information (PMI) and HowNet. Secondly, modify the sentiment polarity value of a word through syntactic dependencies. Finally, accumulate the sentiment polarity value of each word, so the sentiment polarity value of a microblogging can be obtained. The sentiment polarity value of a hot topic can be obtained in the end, through accumulating the sentiment polarity value for all microblogging in a hot topic. Contrast experiment results show that, the method can obtain the sentiment polarity value of a hot topic more accurately and effectively.

Ad Hoc network is a multi-hop temporary communication network of mobile nodes. Because the lack of infrastructure support in Ad Hoc network, some attacks are more serious than in other type of networks. [1] Therefore security problem in this type of network is a challenging issue. To against the attacks which threat seriously security of Ad Hoc network, a new authentication scheme is proposed. The proposed solution involves three main stages: intermediate nodes pre-authenticating stage, common key ki between n0 and ni negotiating stage and authentication during all routing phases. At the same time, the network simulation of the proposed solution is conducted. The simulation result shows that the proposed solution effectively resists the attacks mentioned above. Meanwhile, the negative affection to the performance of network, such as delay and overheads, is tolerable according to the simulative result. The research in this paper enable us to put forward a reasonable authentication solution during all phases.

In order to satisfy the hardware implementation of the complex image algorithm, this paper gives a model-based design (MBD) workflow for an image processing algorithm applicable for edge detection of an image by Xilinx Spartan 6 FPGA. MBD provides a design flow that directly maps the design into FPGA using functional models of the design specification. Simulation results show that the proposed workflow is not only overcoming the defects of traditional development flow, but also to shorten the time-to-market, raise the quality of final the product.