Earticle

Digital content industry is the core of emerging cultural industry. If it wants to realize the transformation from “Platform is king” to “Content is king”, it needs the external technology’s support. Content and technology restrict each other and develop jointly. Both of them promote the development of the digital content industry fundamentally. This article makes an analysis of content and technology’s present situation that base on a new point of view, and analyzes digital content industry’s developing status quo and problems from the microscopic level, then it proposes the idea of “content bank” , and shows that content bank’s operating system to promote the digital content industry to develop rapidly and healthily.

Power Analysis Attack is a type of side-channel attack that uses power consumption of a cryptographic device to reveal the sensitive information. Power Analysis Attack is causing a serious threat to the embedded systems like smart cards. So there is a need to secure embedded systems from power analysis attack. In this paper, various methods of power analysis attack are addressed. The power analysis attack experimental setup using SASEBO-W is depicted and the various countermeasures are proposed. Performance comparison of counter measures are analyzed and tabulated.

This paper discusses the security of the clock synchronization algorithm based on the biological example of Asian Fireflies in wireless sensor networks. Huge swarms of these fireflies use the principle of pulse coupled oscillators in order to synchronously emit light flashes to attract mating partners. When applying this algorithm to real sensor networks, the potential threat of hostile flashes may disturb this synchronization. An improved Reachback Firefly Algorithm is implemented in the MAC layer of wireless sensor networks (WSNs), which change coupling strength among oscillators to anti hostile attack in clock synchronization. Its security is analyzed through a Susceptible-Infective-Recovered epidemic model. Numerical results and simulations are provided for further understanding of the analysis.

To meet the demand of digitizing progress of pharmaceutical retail industry, there are various kinds of software are made for pharmaceutical retail enterprise. However, much commercial software on the market fails to meet the demand of data transmission safety. Therefore, a novel system was designed for medium size pharmaceutical retail enterprise with multiple branches. It is designed to digitize the process of retail operations including management of stock, order client, staff, product, branch and warehouse. Advanced Encryption Standard (AES) algorithm was used to secure the data transmission on the Internet. The system can be deployed1 in pharmaceutical retailing, hospital prescriptions issues, pharmaceutical company management, medical supplies market, medical devices market and hospital staff management. With minor modification the system can be deployed to other retail or wholesale industry.

Wireless sensor network consists of several resources constrained sensor nodes that are positioned in distant and un-navigable areas to monitor and sense various environmental conditions in the areas of interest. The sensor nodes arrange themselves into a network with the help of routing protocols. The sensor nodes instead of communicating the information individually to the base station, the information is sent to the transient cluster head, further it is communicated to the base station after computation. This is done to reduce the energy utilization incurred by the communication over head. In order to efficiently manage the energy level of cluster head, the cluster head should be well equipped with suitable computation processes that generate appropriate quality information to be communicated to the base station. Such computational processes are referred to as aggregation techniques. This paper proposes a refined data aggregation technique that aims at reducing the energy consumption at the same time preserving integrity and increasing security of aggregated data based on statistical approaches.

WLAN (wireless local area network) connect the users and the network by using radio frequency signals. It reduces network cabling between the terminals and the network equipment. Thus WLAN has the following benefits: giving end users a great deal of mobility, convenience, saving network cabling project costs. WLAN can share the wireless traffic of 2G or 3G network. But WLAN authentication from the safety and convenience of comprehensive consideration has not been a fine solution. This paper analyzes the various existing problems of authentication used in the field of WLAN. A fast authentication method is proposed in this article considering the character of the terminal user. Compared with existing authentication methods, this method is fast, it improves the system applicability under the comprehensive consideration of accessibility and safety. This method is validated by experiments, so that users can easily access secure WLAN systems.

The time and cost saving for banks when implementing cloud computing strategies are staggering. However, it is important to consider the security and protection of data when it comes to the widespread adoption of cloud. Fully homomorphic encryption is currently still undergoing experimentations. One of its limitation is the time required to encrypt and decrypt the sensitive data, as the traditional encryption systems showed a level of resistance and considerable maturity that can be rehabilitated or hybridized for application in the field of sensitive data protection hosted in the Cloud. In this paper we will propose hybrid homomorphic system that will be applied to the banking data to perform operations on encrypted data without decrypting, based on the encrypting, the decryption and the operation treatment time on the ciphertext which were obtained by simulating an addition and multiplication homomorphic cryptosystem and comparing it with DGHV that is somewhat homomorphic; then we will choose our model which is most suitable for banking application.

Fingerprint recognition systems are the top topics of biometric research and more researchers’ effort is provided to improve high accuracy and speed. Matching methods based on the minutiae points are commonly used and are effective in practice. Algorithms which based on minutia triplets among them are attractive matchers. However, recognizing fingerprints in poor quality images, direction changed, size different fingerprints and so forth is still a very complex job. To overcome these drawbacks, a fingerprint match method used minutiae-based triangular acreage is described here to improve matching accuracy.

Smart electricity meter sealing plays a key role in the automation and test management to electricity smart meter device. Compared with traditional lead sealing and two-dimensional code sealing, advantages of smart electricity meter sealing based RF tags include more convenient, more intelligent, more automated, and more secure. A new kind of smart electricity meter sealing based on RF tag is designed and produced, which conforms to meter device identify specification drafted by State Grid Corporation. Data structures, communication protocols, and secure mutual authentication protocol about this sealing are described. Particularly, this mutual authentication protocol is suitable for low-cost RF tags, and meets the State encryption control requirements for commercial encryption products. This sealing can provide integrity and confidentiality protection properties, prevents unauthorized access and tampering, and avoids illegal cloning.

There are always VANETs malicious nodes attempt to disrupt the message during normal delivery in the routing protocol of VANETs (Vehicular Ad hoc Networks). At the same time due to the dynamic changes of the vehicle, so that the topology of VANETs changes rapidly, it is very easy to make the communication link of vehicles attacked, or there is no reliable disconnection phenomenon. Based on this, it presents a secure and stable cooperative with node VANETs routing protocols (RSVR). First regular intervals to detect signal strength, residual energy and interface queue length, and then check the data transmission, while the message load and transfer process certificate for authentication, and then set the collaborative monitoring message passing node in the routing protocol, for messages can not be delivered to the destination node, which will serve as the task of passing messages, and adjust the final routing allows data transmission can selectively defense, or selective forwarding data. Experimental results show that RSVR packet delivery rate increase 15%, to consider combining overhead and latency, etc., it come in a wide range of node RSVR intensive environment, that has better reliability and security.

In order to determine the conditions for the application of the dynamic authorization problem in the Internet of things, a reliable trust mechanism must be established between the institution, the reader and the tag. Thus, this paper proposes a hierarchical trust mechanism, and puts forward a verifiable caching interaction digest schema at the same time. At first, this paper analyzes the features of the application and the trust demands of different subjects in the Internet of things, the credibility of the detaching mechanism and the reader trust. Then, it proposes the improved method of evidence theory accoording to the characteristics of the readers, which can deduce the routing trust of the reader. The experimental results show that the hierarchical trust mechanism has a very good convergence of trust, and the algorithm in this paper can effectively detect the malicious terminal nodes.

Authentication between user and server has become more and more important in the insecure network. Chen et al’s proposed a user-participating authentication scheme. The CAPTCHA techniques and visual secret sharing is used in their scheme. The scheme can complete mutual authentication and resist certain known attacks. But for password guessing attack and denial-of-service attack, it can not resist. Therefore, an improved scheme to eliminate these weaknesses is proposed in this paper.

Safety driving performance estimation and alertness (SDPEA) has drawn the attention of researchers in preventing traffic accidents caused by drowsiness while driving. Psychophysiological measures, such as electroencephalogram (EEG), are accurately investigated to be robust candidates for drivers’ drowsiness evaluation. This paper presents an effective EEG-based driver drowsiness monitoring system by analyzing the changes of brain activities in a simulator driving environment. The proposed SDPEA system can translate EEG signals into drowsiness level. Firstly, Independent component analysis (ICA) is performed on EEG data to remove artifacts. Then, eight EEG-band powers- related features: beta, alpha, theta, delta, (alpha plus theta)/beta, alpha / beta, (alpha plus theta)/(alpha plus beta) and theta / beta are extracted from the preprocessed EEG signals by employing the Fast Fourier Transform (FFT). Subsequently, fisher score technique selects the most descriptive features for further classification. Finally, Support Vector Machine (SVM) is employed as a classifier to distinguish drowsiness level. Experimental results show that the quantitative driving performance can be correctly estimated through analyzing driver’s EEG signals by the SDPEA system.

As Wireless Sensor Networks (WSNs) are usually deployed in remote or even hostile environment, the adoption of security mechanism is fundamental. To achieve secure communication between sensor nodes in WSNs, it is important to establish efficient key predistribution schemes. Unfortunately, key management scheme is a challenging issue for WSNs because of the resource limitations in the sensor nodes. In this paper, we propose an efficient key management scheme for WSNs, which assigns the key spaces to sensor nodes via combinatorial design. In the scheme Finite Projective Plane is mapped to obtain efficient key distribution scheme. Connectivity, resistance against attacks, storage and communication overhead are studied analytically and computationally. Compared to related schemes, the proposed scheme performs better against compromised node attacks.

One-way authentication and key agreement scheme can achieve strong user anonymity and transmitted data confidentiality over insecure public communication channel, which is very useful for the user who cares about his/her identity information. In conventional networks, Public Key Infrastructure (PKI) is a very useful component to design one-way authentication key agreement scheme. However, it will consume large amounts of computing resources. Therefore, it is inappropriate to PKI in a resource-constrained environment. In this paper, we proposed a new one-way authentication and key agreement scheme based on Chebyshev chaotic map. Compared with the related research activities, our proposed scheme has not only the high efficiency and unique functions, but also robust to various attacks and achieves perfect forward secrecy. Security and performance analyses demonstrate that the proposed scheme can solve various types of security problems and can meet the requirements of computational complexity for low-power mobile devices.

The encryption algorithm has disadvantages like the long key making memory difficult and uneasy safekeeping, which causes a potential threat to the information security. Therefore, a new direction of the encryption method research is to combine the biometric information with the traditional encryption algorithm. The key extracted from the iris and AES encryption algorithm are used in the image encryption algorithm. The db2 wavelet decomposition to the iris region is performed, and the third level high frequency coefficient is extracted as the iris feature codes, from which a 192 bit key is generated by using the stochastic mapping function. The randomness of the key extraction is analyzed. The proposed algorithm is employed to do the encryption test to the image. The encryption effect is compared with the scrambling encryption effect of the classic Arnold method. The experiment results show that security of the encryption image gained by using the proposed algorithm is higher, achieving the purpose of protecting image information.

Software systems often contain plenty of code clones, which bring significant impact on software development and maintenance. Tracking clones in the evolution process is essential to analyzing clones, since we cannot understand clone phenomenon well just rely on the clone detection results of single version. We developed a function clone genealogy extractor, cGen, which can track clones across multiple versions to extract type-1 and type-2 function clone genealogies. By using cGen, we examine nine open source C projects and analyze their evolution. Our study shows that cGen can efficiently extract clone genealogies from multiple versions of a project, and provide support for clone evolution analysis.

New Approach to observe web Access beside Usage of information measure victimization Intrusion Detection System could be a comprehensive web use observation and news utility for company networks. It takes advantage of the very fact that the majority companies give web access through proxy servers, like MS ISA Server, MS Forefront TMG, WinGate, WinRoute, MSProxy, WinProxy, EServ, Squid, Proxy Plus, and others. Whenever the user accesses several websites, transfer files or pictures, these actions were logged. The system processes these log files to supply system directors a good vary of report-building choices. It might build reports for individual users, showing the list of internet sites visited, beside elaborate classification of web activity (downloading, reading text, viewing footage, observation movies, paying attention to music, and working). This technique might produce comprehensive reports with analysis of overall information measure consumption, building easy-to-comprehend visual charts that show the areas wherever wasteful information measure consumption has eliminated. This new approach is employed to observation the web information measure employed by the user. victimization this technique will simply decide that user fill the information measure most heavily, when, and what specifically they transfer, what proportion time they pay on-line, and what knowledge transfer traffic they produce.

Ad Hoc network is a multi-hop temporary communication network of mobile nodes equipped with wireless transmitters and receivers without the aid of any current network infrastructure. [1] Due to lack of infrastructure support, security problem in these networks is a challenging issue. There exist previous work that studied the performance of the network under different types of security attacks. In this paper, complementary research by providing more realistic network scenarios such as various protocol used in the network is made. We consider two common types of attacks, black hole attack and gray hole attack, based on both AODV and DSR protocol respectively. We study the performance of the network in different number of malicious nodes and on different protocol via observing the metrics of a connection such as packet delivery ratio, throughput and end-to-end delay. The simulation result shows that the performance of the network based on both routing protocol is similar. It is should be noticed that the end-to-end delay is different in two routing network. The results enable us to put forward some suggestions to minimize the impacts of the above types of attacks in Ad Hoc network.

As a kind of accurate, rapid and real – time data acquisitions and processing technology, RFID can give unique identification to entity object, has been widely used in various industries, such as manufacturing, sales, transportation and so on. But with its widely application, many relevant problems, especially the safety issues of RFID system and the low cost issue of label have been raised more and more attention by people; therefore, a new and more appropriate security authentication protocol becomes necessary. In this paper, firstly introducing several now available security authentication protocols, and analyzing their strengths and drawbacks, then proposed a new authentication scheme based on Hash function, doing security properties and feasibility analysis of it in theory, and proving that the security properties of this scheme is more efficient, and it is more applicable to meet the needs of people through test at last.

In this article, the development of integrated security model for the next generation using big data technology is proposed. The main objective of this model is to make a paradigm shift from managing separate security to managing integrated security with real time basis monitoring of hacking attacks which are coming from all kinds of security input channels, using big data analysis technology. This new model technology can be a more enhanced approach than conventional security technology in terms of detection and response speed. This new model will contribute to governance and management of security in many areas significantly.

Intrusion detection systems (IDS) play an important role in defending network systems from insider misuse as well as external attackers. Compared with misuse-based techniques, anomaly-based intrusion detection techniques perform well in detecting new attacks. Firstly, this paper proposes a feature selection algorithm based on SVM (termed FS-SVM) to reduce the dimensionality of sample data. Moreover, this paper presents an anomaly-based intrusion detection algorithm, i.e., multiclass support vector machine (MSVM) with parameters optimized by particle swarm optimization (PSO) (termed MSVM-PSO), to detect anomalous connections. To verify the effectiveness of these two proposed algorithms (FS-SVM and MSVM-PSO) and the detection precision of MSVM-PSO, this paper conducts experiments on the famous KDD Cup dataset. This paper compares MSVM-PSO with three commonly adopted algorithms, namely, Bayesian, K-Means, and multiclass SVM with parameters optimized grid method (MSVM-grid). The experimental results show that MSVM-PSO outperforms these three algorithms in detection accuracy, FP rate, and FN rate.

Objection of this research is to introduce a development model and a function to secure agents who working in field of protection to VIP, counterterrorism, disaster and safety control, and salvage requiring of brilliant security equipment to increase ability to deal with business. This research tried to give an explanation of purpose of this study by dividing development model into 4 areas. This device could monitor to confirm concentration, fatigue, mental change, checking life or death also could monitor location of agents through GPS system in real time. These lead finally for increasing business efficiency In this study, typical case sampling method was used. This is a method which can be claimed that same things can be shown in other cases if somethings were shown in some cases. Information for objects of study should be specifically provided in this method of study because this study is for specific location, objects, and cases so introduction to location and participant for study were needed. In this study, academic fields are divided as Security(Protection to VIP, Counterterrorism, Disaster and Safety Control, Salvage), Medicine(Otolaryngology, Neurosurgery, Neuropsychiatry, Ophthalmology) and Engineering(Information Technology, hardware production) and specialists who have over 10 year work experiences or doctoral and philosophy degree and specialists are chosen as fields and then we have sufficient information for study from each participant for 6 months. Finally, results of this study are conformed from participants to secure reliability and validity of results of this study. I would like to wish this product become popular and helpful to agents on site for security assurance and public order in the future.

The traditional static detection method for malicious JavaScript detection has high efficiency without the need of code executing, but it cannot detect new malicious script. While the dynamic method usually needs to execute code and extract features, which lead to low efficiency and highly difficulty. In this paper, we propose a half-dynamic detection method for classification, which can solve the problem of obfuscated malicious JavaScript. The proposed method starts with obtaining the intermediate-state machine code using the JavaScript interpreter to compile the JavaScript. After extracting the function calling sequence of machine code, the feature model of the sequence is built using N-gram. Then we use k-NN classifier for training and detecting the malicious script. N-gram can directly be used to statically analyze the sequence of the obfuscated JavaScript, but not available to recognize the maliciousness. Then N-gram on the call function sequence of the compiled machine code is proposed as an efficient half-dynamic malicious script detection method. Finally, the efficiency and effectiveness of the proposed method is demonstrated through the experiments.

Selection of cohort models plays a vital role to increase the accuracy of a biometric authentication system as well as to reduce the computational cost. This paper proposes a novel approach for cohort selection called Max-Min-Centroid-Cluster (MMCC) method. The clusters of cohorts are generated by K-means clustering technique. The union of the clusters having largest and smallest centroid value is taken as cohort subset. The cohort scores, after normalization using different cohort based score normalization techniques, are used in authentication process of the system. Evaluation has been carried out on FEI face datasets. The performance of this novel methodology is analyzed using T-norm and Aggarwal (max rule) normalization techniques. Experimental results exhibit the efficacy of the proposed method.

In this work, we are going to use thermal aware approach in Encoder design and also testing thermal stability by working on different ambient temperatures 298.15K, 308.15K, 318.15K, 328,15K, 338.15K and 348.15K and 358.15K. We have observe the compatibility of our device with wireless network by working on different I/O standards (LVCMOS15 and LVCMOS25) . There is 30.29% reduction in leakage power, when we scale down temperature from 358.15K to 298.15K using LVCMOS15 as I/O standard on 40nm Virtex FPGA. Leakage power is calculated for 65nm FPGA and 90nm FPGA as well .In this work, we are using Verilog Hardware Description Language.

Embedding data into smooth regions introduces stego-images with poor security and visual quality. Edge adaptive steganography, in which the flat regions are not employed to carry a message at low embedding rates, was proposed. However, for the high embedding rates, smooth regions are contaminated to hide a secret message. In this paper, we present an adaptive multi-layer block data-hiding (MBDH) algorithm, in which the embedding regions are adaptively selected according to the number of the secret message bits and the texture characteristic of a cover-image. Via employing the MBDH algorithm, more secret message bits are embedded into the sharp regions. Therefore, the smooth regions are not used, even at high embedding rates. Furthermore, most of edge adaptive steganography algorithms have a limited capacity when the smooth regions are not employed in data hiding. The proposed scheme solves this issue when it can embed more secret bits into the selected regions while the perceptual quality of stego-images is still maintained. The experimental results were evaluated on 10,000 natural gray-scale images. The visual attack, targeted steganalysis, and universal steganalysis are employed to examine the performance of the proposed scheme. The results show that the new scheme significantly overcomes the previous edge-based approaches and least significant bit (LSB) based methods in term of security and visual quality.

The authenticity and the integrity of digital evidence are critical issues in digital forensics activities. Both aspects are directly related to the application of The Locard Exchange Principle (LEP), which is a basic principle of the existence of evidence in an event. This principle, not only applies before and at the time the event occurs, but also applies to the investigation process. In the handling of digital evidence, all activities to access the digital evidence are not likely to occur without the mediation of a set of instruments or applications, whereas every application is made possible for the existence of bugs. In addition, the presence of illegal access to the system, malicious software as well as vulnerabilities of a computer system are a number of potential problems that can have an impact on the change in the authenticity and the integrity of digital evidence. If this is the case, secure and trust characteristics that should appear in the activity of digital forensics may be reduced. This paper tries to discuss how the concept of a secure and trusted environment can be applied to maintain the authenticity and integrity of digital evidence. The proposed concept includes the unity of five components, namely standard and forensics policy, security policy, model and trusted management system, trusted computing, secure channel communication, and human factor. The ultimate purpose of this paper is to provide an overview of how the recommendation can be applied to meet the requirements of a secure and trusted environment in digital forensics for keeping the authenticity and the integrity of digital evidence. In general, this paper tends to explain a high-level concept and does not discuss low-level implementation of a secure and trusted environment.

In this paper, a novel scheme is proposed for watermarking lossy compressed images just before transmission and authenticating them once they are received, away from the core of the compression and de-compression processes. The scheme is inserted into the Joint Photographic Expert Group (JPEG) structure that is encoded using the Discrete Cosine Transform (DCT) at specified locations. The watermark information is extracted from and embedded into specified DCT coefficients, following novel criteria. The scheme is robust to lossy compression; though it is fragile, exposing any slight changes of the probe images. The scheme is also blind, needs no prior information about the original image or the watermark information to authenticate the received image. Experimentally, if the received watermarked data is not manipulated, the proposed scheme verifies them as ‘authenticated’. On the other side, if geometrical or image processing attacks are applied to the watermarked images, they are then verified successfully as ‘not authenticated’. The proposed scheme is further evaluated and compared to similar authentication schemes. The noise added to the original image due to embedding the watermark information is 0.063 dB (decibel), overcoming all results in the reviewed literature.

In this paper, a robust adaptive repetitive control algorithm is presented for periodically time-varying systems. Periodic time-varying parameter estimation through periodic learning algorithm, and the uncertainty of aperiodic was robust adaptive method. Different from the existing repetitive control, this paper introduces the design of a new variable cycle number control. Convergence error when the number increase will gradually decrease due to the cyclical repetition character system, in order to ensure the global asymptotic stability. Further, this method is applied to a class of nonlinearly parameterized systems with non-parametric disturbances, and the tracking error converges asymptotically. The results verify the simulation model of the inverse pendulum. In addition, it is proved that the proposed design method is applied to eliminate the influence of approximation error of neural network. Theoretical analysis shows that the system output is convergent to the desired one and all signals in the network based robust adaptive repetitive control system are bounded. The experimental result illustrates the effectiveness of our proposed methodology.