Earticle

Digital watermarking technology plays an important role in the areas of copyright protection and identity tracing for owners of digital mediums. At present, the security of the watermarking scheme is facing a great threat. The security of a digital watermarking scheme must not depend on the scheme being kept secret. Zero knowledge-based watermark detection scheme (ZKWD) can achieve this aim. For ZKWD scheme, an owner can provide prove to a verifier that a digital medium in question indeed contains the owner’s watermark information without revealing any secret key and watermark-related information. However, the existing ZKWD protocols are still facing some challenging problems, such as ambiguity attacks. In this paper, a public ZKWD protocol is proposed for plain text, and the homomorphic property of asymmetric encryption algorithm in the multiplication operation is used to prevent the owner from cheating by ambiguity attacks. Compared with existing methods, the security of our proposed ZKWD scheme is improved by using the improved feature extraction algorithm.

Liao et al.’s has recently announced the suitable authentication scheme for mobile device environment, which can authenticate remote users by using QR code. However, Liao et al.'s scheme cannot satisfy several important security requirements. The biggest drawback of Liao et al.'s scheme is that it is not able to satisfy the mutual authentication between remote users and SP since it is vulnerable to eavesdropping, man-in-the-middle, theft and loss of mobile devices and forgery attack. This paper aims to analyze the problems of Liao, et al., scheme and propose a safe authentication scheme using password based QR code that has fixed the aforementioned vulnerabilities.

Risk evaluation is the core process of information security risk management. An effective risk evaluation can protect organizations and maintain their abilities to carry out missions and activities against threats as well as helping to implement controls and safeguards that are actually needed. While the traditional information security risk evaluation approaches are lack of granular analysis and clear expression of security characteristics of risk, such as the possibility, attack path, and business impact. This paper presents the scenario-based information security risk evaluation method, based on the thought of Advanced Persistent Threat (APT) attack, by constructing risk scenario, evaluate information system security risk status. The separation analysis of the technical impact and business impact contribute to the technicians and business decision makers to grasp system risk status from their respective responsibilities. In the end of the paper, we propose a practical risk scenario construction example, which provides scientific and effective guidance for the preparation of a risk evaluation report.

To avoid fighting and violence occurred in the elevator, this paper proposed an abnormal behavior detection method based on SVM to achieve real-time monitoring. Firstly, the corners of the video sequences were detected and the Lucas-Kanade algorithm was used to calculate the optical flow to obtain velocity vector information. Secondly, this algorithm established a feature vector combining the corner kinetic energy with movement characteristics of targets (including change rate of area, change rate of external rectangle length-width ratio, distance between the targets and the angle difference of target movement direction) as the basis of violent behavior detection. Finally, SVM classifier was constructed to identify the violent behavior. The experiment results showed that the method could detect violent behavior in the elevator effectively and the algorithm was with less complex calculation and higher detection rate thus it could alarm real-time.

The images of different areas require different test results on the edge. In this paper, the images of red blood cells in medical field need to be detected theirs cell size, roundness, number and other features. For the test requirements, an image edge detection algorithm is proposed based on improved Canny operator. This algorithm calculates the optimal high and low dual-threshold by using iteration arithmetic, and uses mathematical morphology to thin the detected images. The results proved that this algorithm can effectively reduce interference and noise edge and make more prominent detection characteristics, which is good ready for subsequent processing of the image.

The process of routing in MANET (Mobile ad hoc network) requires a trust based environment and therefore security is one of the major concern. A backbone network in a MANET is difficult when it is implemented for a specific application. A security based environment is one of the most critical issues in a MANET because it is mostly involved with sensitive and secret information. This work deals with a specific type of denial-of-service (DOS) attack called node isolation attack and thus analyze the vulnerabilities of a pro-active routing protocol called optimized link state routing (OLSR). Based on this analysis, this work proposes a mechanism called enhanced OLSR (EOLSR) protocol which is a trust based technique to secure the OLSR nodes against the attack. According to the proposed technique, isolation can be detected by the hello packets it sends. Verification is done through this, whether a node is advertising correct topology information or not thus leading to detection of the isolation node that perform the DOS attack. Enhanced OLSR is further improved using the trust based system called Trustbased OLSR (TOLSR). Once the node is detected as attacker using EOLSR, its trust value is reduced to half of its initial value. Hence in future, selection of attacker as MPR node is prevented since all the nodes will select only high trust node as MPR node. The concept of ensuring security to the network does not involve much computational complexity and therefore, the proposed scheme is a light weight technique.

Extenics and rough set theory are brought into transformer fault diagnosing procedure in this paper to get rid of abundant information data and to obtain more precise diagnosing result. Using the dissolved gas data as fault diagnosing attribution set, attributions which are needed for transformer fault diagnosis are predigested and preliminarily grouped by means of rough set method, and then matter element model for transformer’s fault diagnosing is built. With the transformer’s standard fault modes as the transformer’s fault diagnosing decision set, utilizing extenics association function to calculate each fault degree, acceptance and rejection rule is defined to diagnose transformer’s fault. 76 dissolved gas information data have been collected to verify the method proposed in this paper, the diagnosing results show that the correctness of diagnosing results got by this method is better than frequently used IEC three ratio methods.

Failure types of Information Systems are varied, which leads to the long duration for locating faults, and decreases the quality of customer service or income. In order to accurately and timely locating BOSS faults, a cascading neural network ensemble was proposed. In the proposed ensemble, the approach of ensemble was used to promote the accuracy of locating faults, and the cascading structure was employed to decrease the time duration of locating. The proposed approach used in fault location BOSS achieved the following results: (1) the speed of locating faults has been improved; (2) complaint rate from customers has been reduced; (3) the billing losses have been decreased.

As this era is known as Electronic era where everything is associated with Internet and its growing number of security threats. In our study, we focused on three different e-mail account securities, comparatively. First, by performing an analysis on online E-mail service providers we concluded that what type of functionalities they are providing to secure their user’s information. Second, we categorized users in to three types and on the basis of that we study on user’s view on online security, confidence and usability on their E-mail service provider. Third, we evaluate the outcome of our study which emphasizes the user’s precautions from protecting their accounts from unauthorized access. The goal is to analyze how users perceive the security of their email account based on the domain in which it was created. We will start by examining different free email providers based on their security and perform a comparison of their features. Then will follow a risk assessment of the information security system as perceived by some students and business users. The reality analysis will allow us to examine and possibly classify the email providers based on their security parameters and users account protection levels. A final comparison will then be made between the results of the reality and the perception analysis to put in evidence their differences and similarities.

One of the most important tools in security field is Intrusion Detection System. The aim of the IDS is to monitor suspicious network traffic and generate alerts. These systems are known to generate numerousfalse positive alerts. Analyzing the alerts manually by security expert need more time and could be error prone.Another problem with IDS is Identifying attack types and generating correct alerts related to attacks.we introducenew alert management systems to overcome mentioned problems. Alert management systems help security experts to manage alerts and produce a high level view of alerts. In this paper a new alert clustering algorithm for IDS Alert Management System proposed that uses the K-mean Based Genetic (KBG). The proposed algorithm reduces alerts and detects false positive alerts. By the experimental results on DARPA KDD cup 98 the system is able to cluster and classify alerts and causes reducing false positive alerts considerably.

In Software Defined Networking (SDN) architecture, the control plane is separated from the data plane. On one hand, OpenFlow switches can only store and forward packets, which leaves all decisions to be made by the controller. On the other hand, the controller has a global view over the SDN. But if any switch is captured by an adversary, it may mislead the controller to make inaccurate decisions which may have terrible influences on the overall networks. In this paper, we elaborate on these problems and propose methods to detect malicious OpenFlow switches. We set a threshold value of the traffic-flows across an OpenFlow switch. If the switch’s current traffic-flows exceed the threshold value, the controller has reasons to believe that this switch is suspicious and may monitor it intensively. Another scheme is to add a third-party server to accept users’ report to warn the controller. In SDN, the controller cannot communicate with users directly, and sometimes users need to feed back their experience to the controller to help improve the SDN. In this case, it is necessary to set a third-party server in SDN to act as a middle role. These two schemes help to detect malicious switches. The controller can analyze the flow table of the suspicious switch and identify whether it is really malicious before isolating it.

The integration of Wireless Body Area Networks (WBANs) with cloud computing will enable users (including physicians and nurses) to globally access the electronic healthcare data at competitive costs. However, some new issues on data access control are associated with the integration of WBANs and cloud computing. In order to address these issues, we propose a lightweight trust-based access control model, where the users can acquire their access control privileges for the electronic healthcare data according to the user role and trust value in the trust certificates. Simulation results show that our method can better alleviate the communication overhead and energy consumption problem.

This paper studies about bit plane watermarking. The watermarking has been studied to protect digital image against illegal copyright action. Generally speaking, adding watermarking symbol in least significant bit (LSB) is desirable. However, sometimes watermarking information in LSB can be lost during the compression and transmission. Therefore, well designed watermarking technique is necessary. In this paper, we show how to design watermarking application, and compare watermarking performance on different bit plane. Two datasets were used; they are Kodak and McM datasets.

Access control is a process which control users to execute some operations of access some network resource according to the users identify of attribution. This paper analyzes current access control model, and extends the RBAC (role based access control) model, and based on which we propose a trust based access control model in Multi-domain environment (MD-TRBAC). Design a heap-based trust management mechanism for MD-TRBAC Model, which is used to control the cross-domain access resource among different domains. The MD-TRBAC model can provide more security, flexible and dynamic access control mechanism, and therefore improve both the security and the reliable of authorization mechanism.

Use of personalized security mechanisms among financial sectors is gaining rapid momentum day-by-day. Banking and e-shopping portals, which are paramount of cyber-attacks, strongly recommend that both the merchant (i.e., a merchant web portal) and its customers (customers using these portals) be certain about each other’s identity. This emphasizes not only that the merchant portal must be able to detect an attacker spoofing the identity of one of its customers, but also that a customer must not leave her secrets with a fraud-cum-look-alike website spoofing address of the merchant’s portal.This thesis envisages a novel, scalable approach to detect a fraud, look-alike web page to help a customer unaware of digital certificates, Internet security policies and their glitches, truly recognize her merchant’s web-site using her smartphone. The approach uses a reverse challenge-response framework; and uses QR codes which are generated dynamically and depend on the GPS parameters of the customer. The customer uses her smartphone to scan the QR codes with an application provided by the merchant; which detects correctly whether she logged on to the genuine website. The additional benefit of this approach is that it can be modelled to offer a novel, non-telephonic two-step authentication system with minor modifications.

Privacy threat is one of crucial issues for the wide deployment of Vehicular Ad-hoc Networks. Due to the open nature of the wireless communications, many kinds of attacks such as eavesdropping and traffic analysis can be launched by various malicious adversaries. Network coding allows intermediate nodes to encode/mix incoming message, thus it can provide a feasible way to thwart effectively eavesdropping and traffic analysis attacks. Inspired by newly developed secure network coding solution, we propose a privacy preservation scheme for online service access in VANET. The proposed scheme can achieve data confidentiality and flow untraceability, and protect the identity and location privacy of vehicles. Moreover, because lightweight coding operation is performed on message content instead of computation-expensive public key encryption, the proposed scheme is much more efficient than traditional privacy preservation scheme, such as Mix-net and Onion Routing based scheme. Finally, security analysis and simulation demonstrate the validity and efficiency of the proposed scheme.

To solve the seafood quality and safety information table missing data problem, a method for filling missing data based on rough set was proposed. This method first determine whether there is missing data in information table, if there is, then the information table is divided into two parts, one for the complete information table, and the other part is totally incomplete information table, and then complete the information sheet structure similar matrix to calculate the attributes importance, then calculate the number of missing attributes in incomplete information table, and the calculated results conjunctive operation to fill the missing data. If it is not, then output directly. Numerical examples show that the method can be used filling the missing data in seafood quality and safety information table effectively.

Analysis of human emotion plays an important role in interaction between human and machine communication. The most expressive way to extract and understand of human emotion is by facial expression analysis. This paper proposes a novel recognition method of multiple emotions from facial expression running on mobile environments. Especially, we formulate the classification model of facial ambiguous emotions using a variance of the estimated facial feature points. First, we extract 65 landmark points from input stream using active appearance model, and we then analyze the changes of the values of the feature points to recognize a facial emotion by comparing with fuzzy k-NN classification. Finally, five types of the emotions are recognized and classified as a facial expression. To evaluate the proposed approach, we assess the ratio of success with iPhone camera views, and we achieve the best 93% accuracy in the experiments. The results show that the proposed method performed well in the recognition of facial emotion on mobile environments, and the implementation system can be represented by one of the example for augmented reality on displaying combination of real face video and virtual animation with user’s avatar.

Software security is one of the most considerable domains of software development. It provides a strong mechanism to manage and incorporate security features for precious estimation at design phase. The structural and behavioral design properties of classes, objects and their relationships are evaluated to develop metric for authorization. The assessment of security using the model is more appropriate and its validation signifies the valid impact of structural and functional information of object oriented design software. The authorization quantification model is developed using multiple linear regression technique on object oriented design constructs. The applied statistical analysis on this study concludes its statistical significance remarked that calculated data is highly acceptable. A strong theoretical basis has been developed for designing the metrics required for complexity factors as well as security attributes.

In view of the existing IDS are widespread the problem of high false alarm rate, this paper proposes a kind of alarm information filtering method of IDS based on support vector machine (SVM). The method consists of two parts, training, and data prediction. Model training including parsing command line parameters, read the training sample, select the appropriate penalty coefficient, kernel function and kernel parameter, statistical types and the number of each type of sample, sample training data grouping, using the minimum sequence optimization algorithm C - SVM classifier model. Training data to predict including read alarm data and based on the model of C - SVM classifier model calculation values of decision alarm data. Theoretical analysis and experimental data show that the rational selection of kernel function and kernel parameters and the training data set, this method can effectively reduce the intrusion detection system false alarm rate.

As for illumination variation, traditional feature extraction methods are not satisfactory for face recognition. A block discriminant analysis algorithm is proposed to solve the problem. Firstly, local contrast enhancement is used to compensate for uneven illumination; secondly, discrete cosine transform (DCT) is implemented for divided image blocks. According to data distribution of DCT matrix, the block candidate features are selected, and merged to candidate features; finally, block discriminant analysis are carried out for features extraction. Experiments are tested on Yale and Yale B, the results prove the algorithm outperform related algorithms.

Currently, with the increasing number of embedded applications, the research for the security of embedded systems has become popular. Considering the requirement of integrity and security, the characteristics and the design constraints of embedded systems, a method of constructing software trusted root and a trunk-branch trusted chain transfer model is proposed. The software trusted root is composed of boot loader and reliable kernel. SHA-1 engine which is included in boot loader (burned in boot flash), measures and loads the trusted kernel and protect the boot loader by prohibiting kernel and user-level application to write to flash. SHA-1 and trusted kernel together can be used as a trusted root to withstand non-physical attacks. Trusted kernel contains virtual trusted platform module (vTPM) module which can provide cryptographic functions and related services to the user kernel and guides flash to open up specific memory for platform configuration register (PCR) of vTPM. Application is running as a process of the trusted kernel. In the trunk-branch trusted chain transfer model, boot loader verify the trusted kernel, trusted kernel authenticate users kernel, and kernel users verify the application, thus the trust extents to the application layer. The proposed method not only avoids the trust attenuation problem which may occur in chain transfer, but also raises the low efficiency caused by using only ETPM to measure reliability in the star model. Finally, a prototype system is given, and the test results show that this method has built a trusted computing environment for embedded applications on existing hardware and software resources without additional hardware.

In this paper we propose a Hamming Distance Deviation Matching Approach (HDDMA) for Iris recognition. Our HDDMA approach is different from the traditional iris matching method based on Hamming Distance. Firstly we use the odd symmetry Gabor filters with single frequency and two directions to extract iris edge information. Secondly we use zero-crossing detecting method to encode the filtering results． Finally we construct the HDDMA parameter for iris matching. Comparison experiments between the traditional Hamming Distance matching method and the proposed HDDMA are conducted on five iris datasets. The experimental results show that the equal error rate and the correct recognition ratio of the HDDMA are better than those of the traditional Hamming Distance matching method consistently in all iris datasets and the HDDMA has strong anti-eyelid and eyelash noise capability．

In this paper, we propose a blind watermarking scheme based on dual transform domains of discrete wavelet transform and discrete fractional random transform. In order to achieve the robustness and security, we also use the visual secret sharing scheme to split the secret image into two shares and use hologram quantization to spread the watermark information and analyze the cover image detail. For the purpose of widely practical application, we use a QR code for the watermark information. The QR code is decomposed into two shares, the first share is generated by the random seed, and the second share is generated with the help of secret image and the first share. Firstly, the two shares are respectively transformed into a hologram by using the hologram quantization, and then a discrete fractional random transform is applied to them. The cover image is decomposed by two-dimension discrete wavelet transform. The subband generated watermark then is embedded into the intermediate frequency components of the cover image. The watermark extraction process is the reverse of the embedding process. Because of the spectrum characteristic and tear resistant of the hologram, the algorithm has good invisibility. The experimental results show that the proposed algorithm is effective and robust against JPEG loss compression, cropping, rotation and noise.

Personal cloud computing is user-oriented service to satisfy user service demand in existing cloud circumstance and personalized service is available whenever, wherever. However due to personal cloud market is growing rapidly, accidents such as unauthorized user access, leak of secret information, service invasion are occur and existing wire or wireless network communication had been threaten on security. Also the studies about user certification and data management are required. So this paper suggested key generating protocol for user certification and user authority. In addition, it designed safe contents transfer protocol for user by using generated key value. It analyzed the security with referring security service requirement of existing personal cloud service.

In this paper, we propose a multi-layer selection and mining methods for effective intrusion detection, which utilize feature selection, classification, clustering and evidence theory for decision making. In the experiments, DARPA KDD-99 intrusion detection data set is used for evaluation. It shows that our proposed classifier not only classifies and separates the normal and abnormal data, but also reduces false positive and false negative besides detecting all four kinds of attacks.

In this paper, we proposed roles and responsibilities of cyber intelligence in cyber operations. In particular, we focused on the roles and responsibilities of cyber intelligence on each phase of cyber operations. Cyber operations are activities related to defense, assurance, and attack to achieve objectives in or through cyberspace. While cyber operation is conducting, cyber intelligence must properly support cyber commander and units for ensuring cyberspace intelligence superiority. Cyber intelligence is a cyber-discipline that exploits a number of information collection and analysis approaches to provide direction and decision to cyber commander and cyber operation units. This is a key role in both cyber-attack and cyber defense. We know that the branch of information and communications conducts cyber operations in cyberspace. But we don’t know well that the cyber intelligence is more in charge of the policy, strategic, and tactics in cyber operations. It is collected information requested from cyber command and units, and is disseminated information to department related to cyber operations. The cyber intelligence is a key factor in cyber operation cycle.

Strong designated verifier proxy signature (SDVPS) enables a proxy signer to sign messages on behalf of an original signer, and only the designated verifier can be convinced of the validity of the proxy signature, and the verifier cannot prove it to any third party. It is a combination of proxy signature and strong designated verifier signature. In this paper, we define a new formal definition and a new security model of existential unforgery of SDVPS, and then analyze a recently proposed SDVPS scheme, and give four attacks to the scheme, and further we give out an improved SDVPS scheme, and prove it in the new security model. Performance analysis shows the improved scheme is efficient and suitable for electronic commerce.