Recently, Han-Chang proposed a flexible chaotic key agreement protocol based on nonce. In this paper, we demonstrate that it is vulnerable to spoofing attack and replaying attack. Furthermore, a secure improvement is suggested, which avoids the flaws while keeping all the merits of the original scheme.
Biometric data is non-renewable and irrevocable, so it is necessary to encrypt in the process of collection, storage and transmission to preserve its security. In this paper, a lightweight block cipher applied in the resource-limited environment is proposed by combining generalized Feistel network with chaotic maps. The cipher employs linear mixing transformations within encryption operation and adopts round keys from chaotic systems. Theoretical analysis and experimental results indicate that the cipher provides fast diffusion speed and high security.
As the number of malware variants has grown rapidly, classification speed has become crucial in security issues. While several techniques for malware variant classification have been proposed, they involve a speed-accuracy trade-off. In an attempt to achieve a speedy and accurate malware variant classification, we thoroughly analyze previously proposed methods and identify a critical performance bottleneck in string-to-string matching. This paper presents and evaluates a technique called I-Filter that enhances the performance of the previous approach, approximate matching. I-Filter has the following novel mechanism, the hash-based equivalent procedure matching technique. Our performance evaluation confirms that a performance improvement of on average 1,043 times through I-Filtering.
As biometric vector may not follow the Gaussian distribution under complex light, pose and accessories, systems often yield unacceptable performance when subjected to impulsive, non-Gaussian noise. This paper adopts signal symmetric alpha stable distribution theory to construct fractional low-order independent component analysis algorithm (FLOD-ICA) and applied FLOD-ICA to solve the partial occlusion face recognition problem. Experiments verified that our proposed scheme is effective for face recognition under partial occlusion.
Galois Field has received a lot of attention because of their important and particular applications in cryptography, channel coding, etc. This paper presents the Reconfigurable Galois Field multiplier used to calculate the Galois field multiplication of different lengths which consists of AND gates and special cells. The special cell makes multiplier architecture easier to extend and calculate arbitrarily length multiplication. The Reconfigurable Galois Field multiplier only uses combinational logic circuits which have been implemented on Xilinx FPGA. The results prove that this work has better performances than other previous similar works.
Several methods have been devised by researchers to facilitate malware analysis and one of them is through malware visualization. Malware visualization is a field that focuses on representing malware features in a form of visual cues that could be used to convey more information about a particular malware. There has been works in malware visualization but unfortunately, there seems to be a lack of focus in visualizing malware behavior. In this paper, we highlight our findings in visualizing malware behavior and its potential benefit for malware classification. Our research shows that malware behavior visualization can be used as a way to identify malware variants with high accuracy.
Medical image survivability and confidentiality is an important concern for digital medical image storing in healthcare institution. Survivability issue arises when a storage server goes down due to unexpected disasters whilst medical image confidentiality issue arises due to disclosed data by third party on a conventional storage. This study explores secret sharing threshold scheme: Rabin's IDA, and Shamir's SSA, as potential approaches to address these issues. Currently, these schemes are widely known for providing data survivability and confidentiality in other fields. However, the aim of this project is to apply these secret sharing schemes through MIaDPACS to provide survivability and confidentiality on digital medical image. Pixels are extracted from the image, encoded and dispersed using Rabin's IDA into distributed storages. In addition, the secret key used in Rabin's IDA is also dispersed through Shamir's SSA. To reconstruct back the original image, it only requires a subset of the dispersed files with numbers equals to a threshold defined during dispersal. Experimental results conducted have shown that MIaDPACS able to provide survivability and confidentiality for digital medical image.
In this paper, we propose a matrix random low-rank approximation (MRLRA) approach to generate cancelable biometric templates for privacy-preserving. MRLRA constructs a random low-rank matrix to approximate the hybridization of biometric feature and a random matrix. Theoretically analysis shows the distance between one cancelable low-rank biometric template by MRLRA and its original template is very small, which results to the verification and authentication performance by MRLRA is near that of original templates. Cancelable biometric templates by MRLRA conquer the weakness of random projection based cancelable biometric templates, in which the performance will deteriorate much under the same tokens. Experiments have verified that (i) cancelable biometric templates by MRLRA are sensitive to the user-specific tokens which are used for constructing the random matrix in MRLRA; (ii) MRLRA can reduce the noise of biometric templates; (iii)Even under the condition of same tokens, the performance of cancelable biometric templates by MRLRA doesn't deteriorate much.
To make use of information contained in the null space of withinclass during the implementation of discriminant locality preserving projection(DLPP), a very efficient feature extraction algorithm called two-dimensional direct discriminant LPP (2D-DDLPP) algorithm is proposed for face recognition in this paper. By modifying the simultaneous diagonalization procedure, the null space of the interclass matrix can be discarded for it carries no discriminative information and the null space of intraclass matrix is preserved for it contains very important information for classification. Also, the 2D-DDLPP algorithm does not need to transform 2D image matrix into a vector prior to feature extraction so that it can be implemented more efficient and accurate than the 1D traditional in extracting the facial features. Therefore, the performance of 2D-DDLPP has been greatly improved. Extensive experiments are performed to test and evaluate the new algorithm using the UMIST and the AR face databases. The experimental results indicate that our proposed 2D DDLPP method is not only computationally more efficiently but also more accurate than the 2DLPP method in extracting the facial features for face recognition.
User authentication is an important security issue for network based services. Multi-server authentication scheme resolves the repeated registration problem of single-server authentication scenario where the user has to register at different servers to access different types of network services. Recently, Pippal et al. proposed a smart card authentication scheme for multi-server architecture. They claimed that their scheme has some advantages and can resist kinds of attacks. In this paper, we analyze the weaknesses of Pippal et al.'s scheme, and point out that their scheme cannot provide correct authentication, cannot resist impersonation attack, stolen smart card attack, and insider attack. Besides, their scheme is non-extensible when a new server added into the system.
Threats which come from database insiders or database outsiders have formed a big challenge to the protection of integrity and confidentiality in many database systems. To overcome this situation a new domain called a Database Forensic (DBF) has been introduced to specifically investigate these dynamic threats which have posed many problems in Database Management Systems (DBMS) of many organizations. DBF is a process to identify, collect, preserve, analyse, reconstruct and document all digital evidences caused by this challenge. However, until today, this domain is still lacks having a standard and generic knowledge base for its forensic investigation methods / tools due to many issues and challenges in its complex processes. Therefore, this paper will reveal an approach adapted from a software engineering domain called metamodelling which will unify these DBF complex knowledge processes into an artifact, a metamodel (DBF Metamodel). In future, the DBF Metamodel could benefit many DBF investigation users such as database investigators, stockholders, and other forensic teams in offering various possible solutions for their problem domain.
Security of information systems is becomes a major concern for many organizations nowadays as security risks may have a serious impact on the organization's information assets. Information Security Management (ISM) describes controls that an organization needs to implement to ensure that it is sensibly managing the risks of loss, misuse, disclosure or damage. Thus, it makes ISM knowledge domain is so complex to both its modeling and sharing. The current ISM models do not provide an apparent structure that can be easily reuse to the current situation without an analysis in -depth and this could lead to a waste of time. It is useful to categories and describes the elements, components or aspects of information security management in a unified conceptual model (metamodel) to facilitate knowledge sharing, reuse, modelling and enhancing the communications amongst ISM users. For this purpose, we proposed the Information Security Management Metamodel (ISMM).
Improving the performance of non-idealistic iris recognition has recently become one of the main focus in iris biometric research. In real-world iris image acquisitions, it is common and unavoidable to capture off-angle iris images. Such off-angle iris images are categorized as non-idealistic because they substantially degrade the performance of iris recognition. In this paper, we present a unified framework designed to improve off-angle iris recognition performance. We propose combination of least square ellipse fitting (LSEF) technique and the geometric calibration (GC) technique for the iris segmentation. For off-angle images, the improper location of iris and pupil interferes with the ability to effectively segment the inner boundary and outer boundary of the iris image. With the proposed techniques, inner and outer boundaries are fitted iteratively. For feature extraction, we propose a NeuWave Network (inspired by the Haar wavelet decomposition and neural network). The iris features are represented using the wavelet coefficients. Each different angle of the iris have its own significant coefficient and these coefficient, with a set of weights, then forms the iris template. The approach is evaluated based on recognition accuracy measured by the false rejection, false acceptance rate, and decidability index. We evaluate the algorithms with WVU-IBIDC datasets.
Homomorphic encryption has become a popular research topic since the cloud computing paradigm emerged. This paper discusses the design of a GPU-assisted homomorphic cryptograph for matrix operation. Our proposed scheme is based on an n*n matrix multiplication which are computationally homomorphic. We use more efficient GPU programming scheme with the extension of DGHV homomorphism, which prove the result of verification does not leak any information about the inputs or the output during the encryption and decryption. The performance results are obtained from the executions on a machine equipped with a GeForce GTX 765M GPU. We use three basic parallel algorithms to form efficient solutions which accelerate the speed of encryption and evaluation. Although fully homomorphic encryption is still not practical for real world applications in current stage, this work shows the possibility to improve the performance of homomorphic encryption and achieve this target one step closer.
Cloud based video surveillance systems have been proposed and implemented recently. With the advances in cloud technologies, opportunity for getting on-demand remote video surveillance service can be pursued. In this paper, we propose a novel remote display solution that allows remote surveillance users to watch real-time surveillance video, to use surveillance software and to share screen updates among users on remote desktop. Multiple encoders and parallel encoding method are adopted in remote display to meet quality of service requirement under varying situations. Our proposed system deals with dynamic workload better than traditional remote display methods since surveillance task and encoding task are separately managed. Two queuing models are designed to handle resource provisioning problem for different encoders.
Ear biometric is slowly gaining its position in biometric studies. Just like fingerprint and iris, the ears are unique and have other advantages over current regular biometric methods. Besides those advantages, there are some issues arising for ear recognition. One of those is regarding the illumination. Low illumination may result in low quality image acquired resulting in low recognition rate. Based on this situation, we proposed a cross-band ear recognition to overcome the variant illumination problem. This method starts by measuring the environments illumination which will determine which type of images (i.e.: thermal or visible) acquired to be processed. Once determined, the images will undergo pre-processing before the ear region is being localized using Viola-Jones approach with Haar-like feature. The ear features will be extracted using local binary patterns operator. Euclidean distance of the feature of test image and database images will be calculated. The lowest Euclidean value will determine the individual identity (intra- and inter-variance).
2DPalmHash Code (2DPHC), which is constructed based on Gabor filter, is a cancelable palmprint coding scheme for secure palmprint verification. In this scheme, multiple-translated matchings between two 2DPHCs are performed to remedy the vertical and horizontal dislocation problems of Gabor feature matrix. According to the analysis, vertical translation matching fixes the vertical dislocation, but the horizontal translation matching does not work out horizontal dislocation. Therefore, the computation of multiple-translated matching of 2DPHC can be reduced by discarding the horizontal translation matching. The matching reduction not only reduces the computational complexity of matching, but also improves the verification performance and enhances the changeability capacity of 2DPHC as a cancelable scheme.
Authentication is one of the essential security features in network communication and ensures the system resources are not obtained by illegal users. In authentication process, the originator of the communication and the respondent will manage some identification codes of each other before to start of the message transaction. Several approaches have been proposed regarding the authentication process from time to time. However, the previous approaches are vulnerable to various attacks. This research introduces a new scheme named plan recognition authentication scheme that use for smart card based on networking system. It is an authentication scheme which is different with existing scheme to ensure and enhance the smart card based authentication and security. All the features of this scheme such as reliability, integrity, confidentiality and accessibility are applied during the authentication process. In this plan recognition scheme, the technique that use to identify authentication with combination of something known and something possessed such as a usage of smart card and password.
The evolution of an information technology has been expended and growth rapidly since last decade, especially in the era of an internet web technology, such as, e-commence, ebusiness or e-payment or e-shopping and more. The evolution of an internet web technology has made the transmission of the data or information over the web is more comprehensive. Thus, the data or information is easy to hack, crack or spy by the unauthorized persons over the network. This paper proposed a technique of cryptography to make the data or information to be more secure during transmission over the internet technology based on the DNA Stenography with the Finite State Machine (Mealy Machine) theory. This proposed algorithm is able to securing the data or information at least 3 levels of combinations for the password conversion.
As use of the internet has become wide spread, many good effects are seen but the adverse functions are also found. One of these adverse functions is the unnecessary personal information exposure. This issue may be a significant problem because there is the potential for so many people to see the information if the information is disclosed by mistake by its collector such as internet service provider. Information can also be disclosed by the person who holds a superior role in the system, namely, the system administrator. Internet users have paid special attention to this issue caused by the fact that many of the operations and transactions that they carry out through the internet can be easily recorded and collected. Thus, identity disintegration has become a desirable feature to be implemented in a database management system. In this paper, we propose an identity disintegration mechanism that is intended for use in the healthcare field.
