Kai Xi

A fingerprint based bio-cryptographic security protocol designed for client/server authentication in mobile computing environment

With fast evolution of mobile devices and mobile network, the need of protecting user sensitive information locally and performing secure user authentication remotely become evermore increasing. Bio-cryptography is emerging as a powerful solution which can combine the advantages of conventional cryptography and biometric security. In this paper, we present an efficient bio-cryptographic security protocol designed for client/server authentication in current mobile computing environment, with a reasonable assumption that server is secure. In this protocol, fingerprint biometric is used in user verification, protected by a computationally efficient Public Key Infrastructure (PKI) scheme, Elliptic Curve Cryptography (ECC). The genuine fingerprint information is hidden in the feature vault which is the mixture of genuine and chaff features. Fingerprint features are not only used for biometric verification but also for cryptographic key generation. Our security analysis shows that the proposed protocol can provide a secure and trustworthy authentication of remote mobile users over insecure network. Experimental results on public domain database show an acceptable verification performance. We also tested the computational costs and efficiency of our protocol on the CLDC emulator using Java ME (previous J2ME) programming technology. The simulation results prove that the proposed protocol suits current mobile environment. Copyright

Correlation Keystroke Verification Scheme for User Access Control in Cloud Computing Environment

Cloud security is a major concern that may delay its widespread adoption. User access control (UAC) is the core component of security in cloud computing environment, aiming to ensure that stored data are allowed to be accessed only by authenticated/authorized users. As a typical behavioural biometrics, keystroke dynamics provides a promising UAC solution. The most challenging issue that hinders the wide deployment of keystroke is the high verification error rate. Gunetti et al. proposed a classical n-graph-based keystroke verification method (GP method), which can achieve a low False Acceptance Rate (FAR). However, the GP method suffers from a high False Rejection Rate (FRR) and a severe scalability issue. Thus, GP is not a feasible solution for computing cloud application where scalability is a big issue. In this paper, two keystroke verification approaches (nGdv-V and nGdv-C) are proposed to overcome GPs shortcomings. To reduce high FRR, we designed a new correlation measure using n-graph equivalent feature (nGdv) that enables more accurate recognition for genuine users. Moreover, correlation-based hierarchical clustering is proposed to address the scalability issue. The experimental results show that the nGdv-C can produce much lower FRR while achieving almost the same level of FAR as that of the GP method. Furthermore, 1250 times (when using nGdv-V) and three times (when using nGdv-C(17,4)) authentication speed gains have been achieved.

An alignment free fingerprint fuzzy extractor using near-equivalent Dual Layer Structure Check (NeDLSC) algorithm

Biometric techniques provide a feasible solution for protecting personal information at a high security level. However, biometric features themselves demand protection. As a promising method, fuzzy extractor seamlessly binds a cryptographic key to biometric features, in order to prevent both keys and features being exposed to attackers. Some related research has been done in this area however three major issues are still unsolved, which are : 1) Feature alignment 2) Verification accuracy. 3) Information leakage. In this paper, an alignment-free fingerprint fuzzy extraction scheme is proposed. To eliminate the alignment process, we use the minutia local structure features which has been proved to be stable, discriminative, rotation and shift free. The Dual Layer Structure Check (DLSC) verification scheme is base on the minutia local structure and it achieves a high verification performance. In this paper, we proposed a near-equivalent version of DLSC (NeDLSC) that can be directly employed by the existing bio-cryptographic constructions. Then a new fuzzy extractor scheme which is on the basis of NeDLSC is demonstrated. The preliminary experiments on publicly-available database FVC2002 shows a high verification accuracy.

Mobile device access control: an improved correlation based face authentication scheme and its Java ME application

This paper investigates face authentication based access control solutions for camera‐equipped mobile devices. A new hierarchical correlation based face authentication (HCFA) scheme is proposed, which suits resource‐constrained mobile devices such as mobile phones and personal digital assistants. The idea of HCFA is conducting a partial correlation output peak analysis (analyze the relationship between each cross‐correlation output peak generated from selected sub‐regions of a face), in conjunction with conventional direct cross‐correlation methods. The experimental results on the public domain database demonstrate that the proposed scheme achieved better performance than that of the conventional direct correlation based schemes. Furthermore, HCFA was implemented on the Nokia S60 CLDC emulator using Java ME (previously J2ME) programming technology in order to test the applicability and implementability. The test results show that the proposed algorithm is implementable on mobile devices. It not only shortens processing time but also reduces resource demand significantly, compared with the direct correlation algorithms. Copyright

Compatibility of photographed images with touch-based fingerprint verification software

In this paper, the compatibility of fingerprint images captured with mobile cameras (touch-less) with existing touch-based commercial fingerprint verification software VeriFinger SDK is investigated. The touch-less fingerprint images taken with mobile cameras are different with the fingerprint images captured from touch-based scanners. The research in this paper shows that the commercial fingerprint verification software VeriFinger SDK can load the photographed fingerprint images, and can extract minutiae from the photographed images. Furthermore, the minutiae matching of a sample against a reference have been successfully performed based on the photographed fingerprint images using VeriFinger SDK. This research result will make the mobile fingerprint verification more interoperable which has significant contribution to the security of m-commerce applications.

Dual Layer Structure Check (DLSC) fingerprint verification scheme designed for biometric mobile template protection

Recently biometric fingerprint mobile template protection has attracted research attentions. One major challenge is finding reliable biometric features that are robust against distortion and registration error. It is also desirable that raw fingerprints are not easily recovered once the template has been compromised. In this paper, we propose a new Dual Layer Structure Check (DLSC) fingerprint verification algorithm based on composite features which are reliable, distortion tolerant and registration free. The algorithm shows a great promise for incorporation into existing template protection schemes such as Fingerprint Fuzzy Vault. In addition, the simplicity nature of our scheme makes it easy to be implemented on mobile devices at either software or hardware level. Our experimental results on public domain database FVC 2002 show that the scheme can achieve a low FRR with low FAR.

Statistical analysis and security estimation of fingerprint minutia local structure in bio-cryptographic system

Bio-cryptographic systems, such as Fuzzy Vault and Fuzzy Extractor, can not only verify a person but also protect a pre-stored user feature template. Nearly all of the existing bio-cryptographic systems work in encrypted domain, and hence all biometric features should be transformed from biometric domain to encrypted domain, usually referred to the encoding and decoding process. The selection of biometric features play a vitally important role for the system. Minutia local structure features are considered as one of the most promising biometric features since they are stable, discriminating, alignment free, easy to be encoded and with large feature space. Unfortunately, although this category of features have been proposed for years, very few deep investigations, such as mathematical proof, appear in exisiting literature. In this paper, a comprehensive and detailed analysis of the minutia local structure is provided, covering the following topics: statistical test and analysis, theoretical matching performance estimation and security strength analysis.

A correlation based face verification scheme designed for mobile device access control: From algorithm to Java ME implementation

In this paper, we investigate face recognition based access control approaches dedicatedly designed for camera-equipped mobile devices. We developed a Hierarchical Correlation based Face Verification (HCFV) scheme which is deployable for the most resource constrained mobile devices such as low-end mobile phones with available memory size less than 1MB. The novelty of HCFV is to perform the Partial Correlation Output Peak Analysis (analyze the relations among multiple cross-correlation peaks which are generated from selected sub-regions of a face). The experimental results on the public domain database Yale Face Database demonstrate that the proposed scheme has achieved better performance than using conventional correlation based schemes directly on either full-size or downsized images. Furthermore, in order to investigate the applicability and implementability issues, we have also implemented HCFV on the Nokia S60 CLDC emulator using Java ME programming technology. The experiment shows that HFVC consumes approximately 1/10 memory, 1/6 storage space, and 3.5% processing time in comparison with the result using the conventional correlation methods.

Highly efficient one-time pad key generation for large volume medical data protection

In this paper, an efficient one-time pad key generation scheme using grid or space scroll chaotic attractors is proposed. This key can be used for low cost protection of large volume digital medical data, e.g. real-time monitoring ECG data. The one-time pad key is generated from grid or space scroll chaotic attractors to ensure its high-level randomness. In addition, each communicating party needs neither to pre-store nor to distribute the large number of session keys. Simulation results show that this proposed scheme requires low computational power.

A dual-layer clustering scheme for real-time identification of plagiarized massive multiplayer games (MMG) assets

Theft of virtual assets in massive multiplayer games (MMG) is a significant issue. Conventional image based pattern and object recognition techniques are becoming more effective identifying copied objects but few results are available for effectively identifying plagiarized objects that might have been modified from the original objects especially in the real-time environment where a large sample of objects are present. In this paper we present a dual-layer clustering algorithm for efficient identification of plagiarized MMG objects in an environment with real-time conditions, modified objects and large samples of objects are present. The proposed scheme utilizes a concept of effective pixel banding for the first pass clustering and then uses Hausdorff Distance mechanism for further clustering. The experimental results demonstrate that our method drastically reduces execution time while achieving good performance of identification rate, with a genuine acceptance rate of 88%.