Tohari Ahmad

Pair-polar coordinate-based cancelable fingerprint templates

Fingerprint-based authentication has been widely implemented, however, security and privacy of fingerprint templates still remain an issue. Some schemes have been proposed to protect fingerprint templates, such as the design of cancelable fingerprint templates. Yet, most of the existing schemes rely on accurate fingerprint image registration, which is very hard to achieve, especially considering the need to avoid storing any information related to the raw fingerprint features. In this paper, a pair-polar coordinate-based template design method is developed which does not need registration. The proposed scheme explores the relative relationship of minutiae in a rotation- and shift-free pair-polar framework. A many-to-one mapping is applied to ensure the non-invertible recovery of raw templates. A random translation parameter is introduced to further distort the minutia distribution. Under various scenarios, the proposed scheme is evaluated using the public databases, FVC2002DB1, FVC2002DB2 and FVC2002DB3. The experiment results show that the new method satisfies the template protection requirements and the performance degradation caused by the transformation is very low.

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

An Efficient Mobile Voting System Security Scheme Based on Elliptic Curve Cryptography

The wide-spread use of mobile devices has made it possible to develop mobile voting system as a complement to the existing electronic voting system. However, due to limited onboard resource, it is challenging to achieve both efficiency and security strength for mobile voting system. Conventional solution is to either use symmetric encryption algorithms or hybrid symmetric and asymmetric algorithms at the expense of weaker security strength. In our proposed mobile voting scheme, the users’ votes are secured by using the elliptic curve cryptography (ECC) algorithm. ECC is chosen as it has smaller key size than other public key cryptographies; and its homomorphic encryption property which is able to keep users’ anonymity. We evaluate the method of ECDH with AES and ECC in comparison with our proposed method. The experiment demonstrates that our proposed ECC based scheme can outperform the traditional hybrid symmetric and asymmetric cryptographic scheme in the context of mobile evoting environment.

Generating cancelable biometrie templates using a projection line

Biometrie authentication systems can address the problems of genuine user verification and usability suffered by the conventional cryptosystems based on the password and token. However, as biometrics is not replaceable, its privacy has become a concern. Also, if the same biometrics is used in multiple applications, it will be vulnerable to potential cross-matching attacks. In this paper, a projection line method is proposed for cancelable fingerprint template design. The main advantage of this method is its simplicity. Because there exist many possibilities projecting minutia into the projection line controlled by the whole range of possible projection line properties, the proposed approach offers non-invertible transformation and also possess good revocability property.

String-based cancelable fingerprint templates

Cancelable (revocable) fingerprint templates have been proposed to protect fingerprint data. However, many of them have incurred significant authentication performance degradation. In this paper, we propose a cancelable fingerprint template design mechanism to protect fingerprint data while maintaining a satisfactory authentication performance. The proposed scheme transforms fingerprint minutiae points into a vector string which serves as the cancelable fingerprint template. The results of the experiment carried out using a public database FVC2002DB2 show that it meets the requirements of revocability, diversity and security for cancelable fingerprint templates, in addition to the low error level.

Increasing the Performance of Difference Expansion-based Steganography when Securing Medical Data

Steganograpy has been widely used for hiding secret data in various types of other data, such as images, audio, or video. In order to obtain this secret data, an extraction algorithm is used according to the respective steganographic embedding algorithm. Nevertheless, many data hiding methods have three common problems: reversibility or obtaining both secret and cover data in the extraction process, similarity between cover data and stego data, and the size of the secret data that can be hidden. In this paper, we focus on the last two problems while still maintaining reversibility (the first problem) by proposing four methods which are developed based on Difference Expansion. In the first three methods, we use a threshold to control the stego image quality, while in the fourth we use the smoothness level instead of a threshold value. In these proposed methods, we use text and images as the secret and cover data, respectively, where the secret data is embedded into the difference of pixel blocks. The size of these blocks varies. In addition, the difference is reduced before the secret data is embedded. The experimental results show that the secret data as well as the cover data can be reconstructed to be exactly the same as the original. Furthermore, both the capacity of the secret data and the similarity level increase for certain block sizes.

Falls Detection and Notification System Using Tri-axial Accelerometer and Gyroscope Sensors of a Smartphone

Fall situations can be risky especially for elderly people with health problems. This fact has highlighted the need of fall detection systems. Various fall detection systems have been proposed. The proposed systems commonly used special devices placed at several position of users body. On the other hand, smartphones with various sensors including gyroscopes are available in the market nowadays. This has motivated us to propose a prototype system of fall detection application designed for a smart phone. A threshold based fall detection algorithm is adapted for the proposed system since it relatively requires lower computational processes compared to complex reasoning techniques. Hence is more suitable to be implemented in smart phones with limited resource and processing power. The basic idea of the algorithm is to detect dynamic situations of posture, followed by unintentional falls to lying postures. The algorithm monitors sets of linear acceleration data and angular velocity and compares them to set of thresholds obtained from training data from the observed user. The process to detect a fall situation followed by sending notification to colleagues can be done in real-time manners while still maintain high accuracy for certain fall situations.

Cartesian and polar transformation-based cancelable fingerprint template

Fingerprint authentication systems suffer from security and privacy issues since it needs to store the fingerprint template in the database. Once this data is compromised, the effect is forever as it can not be revoked. In this paper, we propose a local feature-based cancelable fingerprint template scheme. The experimental result which is generated by using a public database, FVC2002DB2, shows that it has a low error level and also meets the security and privacy requirements, such as revocability and diversity.

Shared secret-based steganography for protecting medical data

Medical data (i.e., medical image and medical record) is private which should be protected before being transferred or stored. There have been some methods proposed by implementing various algorithms, such as steganography. It is sometimes combined with the shared secret method, so that, the reconstruction of the original data must be done by some users. It is believed that this method increases the security of the data. However, there is still a need to make the stego data (i.e, stego image) has an as good as possible quality. This means that the stego image has high similarity to the cover (carrier) image. In this paper, we propose methods to protect the medical data by using the shared secret mechanism and steganography for 2 and 1 bit LSB. The experimental results show that they produce relatively good quality (similarity) in terms of PSNR.

Increasing performance of IDS by selecting and transforming features

Dealing with problems of network security in the information age is absolutely necessary so that data exchanged or stored in a network can be maintained from the threat. Numerous studies have shown that the use of Intrusion Detection System (IDS)-based machine learning can be used to overcome the accuracy problem. Dimensionality reduction approach to optimize the detection process has also become the focus. However, there is still a need to improve the results of previous research. In this paper, we propose a method to perform dimensionality reduction which can optimize the intrusion detection process by limiting the size of the clusters and the usage of sub-medoids to form new features. The results of this research show that the proposed system is able to provide better results than the existing. This can also be depicted by the increase of sensitivity and specificity values.