K. R. Venugopal

Heartbeat biometrics for human authentication

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like the electrocardiogram (ECG) of a person is unique and secure. In this paper, we propose an authentication technique based on Radon transform. Here, ECG wave is considered as an image and Radon transform is applied on this image. Standardized Euclidean distance is applied on the Radon image to get a feature vector. Correlation coefficient between such two feature vectors is computed to authenticate a person. False Acceptance Ratio of the proposed system is found to be 2.19% and False Rejection Ratio is 0.128%. We have developed two more approaches based on statistical features of an ECG wave as our ground work. The result of proposed technique is compared with these two approaches and also with other state-of-the-art alternatives.

Authentication using Finger Knuckle Prints

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like the finger knuckle print (FKP) of a person is unique and secure. Finger knuckle print is a novel biometric trait and is not explored much for real-time implementation. In this paper, three different algorithms have been proposed based on this trait. The first approach uses Radon transform for feature extraction. Two levels of security are provided here and are based on eigenvalues and the peak points of the Radon graph. In the second approach, Gabor wavelet transform is used for extracting the features. Again, two levels of security are provided based on magnitude values of Gabor wavelet and the peak points of Gabor wavelet graph. The third approach is intended to authenticate a person even if there is a damage in finger knuckle position due to injury. The FKP image is divided into modules and module-wise feature matching is done for authentication. Performance of these algorithms was found to be much better than very few existing works. Moreover, the algorithms are designed so as to implement in real-time system with minimal changes.

Statistical Analysis for Human Authentication Using ECG Waves

Automated security is one of the major concerns of modern times. Secure and reliable authentication of a person is in great demand. A biometric trait like the electrocardiogram (ECG) of a person is unique and secure. In this paper we propose an authentication system based on ECG by using statistical features like mean and variance of ECG waves. Statistical tests like Z −test, t −test and χ 2 −tests are used for checking the authenticity of an individual. Then confusion matrix is generated to find False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). This methodology of authentication is tested on data set of 200 waves prepared from ECG samples of 40 individuals taken from Physionet QT Database. The proposed authentication system is found to have FAR of about 2.56% and FRR of about 0.13%. The overall accuracy of the system is found to be 99.81%.

Human Authentication Based on ECG Waves Using Radon Transform

Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like electrocardiogram (ECG) of a person is unique and secure. In this paper, we propose a human authentication system based on ECG waves considering a plotted ECG wave signal as an image. The Radon Transform is applied on the preprocessed ECG image to get a radon image consisting of projections for θ varying from 0 o to 180 o . The pairwise distance between the columns of Radon image is computed to get a feature vector. Correlation Coefficient between feature vector stored in the database and that of input image is computed to check the authenticity of a person. Then the confusion matrix is generated to find False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). This methodology of authentication is tested on ECG wave data set of 105 individuals taken from Physionet QT Database. The proposed authentication system is found to have FAR of about 3.19% and FRR of about 0.128%. The overall accuracy of the system is found to be 99.85%.

DTCWT based high capacity steganography using coefficient replacement and adaptive scaling

The steganography is used for secure communication. In this paper we propose Dual Tree Complex Wavelet Transform (DTCWT) based high capacity steganography using coefficient replacement and adaptive scaling. The DTCWT is applied on cover image and Lifting Wavelet Transform2 (LWT2) is applied on payload to convert spatial domain into transform domain. The new concept of replacing HH sub band coefficients of DTCWT of cover image by LL sub band coefficients of payload is introduced to generate intermediate stego object. The adaptive scaling factor is used based on entropy of cover image to scale down intermediate stego object coefficient values to generate final stego object. It is observed that the capacity and security are increased in the proposed algorithm compared to existing algorithms.

Covariance Based Steganography Using DCT

The confidential information is communicated through the open channel in a covert way by using steganography. In this paper we propose the Covariance based Steganography using Discrete Cosine Transform (CSDCT) algorithm. The Average Covariance of the Cover Image (ACCI) is computed and threshold ACCI value is fixed at 0.15. The cover image is segmented into 8*8 cells and the Least Significant Bit (LSBs) are replaced by Most Significant Bits (MSBs) of payload based on ACCI values. It is observed that the capacity, Peak Signal to Noise Ratio (PSNR) and security is better compared to the existing algorithm.

Multisource Keyword Extraction and Graph Construction for Privacy Preservation

Privacy preservation is an important branch of Data Mining which handles hiding of an individuals sensitive data without affecting the data usability. This paper proposes a new technique to provide privacy preservation of sensitive data based on the semantic context. Multisource Keyword Extraction and Graph Construction for Privacy Preservation involves extracting keywords from various data formats and preserving privacy among the keywords extracted using the techniques of Vector Marking. Initially, data cleaning and preprocessing is done on the document to extract keywords by applying techniques such as parsing, duplicate elimination, stemming and indexing. The document can be either PDF, SQL or Word files. After preprocessing, a context graph is generated from the keywords extracted with the help of context dictionaries such as WordNet and DBpedia. This context graph acts as a primary source of reference for all user queries. Privacy preservation of sensitive information is achieved using various Vector Marking techniques. The data input by the user can be classified as structured, unstructured and semi-structured data. Appropriate Vector Marking approaches are used for the given input data format. The keyword specified by the user in the input data as private is queried in the context graph to obtain the correlated words and these words are hidden from the access of the other users. Thus solving some of the issues related to privacy leakage.

RePID-OK: Spam Detection Using Repetitive Pre-processing

Email proves to be a convenient and powerful communication tool but it has given rise to unwanted mails. Spam mails leads to wastage of server storage space, consumption of network bandwidth and heavy financial losses to the organization, thus a serious research issue. Filtering mails is one of the popular approaches used to block spam mails. In this work, we propose RePID-OK (Repetitive Preprocessing technique using Imbalanced Data set by selecting Optimal number of Keywords) model for spam detection. Using the data set Ling-Spam, we show that efficiency of the proposed model is more powerful and effective than existing schemes. The performance of the proposed RePID-OK has been checked across the identified parameters and also evaluated against other existing models, thus demonstrating the efficiency of the proposed technique over other models in this area of research.