Use of Novel Algorithms MAJE4 and MACJER-320 for Achieving Confidentiality and Message Authentication in SSL & TLS

Extensive use of the Internet coupled with the marvelous growth in e-commerce and m-commerce has created a huge demand for information security. The Secure Socket Layer (SSL) protocol is the most widely used security protocol in the Internet which meets this demand. It provides protection against eaves droppings, tampering and forgery. The cryptographic algorithms RC4 and HMAC have been in use for achieving security services like confidentiality and authentication in the SSL. But recent attacks against RC4 and HMAC have raised questions in the confidence on these algorithms. Hence two novel cryptographic algorithms MAJE4 and MACJER-320 have been proposed as substitutes for them. The focus of this work is to demonstrate the performance of these new algorithms and suggest them as dependable alternatives to satisfy the need of security services in SSL. The performance evaluation has been done by using practical implementation method.

Studies on some nonlinear optical phenomena-optical phase conjugation and continuous wave second harmonic generation

Nonlinear optics has emerged as a new area of physics , following the development of various types of lasers. A number of advancements , both theoretical and experimental . have been made in the past two decades . by scientists al1 over the world. However , onl y few scientists have attempted to study the experimental aspects of nonlinear optical phenomena i n I ndian laboratories. This thesis is the report of an attempt made in this direction. The thesis contains the details of the several investigations which the author has carried out in the past few years, on optical phase conjugation (OPC) and continuous wave CCVD second harmonic generation CSHG). OPC is a new branch of nonlinear optics, developed only in the past decade. The author has done a few experiments on low power OPC in dye molecules held in solid matrices, by making use of a degenerate four wave mixing CDFWND scheme. These samples have been characterised by studies on their absorption-spectra. fluorescence spectra. triplet lifetimes and saturation intensities. Phase conjugation efficiencies with r espect to the various parameters have been i nvesti gated . DFWM scheme was also employed i n achievi ng phase conjugation of a br oadband laser C Nd: G1ass 3 using a dye solution as the nonlinear medium.

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

Use of Novel Algorithms MAJE4 and MACJER-320 for Achieving Confidentiality and Message Authentication in SSL & TLS.

Extensive use of the Internet coupled with the marvelous growth in e-commerce and m-commerce has created a huge demand for information security. The Secure Socket Layer (SSL) protocol is the most widely used security protocol in the Internet which meets this demand. It provides protection against eaves droppings, tampering and forgery. The cryptographic algorithms RC4 and HMAC have been in use for achieving security services like confidentiality and authentication in the SSL. But recent attacks against RC4 and HMAC have raised questions in the confidence on these algorithms. Hence two novel cryptographic algorithms MAJE4 and MACJER-320 have been proposed as substitutes for them. The focus of this work is to demonstrate the performance of these new algorithms and suggest them as dependable alternatives to satisfy the need of security services in SSL. The performance evaluation has been done by using practical implementation method.

Development & evaluation of different acoustic models for Malayalam continuous speech recognition

Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%.

Continuous production of L-glutaminase by an immobilized marine Pseudomonas sp BTMS-51 in a packed bed reactor

A marine Pseudomonas sp BTMS-51, immobilized by Ca-alginate gel entrapment was used for the production of extracellular Lglutaminase under repeated batch process and continuous process employing a packed bed reactor (PBR). Immobilized cells could produce an average of 25 U/ml of enzyme over 20 cycles of repeated batch operation and did not show any decline in production upon reuse. The enzyme yield correlated well with the biomass content in the beads. Continuous production of the enzyme in PBR was studied at different substrate concentrations and dilution rates. In general, the volumetric productivity increased with increased dilution rate and substrate concentrations and the substrate conversion efficiency declined. The PBR operated under conditions giving maximal substrate conversion efficiency gave an average yield of 21.07 U/ml and an average productivity of 13.49 U/ml/h. The system could be operated for 120 h without any decline in productivity

Continuous Production of Extracellular L-Glutaminase by Ca-Alginate-Immobilized Marine Beauveria bassiana BTMF S-10 in Packed-Bed Reactor

L-Glutamine amidohydrolase (L-glutaminase, EC 3.5.1.2) is a therapeutically and industrially important enzyme. Because it is a potent antileukemic agent and a flavor-enhancing agent used in the food industry, many researchers have focused their attention on L-glutaminase. In this article, we report the continuous production of extracellular L-glutaminase by the marine fungus Beauveria bassiana BTMF S-10 in a packed-bed reactor. Parameters influencing bead production and performance under batch mode were optimized in the order-support (Na-alginate) concentration, concentration of CaCl2 for bead preparation, curing time of beads, spore inoculum concentration, activation time, initial pH of enzyme production medium, temperature of incubation, and retention time. Parameters optimized under batch mode for L-glutaminase production were incorporated into the continuous production studies. Beads with 12 × 108 spores/g of beads were activated in a solution of 1% glutamine in seawater for 15 h, and the activated beads were packed into a packed-bed reactor. Enzyme production medium (pH 9.0) was pumped through the bed, and the effluent was collected from the top of the column. The effect of flow rate of the medium, substrate concentration, aeration, and bed height on continuous production of L-glutaminase was studied. Production was monitored for 5 h in each case, and the volumetric productivity was calculated. Under the optimized conditions for continuous production, the reactor gave a volumetric productivity of 4.048 U/(mL·h), which indicates that continuous production of the enzyme by Ca-alginate-immobilizedspores is well suited for B. bassiana and results in a higher yield of enzyme within a shorter time. The results indicate the scope of utilizing immobilized B. bassiana for continuous commercial production of L-glutaminase

Characterizations of some continuous distributions using partial moments

Inthis paper,we define partial moments for a univariate continuous random variable. A recurrence relationship for the Pearson curve using the partial moments is established. The interrelationship between the partial moments and other reliability measures such as failure rate, mean residual life function are proved. We also prove some characterization theorems using the partial moments in the context of length biased models and equilibrium distributions

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.