Database intrusion detection using sequence alignment

Information is considered to be the most valuable asset of any organization and hence, it should be securely maintained. However, rapid proliferation of the Internet and Web applications has increased the threat of information security breaches. Traditional database security mechanisms are often not sufficient to protect sensitive information against novel attacks. Intrusion detection systems (IDS) are used to detect any such intrusion, once traditional security mechanisms have been compromised. User-level profile is effective for database intrusion detection, but maintaining such profiles is not practical for an organization with a large number of users. Thus, an IDS needs to be flexible enough to choose a profile granularity according to the type of the organization. Further, only intra-transactional pattern matching for intrusion detection is not quite effective for detecting intrusion in a database. We propose an IDS that uses inter-transactional as well as intra-transactional features for intrusion detection. It supports selection of profile and transactional feature granularity as well. We use sequence alignment as a tool for comparing database access patterns of genuine users and intruders.     

State-based modeling and object extraction from echocardiogram video

In this paper, we propose a hierarchical state-based model for representing an echocardiogram video. It captures the semantics of video segments from dynamic characteristics of objects present in each segment. Our objective is to provide an effective method for segmenting an echo video into view, state, and substate levels. This is motivated by the need for building efficient indexing tools to support better content management. The modeling is done using four different views, namely, short axis, long axis, apical four chamber, and apical two chamber. For view classification, an artificial neural network is trained with the histogram of a region of interest of each video frame. Object states are detected with the help of synthetic M-mode images. In contrast to traditional single M-mode, we present a novel approach named sweep M-mode for state detection. We also introduce radial M-mode for substate identification from color flow Doppler 2-D imaging. The video model described here represents the semantics of video segments using first-order predicates. Suitable operators have been defined for querying the segments. We have carried out experiments on 20 echo videos and compared the results with manual annotation done by two experts. View classification accuracy is 97.19%. Misclassification error of the state detection stage is less than 13%, which is within acceptable range since only frames at the state boundaries are found to be misclassified.     

An analysis of radioactive corrosion product transfer in sodium loop systems

A solution-precipitation model for radioactive corrosion product transfer in LMFBR primary circuits and experimental sodium loops is discussed. Expressions are given for the quantity released to flowing sodium from steel undergoing bulk corrosion. The observed super-stoichiometric release of ⁵⁴Mn and sub-stoichiometric release of cobalt isotopes are attributed to high and low relative solubilities in sodium, respectively. It is shown that relative solubility values are required for calculating ⁵⁸Co and ⁶⁰Co release but not for calculating ⁵⁴Mn release. An expression is given for the quantity deposited onto a surface undergoing either bulk corrosion or bulk deposition. This is reduced to a table of simple relationships which is used to interpret experimental data. It is thereby concluded that ⁶⁰Co deposition is controlled by diffusion in the liquid and ⁵⁴Mn deposition is likely to be controlled by solid-state diffusion at high temperatures and bulk deposition at low temperatures.     

Raman Amplification in Multimode Fiber

We demonstrate that the Raman gain of the fundamental mode in graded-index multimode fiber (MMF) is comparable to that of standard single-mode fiber using the same pump power. Moreover, we show that mode-selective gain is significantly enhanced by the radial dependence of the GeO₂ concentration in these fibers. The mode-selective gain is also shown, via impulse responses and eye diagrams, to reduce the intersymbol interference for near center-launch excitations and thereby enhance high-speed MMF link performance     

Broadband scalable model for Si‐RF on‐chip spiral inductors with substrate eddy current effect

A new broadband scalable compact model for on‐chip spiral inductor is presented. It includes a substrate network and a high resistive component to accurately capture the substrate eddy current effect, skin and proximity effects at high frequencies. The proposed model shows a good match with the measurement results over a frequency range of up to 20 GHz. An automated parameter extraction and optimization procedure has been developed using equivalent circuit analysis and particle swarm optimization. We achieved good scalability for all model parameters with respect to spiral layout geometry. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.     

Occlusion detection and gait silhouette reconstruction from degraded scenes

Gait, which is defined as the style of walking of a person, has been recognized as a potential biometric feature for identifying human beings. The fundamental nature of gait biometric of being unconstrained and captured often without a subject’s knowledge or co-operation has motivated many researchers over the last one decade. However, all of the approaches found in the literature assume that there is little or no occlusion present at the time of capturing gait images, both during training and during testing and deployment. We look into this challenging problem of gait recognition in the presence of occlusion. A novel approach is proposed, which first detects the presence of occlusion and accordingly extracts clean and unclean gait cycles from the whole input sequence. In the second step, occluded silhouette frames are reconstructed using Balanced Gaussian Process Dynamical Model (BGPDM). We evaluated our approach on a new data set TUM-IITKGP featuring inter-object occlusion. Algorithms have also been tested on CMU’s Mobo data set by introducing synthetic occlusion of different degrees. The proposed approach shows promising result on both the data sets.