Abstract

The word Spoong has been defined differently by different people but the one that is used in this context is as follows: “Spoofing is a scenario in which a person or a program successfully impersonates another identity by falsifying the data and thereby gaining illegitimate advantage.” As the definition goes, spoofing is generally used by the malicious users to trick the victims into making inappropriate actions. These actions may or may not be profitable for the attackers but will surely affect the victims. The spoofing attacks are possible when the attackers are able to exploit the trust relationship between the entities. Hence, spoofing attacks are easy to implement in the scenarios where the authentication procedure between the communicating entities is weak. Though spoofing is not an attack by itself, it is an important step in many of the other dangerous attacks. Due to its effectiveness and ease of implementation, the usage of spoofing has been increasing. In the context of online world, many forms of spoofing have been observed. For an effective utilization of the available resources and in a secure fashion, the spoofing attacks need to be checked in the network. The present day Internet can be viewed as a huge network in which the users request services from the servers and servers provide them. Hence, the users and the servers are considered as the important actors of the Internet. Studies show that both these actors are susceptible to spoofing attacks. So, in this thesis we aim to focus on the following two most important spoofing techniques which are affecting these actors of the Internet: • IP Spoofing, which plays a major role in Denial of Service (DoS) attacks to bring down the servers and • Profile Spoofing in social networks, which enables privacy evasion of the social networking users. In order to mitigate IP spoofing attacks on the server, we have proposed a Hop-Count (HC) based Defensive Mechanism against IP Spoofing (DMIPS) scheme which can filter the spoofed packets effectively and also improves the overall network performance. The Quality of Service (QoS) also has been improved by reducing the number of false positives. At the user side, we focus on the online social networks where numerous attempts are being made by various people to extract private information from the users. This is done by deceiving the users by profile spoofing and then getting more information than they are allowed to get. To mitigate this attack, we have designed a challenge-response based scheme which assists the users in identifying their friends and differentiating them correctly which enables easy and efficient privacy management.

Abstract

Recent studies in classification have proposed ways of exploiting the association rule mining paradigm. These studies have performed extensive experiments to show their techniques to be both efficient and accurate. In this thesis, we propose Perturbed Frequent Itemset based Classification Techniques (PERFICT), a novel associative classification approach based on perturbed frequent itemsets. Most of the existing associative classifiers work well on transactional data where each record contains a set of boolean items. They are not very effective in general for relational data that typically contains real valued attributes. In PERFICT, we handle real valued attributes by treating items as (attribute,value) pairs, where the value is not the original one, but is perturbed by a small amount and is a range based value. We propose a pre-processing step based on perturbation as an alternative to the standard discretization step to convert real valued attributes into ranges. The PERFICT approaches are built on the Apriori frame-work for frequent itemsets generation. We also propose our own similarity measure which captures the nature of real valued attributes and provide effective weights to the frequent itemsets. This MJ similarity measure inherently prunes away the unnecessary frequent itemsets. The probabilistic contributions of different frequent itemsets is taken into considerations during classification. Some of the applications where such a technique is useful are in signal classification, medical diagnosis and handwriting recognition. Experiments conducted on the UCI Repository datasets show that variants of PERFICT are highly competitive in terms of accuracy in comparison with popular associative classification methods, decision trees and rule based classifiers. We developed PERICASA, PERturbed frequent Itemset based classification for Computational Auditory Scene Analysis(CASA), as an application to HistSimilar PERFICT. It provides a novel architecture for perception of sound waveforms. The purpose of this model is to develop a classifier which can correctly identify audio waveforms from noisy sound mixtures i.e. to solve the classical ‘Cocktail Party Problem’. The architecture is based on Gestalt principles of grouping like Pragnanz, Proximity, Common Fate and Similarity. The primary idea is that more the ease with which we can identify different associated feature values, easier it is to identify the sound waveform.

Abstract

General purpose computing on graphics processor units (GPGPU) has attained widespread acceptance in the high-performance computing community. This has largely been at- tributed to the rise of programming models and large peak performance to cost ratio of the GPU. The peak throughput of modern GPUs are typically 5 TFLOPS at a cost of 600 US $. These upper limits are found only for applications that have a regular and low frequency memory access. Many algorithms which have a computational model orthogo- nal to the GPU model, especially in the domain of graph theory, have been traditionally not known to be well suited for the GPU model. Graph theoretical algorithms are considered as one of the fundamental building blocks for Computer Science in general. They are considered impractical on many of the current high performance platforms because of the large dependence on irregular data movement, which in the GPU context is a major performance bottleneck. In this context, we focus on fundamental primitives with applications for graph theory, with a large number of immediate applications Typical primitives related to graph theory, can be divided into  Graph primitives: Graph primitives include traversal, connectivity algorithms, path based algorithms etc.. In this thesis, we have dealt with connectivity algorithms such as connected components, spanning tree and spanning forest.  Generic Primitives: Graph theory applications rely not just on domain specic primitives, but primitives from other domains play a signicant role especially in large graph operations on parallel machines. One such primitive is the Range Query Primitive (esp Minima and Maxima). We present a GPU specic implementation of range queries and use it to answer queries such as LCA, minimum/maximum element in a subtree etc.. All the primitives rely on an array based representation, and focus on reducing the dependence on the hierarchical structure of the graph. Problems such as minimum key in a subtree are converted into equivalent problems (Range Query) that have a solution more suited to the GPU model. Also, solutions presented here try to reduce data movement by exploiting data level as well as functional data movement redundancies. Thus the focus is on handling data movement judiciously. We show that the results we have obtained on data sizes tting the GPU are faster than results on any hardware currently present in literature.

Abstract

The exponential growth of the World-Wide Web has transformed it into an ecology of knowledge in which highly diverse information is linked in an extremely complex and arbitrary manner. At the same time, huge multilingual content is being added to it through various sources like blogs, news articles and several other forms. To facilitate the access of this enormous multilingual content, Cross Lingual Information Access systems (CLIA) are vital. CLIA systems take users’ information need and returns the required information to them. The information can be obtained from various sources and different languages, reducing the effort of user to search in different information sources. Query translation is the most important task in building an effective CLIA system as the accuracy of the results are dependent on the accuracy of the query translation. The user input, usually few words, is considered as the query. Given the differences in vocabulary across the languages, we have to capture the context of the query to increase the efficiency of the query translation. Query translation forms the vital component of any CLIA system as it captures the users need and translating queries effectively is required. We devised a language independent approach that captures the users intent from his query by mapping query words to Wikipedia topics. Wikipedia, the free on-line encyclopedia, is a hypertext document collection with a rich link structure. Unlike ordinary encyclopedias,Wikipedia is based on the wiki concept, which enables community to create or improve articles. Wikipedia articles cover many domain-specific and general topics, making it a rich knowledge resource. Due to its unique concept, Wikipedia is populated with articles in around 240 languages, making it a rich multi-lingual resource. We intend to leverage this multi lingual knowledge base as a resource to aid multi lingual query translation. In this work, we propose a query translation method that uses the rich link structure across the languages present in Wikipedia. The query translation approach we have adopted is language independent and focuses on minimizing the use of language specific resources, making our approach scalable. This approach is specifically useful for under-resourced languages (Indian, African etc) as these languages do not have sufficient resources and tools with good accuracies. For these under-resourced languages, a query translation approach is proposed using the resources mined from Wikipedia substituting the language-specific resources for query translation. Using the cross lingual links and the articles that are connected with these links, we build dictionaries that forms the resource for query translation. A language independent approach to identify parallel text is also proposed. A parallel text is a text placed alongside its translation or translations. Parallel text forms the major resource for many areas of linguistic research and their availability helps to identify many retrieval problems between the pair of languages. The query translation approach we have adopted takes the context of the query into consideration to perform the translation. We use Wikipedia concepts to mine the context of the user query and use them to form the translation. An evaluation method to evaluate query translation is also proposed using Wikipedia, by mining statistics from the articles and the cross lingual links. A separate evaluation method is required in-line with our intent to develop the system without using any language resources due to their non-availability. The coverage of the dictionaries is 78.1% while the accuracy of the query translation is 69.75%. In this work, we develop a language-independent approach to query translation that also considers the context of the query. Since no language resources were used, our approach is scalable and can be applied to any pair of languages present in Wikipedia. The performance of the system is encouraging and condone our intention of substituting Wikipedia for language resources. Further the resources mined and approaches proposed can be leveraged in various areas of linguistic research. Parallel sentence extraction approach can be used to solve the problem of cross lingual plagiarism detection. Extraction of context from a sentence can be extended to support Update Summarization task. Thus, in this work, we suggest a language independent query translation approach which can be a right direction towards building a CLIA system for less resourced languages.

Abstract

In view of the stringent requirements of measurement of capacitances associated with capacitive sensors, there is considerable work going on in the area of VLSI design. Typically MEM based capacitive sensors used in gyroscopes produce changes of atto Farads in nominal capacitance values of the order of pico Farads. The requirements of the measuring equipment are very stringent like the noise conditions, the temperature stability and frequency response etc. There are no readily available interface circuits to measure these order of capacitances. In view of this an attempt has been made to analyze the various issues that are associated with measuring the small capacitances. In the first instance the capacitance variations are converted to voltage variations. Even though there are several approaches for carrying out this operation it is found that a switched capacitor approach with DC source voltage is a suitable technique . In the first stage, amplification of the signal is carried out by minimizing the noise, temperature variations and offset variations. Keeping these in view a switched capacitor fully differential folded cascode amplifier with an open loop gain of 120dB has been designed and simulated using HSPICE simulator. The clock frequency chosen for this operation is much higher than the rate at which the capacitance changes. The high linearity of 0.05% in the maximum output of 0.6V could be achieved only through extensive simulations by varying circuit components. Finally it has been possible to arrive at a circuit with correlated double sampling, common mode feedback and optimal values of feedback capacitors. This circuit is designed as a low noise circuit to give the required resolution such that it can measure a small voltage of 10μV corresponding to 10aF. Since the circuit itself contributes to flicker noise the effect of flicker noise is countered by employing the correlated double sampling and designing the amplifier for low noise. The output of the amplifier is given to a sigma delta modulator so that the noise can be tackled and a digital output of high resolution is obtained. The sigma delta modulator is chosen to be a fourth order cascaded modulator which is realized using two second order modulators operating at same clock frequency as the main switched capacitor amplifier. The integrated blocks of switched capacitor amplifier and sigma delta modulator has been found to give a linearity of 0.05% with a maximum output value of 0.6V and minimum output value of 20μV. This thesis mainly concentrated on these two blocks and also suggests that these two blocks can be integrated in to single chip. Further processing of output of sigma delta modulator involves a process called decimation which converts the sigma delta modulator output into accurate digital output.

Abstract

The growth of Internet, like no other communication medium, has given a "Globalized dimension" to the world. It has become the Universal source of information for millions of people, at home, at school, and at work. Due to numerous contributors across the world, the amount of information available on the web is huge and is distributed across various languages. Hence, there is a need to develop applications to manage such huge amount of varied information. Multilingual Document Clustering (MDC) is one such technique which is highly useful for organizing huge amount of data present in different languages. One of its main applications is Cross-lingual Information Retrieval (CLIR), where search engine takes query in one language and retrieves results in different languages. Instead of providing results as a single long list, it would be very convenient for users if the search engine retrieves them as a list of clusters, where each cluster contains multilingual documents that are similar. It encourages users to opt for cluster based browsing which is very convenient for processing the results. Existing approaches in Multilingual document clustering uses various tools and resources such as Manually Annotated (MA) bilingual dictionaries, lemmatizers, Named Entity Recognizers (NERs), etc., for processing the data. However, many languages across the world do not have the luxury of such tools and resources. Hence, it is very difficult to process and organize the data of languages which do not have sufficient resources. In this thesis, we focus on clustering multilingual documents of resourcepoor languages. We propose three main approaches which do not make use of any language dependent resources or tools for multilingual document clustering. In the rst approach, we perform clustering of multilingual documents using Wikipedia as external knowledge. We avail various features of Wikipedia such as cross-lingual links, categories, outlinks, Infobox information, etc., to enrich the document representation. It helps in comparing two multilingual documents eciently for forming good multilingual clusters. The use of external knowledge improves the clustering performance because it considers the semantic association between the words. In the second approach, we propose a method to identify the Named Entities (NEs) present in resource-poor languages such as Hindi and Marathi. We use the Named Entities present in English, which is a resource-rich language for this purpose. The identied Named Entities help in detecting the topic of a given document, which is highly useful for comparing two documents efficiently for improving the performance of multilingual document clustering. In our final approach, we propose a method which combines our first and second approaches. In this approach, Named Entities and Wikipedia features are used together in enriching the document representation for forming good multilingual clusters. In all our approaches we use Bisecting k-means algorithm for forming multilingual clusters. We do not make use of any non-English linguistic tools or resources such as WordNet, Part-Of-Speech tagger etc., which makes our proposed work easy to extend to other languages. Experiments are conducted on English, Hindi and Marathi news datasets provided by FIRE1 for their 2010 Ad-hoc Cross-Lingual document retrieval task on Indian languages. All our approaches are evaluated using F-score, Purity and Normalized Mutual Information (NMI) measures and the results obtained are encouraging.

Abstract

There are many ways in which science is learnt by students: classroom lectures, real physical activities or computer generated interactions. Computer based simulation tools offer students a means to explore, experience and express themselves through computer generated interactions. Simulation tools are used for enhancing the learning by offering a different way of presenting the information via visualization. In simulation tools, the students can pose hypotheses about a science concept, conduct as many experiments as they want, observe and record data and draw conclusions. This might not always be possible in a real laboratory because of many reasons. The physical phenomenon could itself be complicated to observe or the experiment setup could be time consuming. Laboratory experiments are conducted in a more step-by-step manner following processes of examination and observation, which are very important to build necessary scientific skills in a student. Hence with a simulation tool students can miss out critical examination and observation skill required in a real laboratory. Therefore many researchers have suggested that the simulation can be very useful if used for experiencing before classroom instruction, and applying learned contents after classroom instruction. The classroom instruction and guidance by teachers are very important for making simulation tool an effective learning tool. Development of simulation tools for science education has been explored widely in literature. The results from these efforts indicate that the comfort level of a user with simulations is influenced by their prior experiences with other software environments. Hence for a teacher to be comfortable with a simulation tool, it needs to be customized to their preferences. Development and modification of simulations according to the specific need of teachers, while desirable, is a difficult and time-consuming process as it may require an iterative tailoring of the user interface to meet multiple constraints like their teaching style and students’ learning style. The developer must learn a software package, design the visual composition (menu, tools) and temporal behavior (stored program or task) of user interface to meet requirements. Hence, an authoring tool which allows a user to create various simulations and is easy to use will be an effective educational resource for content developers. An authoring tool, refers to a system that allows a user to create content, by defining the relationship between different media (i.e., text, video, images, etc.) and sequencing them in an appropriate order. In this thesis, we present such an authoring tool, ViPLab, to understand different components required in an authoring tool. We present the design details of the physics engine and user interface. This tool has been evaluated by science teachers and a number of undergraduate engineering students. Based on the preliminary feedback from teachers and students a set of guidelines are identified for authoring tool development. We propose an authoring tool framework that adheres to these guidelines by decoupling the user interface from the physics engine. This enables the integration of user interface with different physics engines. We present a Graphical interface construction Kit (GicK) which helps in creating user interfaces and combine it with a physics engine for creating interactive simulations. A 3D-ViPLab, an authoring tool, is developed as an exemplar of the proposed framework. We end by showing a way to convert simulations developed using 3D-ViPLab into simulation games.

Abstract

The importance of transformers, with their role in transmission and distribution of electrical power and with the effect of their performance on the system, is an obvious axiom in the modern day’s power systems. In addition to their momentous share in the capital investment of a power system, transformer outages have a considerable economic impact on the operation of the power systems. In the course of continuous efforts to make the existing power network smarter and efficient, thermal modeling and monitoring of transformers has become important in the field of transformer engineering. With all the advances in the design techniques as well as material engineering, it is the transformer thermal limitations that decide the loading and designing of the transformer from the purview of user as well as manufacturer. With the research in power systems on the whole progressing towards development of a ‘smart grid’, which infers that each of the equipment should be ‘smart’, that includes that the monitoring of each individual equipment should be intelligent, accurate as well as fast and economical, the problem of thermal Modeling of transformers has been gaining momentum all the more. The maximum temperature in the transformer interior is a significant parameter governing a transformer’s performance and life expectancy. Though the temperature rise in the transformer interior by itself may not have immediate effects, it does trigger other undesirable consequences like excessive deterioration of insulation, which in the long run will reduce the life of the transformer, thus affecting the economics of the power system. Thus the possible maximum temperature rise in the transformer for certain kind of loading needs to be estimated so as to be able to decide on the operational conditions as well as estimate the remaining life of the transformer and plan accordingly. In the perspective of the user, temperatures in a transformer are important to determine the amount and duration of over load it can sustain, and to estimate the effects on the life of the transformer by operation at various temperatures. For a transformer design engineer, prediction of temperatures at various points becomes necessary to determine the amount of copper to place in the coils, leads and outlet bushings, type of cooling and ducts, position of ducts, insulation class, design and settings of control equipment. Apart from this, increased market competency demands for accurate determination of the thermal profile across the transformer, which might result in a more economical as well as efficient manufacturing. Existing thermal models calculate the winding hotspot temperature and top oil temperature using the lumped values of heat generation inside the transformer and the rate of heat transfer and retention in the surrounding media that finally result in the temperature rise. The heat generation is due to the energy losses in the transformer which are the iron losses in the core and ohmic losses in the coils. These temperatures served as an index for the interior temperature rise in the transformer. To calculate the hotspot temperatures, the existing models used the lumped values of losses and lumped values of heat transfer and retention in the different media that surrounded the heat generating elements and the loss distribution across the transformer geometry was not calculated and used in those models. However, advancements in computing capabilities and ever ongoing research enables better transformer interior temperature modeling, which may be a better indicator of transformer thermal status. In the current work, the use of finite element analysis technique was made to calculate the loss distribution across the transformer geometry, which is a different approach. With the calculation of loss distribution across the transformer geometry, the current work proposes a new approach for thermal model of transformer and discusses the development of this thermal model that aims at computing the interior temperatures at different as well as desired points across the transformer geometry. The proposed thermal model has been successfully implemented on four real transformer data to calculate the thermal profiles of transformers that show the real life use of proposed thermal model.

Abstract

The selection of a subset of ’interesting’ regions in a given image forms an important first step in many computer vision algorithms, for example for computing image correspondences , scene recognition, object detection or for learning object categories. The algorithms that are used to detect and represent these subset of regions are known as interest point operators. In order to develop an interest point operator, two key issues need to be addressed: how to select the subset of the image for subsequent analysis and how to represent the subset? In this thesis we examine both the issues of detection and representation. The first topic of this thesis deals with the problem of interest point/region detection. Several interest point/region detectors such as Harris corner detector, SIFT, Maximally Stable Extrema Regions have been developed, all of which by and large rely on some ad hoc filters to quantify ”interest”. This could be due to the fact that the challenging aspect of this problem is to quantify the ”interestingness” of a region in the given image. We address this topic by looking into the mechanisms adopted by Human Visual System (HVS) for identifying visual regions of interest. It is believed that HVS constantly relies on saccades to analyze the scene in front of it in a serial fashion, attending to the most relevant/interesting regions first. Saccades are common eye movements that are used to shift gaze, scan visual scenes or track moving targets. The thesis analyzes the ways in which existing interest point operators and systems developed for predicting saccades are related to each other. The latter rely more on feature contrast known to be influencing HVS in contrast to ad hoc approaches used in the former. This has prompted us to study the role of features like local symmetry, curvature and phase in predicting saliency. The role of each feature is quantified by adding them to an existing feature-based model for predicting saccades and analyzing how well the resultant prediction correlate with fixation maps. The results indicate that of the features studied, phase only reconstruction of an image correlates best with HVS fixations. Phase only reconstruction is one of several spectral domain methods reported recently for predicting interesting/salient regions. We establish a generalization of these spectral domain methods using a simple algorithm known as Frequency self filtering which has been used for automatic image inpainting. The second topic of the thesis deals with the problem of interest region representation. The representation of a region is supposed to capture the spatial arrangement of the pixels while preserving invariance to common distortions, in a compact format. The typical trade-off here is between the detail the representation can capture and the robustness to distortions. Popular representations like SIFT, vGiLOH, Shape Context etc, rely on histograms of edge-like features computed over predefined grids. The amount of spatial distribution information captured by these representations is very much dependent on the granularity of the grid over which histograms are computed. As an alternate way of encoding spatial distribution information we propose a hypothesis that spatial distribution information can be captured using texture information in the projection domain. In order to test this hypothesis a representation based on Radon transform and local binary patterns is developed. This is tested in three different scenarios, namely binary shape retrieval, gray scale image matching and abnormality classification in medical images. In all the three scenarios the proposed representation has shown good performance. The results indicate that spatial distribution information can be encoded into representation using the proposed hypothesis.

Abstract

With increase in technology scaling, semiconductor devices are becoming increasingly less predictable. The device failure rates increase significantly with decrease in device sizes. Memory unit usually has more hardware components than other circuits and therefore is the most unreliable part. The SRAM memory cell has highest density and is more vulnerable to defects compared to other logic circuits. As the technology scales the process variations also affect the functionality of the memory. There are computer applications where extreme reliability of computing system is essential. Even with advances in manufacturing technology to reduce the faults occurring, the errors in memory are still present. So, methods to increase reliability by providing some internal fault-tolerance are gaining importance in memories. This thesis focuses on developing a memory architecture which enables self test of the memories after manufacturing and avoids the faulty rows by incorporating additional test circuits. The effectiveness of the proposed circuits is checked on a word oriented two port memory. We assume that a single fault in any memory cell within a particular row makes the entire row faulty. During the isolation and replacement, the entire row is isolated and replaced with a healthy row. To carry out the replacement, some spare rows are provided in the memory array. A row can have a single or multiple faulty cells within it; it is replaced by a spare row. The fault model considered in this thesis is the stuck-at-fault i.e., stuck-at-0 and stuck-at-1 faults occurring in the SRAM cell. The stuck-at-faults present in the SRAM cell alone are considered in this thesis for testing, isolation and replacement process. The idea has been demonstrated through the simulation for a word oriented two port memory architecture and additional circuits were designed which incorporate all the above discussed facilities. In a word oriented memory the entire row is written or read at a time in a clock cycle. In the two port memories, the read and write ports are completely independent and hence the read and write operations can be performed simultaneously though simultaneous reading and writing of same row cannot be performed. The architecture proposed in this thesis consists of word oriented two port SRAM memory cells consisting of 4 words, and each word consists of 4bits. The memory further has additional circuits for fault detection, fault isolation and replacement of faulty rows. During testing it is assumed that a Built-in Self Test (BIST) controller is present which includes circuits to generate the signals necessary to start and end the test mode in the memory; a Test Pattern Generator (TPG) to generate the necessary test addresses and test input vectors necessary to carry out the testing during the test mode. The BIST controller signals the start of testing process at every power-on of the memory. First the testing is carried which provides the input vectors which sensitize the fault present in the memory and allows to identify them. A compare circuit is used to identify the faulty row(s) in the memory. The signal generated from the compare circuit is used by the isolation circuit to isolate the faulty row from the SRAM array. The same signal generated from the compare circuit is used by the replacement circuit to redirect the signals corresponding to the faulty row to the healthy row. Additional spare rows are provided in the memory architecture which are used during the replacement process. The self healing structure proposed in this thesis enables one to have reliable memory after the testing and replacement process. It helps in improving the memory yield which directly translates into chip yield and chip reliability. The circuits that are proposed and tested through simulation are designed with the same technology as the SRAM memory is designed. Hence it is possible to integrate them with the SRAM memory. The architecture is designed at circuit level and the simulations are carried using HSPICE. The circuit is designed at 65nm technology node and the 65nm Predictive Technology Model (PTM) is used as the model for simulation. Thus the thesis proposes a self healing architecture through BIST and additional circuits proposed for memories which may result in considerable improvement in yield of memories manufactured in the latest technology nodes.