International journal of engineering research and technology, May 30, 2012
This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the... more This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the Elliptic curve y cryptography. S ecurity in WS N is a greater challenge in WS N due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WS Ns is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WS Ns leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
Computer vision techniques for aligning and fusing images have long been employed to create smoot... more Computer vision techniques for aligning and fusing images have long been employed to create smooth photographic mosaics. These methods have found applications in image stabilization features of camcorders, production of digital maps and satellite images through high-resolution photographic mosaics, and more. This paper introduces a novel method for generating composites from two or more images, with the ability to significantly reduce or eliminate white space when operating with a live connection. By leveraging algorithms such as Scale-Invariant Feature Transform (SIFT), the proposed method enables feature recognition and extraction from captured images, facilitating the removal of white space in live images. Additionally, this work presents a technique that merges live images with real-time camera input to complete missing elements by intelligently manipulating controlled elements in the images. The resulting approach offers a promising solution for real-time image fusion and the seamless integration of live camera feeds, enhancing the visual quality and completeness of the final composite.
Advancement of IoT in Blockchain Technology and its Applications
Without energy conservation, the world will deplete its common assets. The increase in usage of s... more Without energy conservation, the world will deplete its common assets. The increase in usage of smart technology has helped to contribute to energy conservation and sustainable development. The model works to cure the limited ability of humans to respond to any situation effectively. A 24*7 smart monitoring system that reacts whenever it encounters irregularities is a way to curb intermediate electricity wastage, increased emission levels and changes in weather patterns. The proposed framework is a measured framework having the parts: Raspberry Pi, PIR sensor, Camera module, Relay driver. The prototype uses a machine learning model aided by sensors that processes real time information in accordance with a data-set which improves decision making. The prototype is a centralized device which works with existing infrastructure as well as smart buildings where it accesses inputs from the surrounding environment and prevents wastage of resources
India, with a population of 1.3 billion and almost 300 million vehicles, is one of the biggest co... more India, with a population of 1.3 billion and almost 300 million vehicles, is one of the biggest contributors to traffic jams, vehicle-specific pollution, and chronic lung diseases. To manage the footfall of these gigantic vehicles, continuous effort and research is taking place in the direction of both active and passive traffic management. This research paper aims towards showcasing a dynamic, fully autonomous deep learning model that uses real-time feeds from existing traffic junctions/ intersection cameras, process them and provide an intensity score based on the density of traffic in each adjoining lane.The proposed CNN model which is based on YOLO framework uses 10 seconds wait analysis time. The proposed system manages traffic, based on the intensity scores which assign traffic a Go time to each lane using an optimal traffic time in the range of 10-50 seconds.The model also scans for emergency vehicles in each lane, to provide a priority pass to such vehicles. Evaluation of model performance Mean Average Precision (mAP) is used.
Road accidents are the main cause of death among the human population. Distracted and drowsy driv... more Road accidents are the main cause of death among the human population. Distracted and drowsy driving takes thousands of lives every year around the world. Subsequently, to forestall such mishaps and save lives, there is a requirement for a system that detects both distraction and drowsiness for both day and night time. In this paper, we present a deep learning convolutional model to detect distraction and drowsiness during driving. The proposed model performs real-time video processing for monitoring the activities of drivers during driving. The model produces an alert in case of any careless driving or inappropriate behaviour of the driver with the minimum response time. For this purpose dataset for training as well as for testing were prepared. For training the model, we have used CNN model. The proposed model was able to achieve 99.95% accuracy on test dataset.
International Journal on Smart Sensing and Intelligent Systems
The presence of near duplicate textual content imposes great challenges while extracting informat... more The presence of near duplicate textual content imposes great challenges while extracting information from it. To handle these challenges, detection of near duplicates is a prime research concern. Existing research mostly uses text clustering, classification and retrieval algorithms for detection of near duplicates. Text summarization, an important tool of text mining, is not explored yet for the detection of near duplicates. Instead of using the whole document, the proposed method uses its summary as it saves both time and storage. Experimental results show that traditional similarity algorithms were able to capture similarity relatedness to a great extent even on the summarized text with a similarity score of 44.685%. Moreover, degree of similarity capture was greater (0.52%) in case of use of embedding models with better text representation as compared to traditional methods. Also, this paper highlights the research status of various similarity measures in terms of concept involve...
Network security is becoming an important issue. Due to increase in the knowledge of intruders an... more Network security is becoming an important issue. Due to increase in the knowledge of intruders and attackers different security tools fails. With the advance of technology new tools are developed and new approaches are embedded in previously developed approaches. So, Intrusion Detection System (IDS) comes into role.IDS provide second line of defense which is not in the limit of firewall and others. . In this thesis a Hybrid intrusion detection method is proposed that is based on Misuse Detection Approach and Anomaly Detection. For Misuse Detection Pattern Matching algorithm is used. Attack pattern are matched with already stored pattern. In second phase for anomaly detection approach clustering is used. But the clustering is based on Neural Network. Through the Neural Network the IDS become selfadapting in nature. Index Terms – Intrusion Detection, Clustering, Neural Network, Network Security.
Back propagation(BP) is used to solve real world problems which use the concept of multilayer per... more Back propagation(BP) is used to solve real world problems which use the concept of multilayer perceptron(MLP). BP have the disadvantage of trapped in local minima, slow convergence rate and more error prone. To optimize BP Algorithm, Particle swarm optimization(PSO) and Genetic algorithm(GA) is used. Limitation of PSO_Hill and PSO_A* is overcomes when these algorithms are combined and on the basis of strength of these two algorithm we proposed a new PSO_Hill_A * algorithm which is used to optimize and enhance learning process in terms of convergence rate and accuracy. GA is a kind of method to simulate and to search the optimal solution, GA can have four operations including Encoding, selecting, crossover and Mutation. To optimize and improve BP, we proposed two architecture: 1) Use of PSO_Hill_A * before and after hidden layer. 2) Use of GA before and after hidden layer.
International journal of engineering research and technology, 2012
This paper discusses different issues of Wireless Sensor Network (WSN) and the relevance of the E... more This paper discusses different issues of Wireless Sensor Network (WSN) and the relevance of the Elliptic curve y cryptography. Security in WSN is a greater challenge in WSN due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WSNs is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WSNs leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
Back propagation algorithm (BPA) have the complexity, local minima problem so we are using Partic... more Back propagation algorithm (BPA) have the complexity, local minima problem so we are using Particle Swarm optimization (PSO) algorithms to reduce and optimize BPA. In this paper, two variants of Particle Swarm Optimization (PSO) PSO_Hill and PSO_A* is used as optimization algorithm. PSO_Hill and PSO_A* algorithms are analyzed and evaluated on the basis of their advantages, applied to feed forward neural network(FNN) for back propagation algorithm(BPA) which is a gredient desent technique. where BPA is used for non_linear problems. These non_linear problems are improved by a PSO_Hill and PSO_A* algorithms.
Security of a network is always an important issue. With the continuously growing network, the ba... more Security of a network is always an important issue. With the continuously growing network, the basic security such as firewall, virus scanner is easily deceived by modern attackers who are experts in using software vulnerabilities to achieve their goals. For preventing such attacks, we need even smarter security mechanism which act proactively and intelligently. Intrusion Detection System is the solution of such requirement. Many techniques have been used to implement IDS. These technique basically used in the detector part of IDS such as Neural Network, Clustering, Pattern Matching, Rule Based, Fuzzy Logic, Genetic Algorithms and many more. To improve the performance of an IDS these approaches may be used in combination to build a hybrid IDS so that benefits of two o more approaches may be combined.
Technology is being on progress since the evolution and currently the main area of research is au... more Technology is being on progress since the evolution and currently the main area of research is automation technology. SMS Based Home Automation System is the earlier technology that came in existence. Each technology has several limitations. This paper emphasizes on the limitations of this technology and some advancement in automation technology to overcome those limitations. This design is presented to overcome the user non-friendly behavior limitation of SMS based automation devices and mobility of internet/gprs and embedding the two technologies. This also focuses on comparison with existing technology. The main idea of paper is to provide user friendly interface.
2019 International Conference on contemporary Computing and Informatics (IC3I)
Everyday large volume of data is gathered from different sources and are stored since they contai... more Everyday large volume of data is gathered from different sources and are stored since they contain valuable piece of information. The storage of data must be done in efficient manner since it leads in difficulty during retrieval. Text data are available in the form of large documents. Understanding large text documents and extracting meaningful information out of it is time-consuming tasks. To overcome these challenges, information in the form of text are summarized in with an objective to get relevant knowledge with the help of text mining tools. Summarized text will have reduced size as compared to original one. In this paper, we have tried to highlight major techniques for extracting important information from a given text with the help of topic modeling, key phrase extraction and summary generation. For topic modelling LSI and NMF method is used, weighted TF-IDF method is used for key phrase extraction while text summary is generated by using LSA and Text Rank method.
Text mining refers to the process of deriving high-quality information from text. A number of app... more Text mining refers to the process of deriving high-quality information from text. A number of approaches have been developed to represent and classify text documents. Most of the approach try to achieve good classification performance by considering a document only by words. Suitable method should be used for mapping text to best features. In this paper, performance analysis of three different supervised algorithms, as a text classifier, on the basis of two different feature representation methods-Count Vector and Term Frequency Inverse Document Frequency method is discussed.
This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the... more This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the Elliptic curve y cryptography. S ecurity in WS N is a greater challenge in WS N due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WS Ns is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WS Ns leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
International Journal of Computer Applications, 2013
Back propagation(BP) is used to solve real world problems which use the concept of multilayer per... more Back propagation(BP) is used to solve real world problems which use the concept of multilayer perceptron(MLP). BP have the disadvantage of trapped in local minima, slow convergence rate and more error prone. To optimize BP Algorithm, Particle swarm optimization(PSO) and Genetic algorithm(GA) is used. Limitation of PSO_Hill and PSO_A* is overcomes when these algorithms are combined and on the basis of strength of these two algorithm we proposed a new PSO_Hill_A* algorithm which is used to optimize and enhance learning process in terms of convergence rate and accuracy. GA is a kind of method to simulate and to search the optimal solution, GA can have four operations including Encoding, selecting, crossover and Mutation. To optimize and improve BP, we proposed two architecture: 1) Use of PSO_Hill_A* before and after hidden layer. 2) Use of GA before and after hidden layer.
International Journal of Computer Applications, 2014
Wireless Sensor Networks (WSNs) has foreseen big changes in data gathering, processing and dissem... more Wireless Sensor Networks (WSNs) has foreseen big changes in data gathering, processing and disseminating for monitoring specific applications such as emergency services, disaster management, and military applications etc. Since large number sensor nodes are deployed to monitor a vast field, where the operational conditions are most often harsh or even hostile so security mechanism in WSN is a greater challenge in WSN. Sensor networks pose unique challenges because of their inherent limitations in communication and computing. Sensor networks are vulnerable to security attacks due to the broadcast nature of transmission. The threats against WSN can be reduced by proper security measures. One of the commonly used methods is the use of cryptographic algorithm. This paper proposes mechanisms for Key Predistribution and mutual Authentication protocol in sensor networks using ECC with respect to constraints of WSN.
International journal of engineering research and technology, May 30, 2012
This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the... more This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the Elliptic curve y cryptography. S ecurity in WS N is a greater challenge in WS N due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WS Ns is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WS Ns leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
Computer vision techniques for aligning and fusing images have long been employed to create smoot... more Computer vision techniques for aligning and fusing images have long been employed to create smooth photographic mosaics. These methods have found applications in image stabilization features of camcorders, production of digital maps and satellite images through high-resolution photographic mosaics, and more. This paper introduces a novel method for generating composites from two or more images, with the ability to significantly reduce or eliminate white space when operating with a live connection. By leveraging algorithms such as Scale-Invariant Feature Transform (SIFT), the proposed method enables feature recognition and extraction from captured images, facilitating the removal of white space in live images. Additionally, this work presents a technique that merges live images with real-time camera input to complete missing elements by intelligently manipulating controlled elements in the images. The resulting approach offers a promising solution for real-time image fusion and the seamless integration of live camera feeds, enhancing the visual quality and completeness of the final composite.
Advancement of IoT in Blockchain Technology and its Applications
Without energy conservation, the world will deplete its common assets. The increase in usage of s... more Without energy conservation, the world will deplete its common assets. The increase in usage of smart technology has helped to contribute to energy conservation and sustainable development. The model works to cure the limited ability of humans to respond to any situation effectively. A 24*7 smart monitoring system that reacts whenever it encounters irregularities is a way to curb intermediate electricity wastage, increased emission levels and changes in weather patterns. The proposed framework is a measured framework having the parts: Raspberry Pi, PIR sensor, Camera module, Relay driver. The prototype uses a machine learning model aided by sensors that processes real time information in accordance with a data-set which improves decision making. The prototype is a centralized device which works with existing infrastructure as well as smart buildings where it accesses inputs from the surrounding environment and prevents wastage of resources
India, with a population of 1.3 billion and almost 300 million vehicles, is one of the biggest co... more India, with a population of 1.3 billion and almost 300 million vehicles, is one of the biggest contributors to traffic jams, vehicle-specific pollution, and chronic lung diseases. To manage the footfall of these gigantic vehicles, continuous effort and research is taking place in the direction of both active and passive traffic management. This research paper aims towards showcasing a dynamic, fully autonomous deep learning model that uses real-time feeds from existing traffic junctions/ intersection cameras, process them and provide an intensity score based on the density of traffic in each adjoining lane.The proposed CNN model which is based on YOLO framework uses 10 seconds wait analysis time. The proposed system manages traffic, based on the intensity scores which assign traffic a Go time to each lane using an optimal traffic time in the range of 10-50 seconds.The model also scans for emergency vehicles in each lane, to provide a priority pass to such vehicles. Evaluation of model performance Mean Average Precision (mAP) is used.
Road accidents are the main cause of death among the human population. Distracted and drowsy driv... more Road accidents are the main cause of death among the human population. Distracted and drowsy driving takes thousands of lives every year around the world. Subsequently, to forestall such mishaps and save lives, there is a requirement for a system that detects both distraction and drowsiness for both day and night time. In this paper, we present a deep learning convolutional model to detect distraction and drowsiness during driving. The proposed model performs real-time video processing for monitoring the activities of drivers during driving. The model produces an alert in case of any careless driving or inappropriate behaviour of the driver with the minimum response time. For this purpose dataset for training as well as for testing were prepared. For training the model, we have used CNN model. The proposed model was able to achieve 99.95% accuracy on test dataset.
International Journal on Smart Sensing and Intelligent Systems
The presence of near duplicate textual content imposes great challenges while extracting informat... more The presence of near duplicate textual content imposes great challenges while extracting information from it. To handle these challenges, detection of near duplicates is a prime research concern. Existing research mostly uses text clustering, classification and retrieval algorithms for detection of near duplicates. Text summarization, an important tool of text mining, is not explored yet for the detection of near duplicates. Instead of using the whole document, the proposed method uses its summary as it saves both time and storage. Experimental results show that traditional similarity algorithms were able to capture similarity relatedness to a great extent even on the summarized text with a similarity score of 44.685%. Moreover, degree of similarity capture was greater (0.52%) in case of use of embedding models with better text representation as compared to traditional methods. Also, this paper highlights the research status of various similarity measures in terms of concept involve...
Network security is becoming an important issue. Due to increase in the knowledge of intruders an... more Network security is becoming an important issue. Due to increase in the knowledge of intruders and attackers different security tools fails. With the advance of technology new tools are developed and new approaches are embedded in previously developed approaches. So, Intrusion Detection System (IDS) comes into role.IDS provide second line of defense which is not in the limit of firewall and others. . In this thesis a Hybrid intrusion detection method is proposed that is based on Misuse Detection Approach and Anomaly Detection. For Misuse Detection Pattern Matching algorithm is used. Attack pattern are matched with already stored pattern. In second phase for anomaly detection approach clustering is used. But the clustering is based on Neural Network. Through the Neural Network the IDS become selfadapting in nature. Index Terms – Intrusion Detection, Clustering, Neural Network, Network Security.
Back propagation(BP) is used to solve real world problems which use the concept of multilayer per... more Back propagation(BP) is used to solve real world problems which use the concept of multilayer perceptron(MLP). BP have the disadvantage of trapped in local minima, slow convergence rate and more error prone. To optimize BP Algorithm, Particle swarm optimization(PSO) and Genetic algorithm(GA) is used. Limitation of PSO_Hill and PSO_A* is overcomes when these algorithms are combined and on the basis of strength of these two algorithm we proposed a new PSO_Hill_A * algorithm which is used to optimize and enhance learning process in terms of convergence rate and accuracy. GA is a kind of method to simulate and to search the optimal solution, GA can have four operations including Encoding, selecting, crossover and Mutation. To optimize and improve BP, we proposed two architecture: 1) Use of PSO_Hill_A * before and after hidden layer. 2) Use of GA before and after hidden layer.
International journal of engineering research and technology, 2012
This paper discusses different issues of Wireless Sensor Network (WSN) and the relevance of the E... more This paper discusses different issues of Wireless Sensor Network (WSN) and the relevance of the Elliptic curve y cryptography. Security in WSN is a greater challenge in WSN due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WSNs is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WSNs leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
Back propagation algorithm (BPA) have the complexity, local minima problem so we are using Partic... more Back propagation algorithm (BPA) have the complexity, local minima problem so we are using Particle Swarm optimization (PSO) algorithms to reduce and optimize BPA. In this paper, two variants of Particle Swarm Optimization (PSO) PSO_Hill and PSO_A* is used as optimization algorithm. PSO_Hill and PSO_A* algorithms are analyzed and evaluated on the basis of their advantages, applied to feed forward neural network(FNN) for back propagation algorithm(BPA) which is a gredient desent technique. where BPA is used for non_linear problems. These non_linear problems are improved by a PSO_Hill and PSO_A* algorithms.
Security of a network is always an important issue. With the continuously growing network, the ba... more Security of a network is always an important issue. With the continuously growing network, the basic security such as firewall, virus scanner is easily deceived by modern attackers who are experts in using software vulnerabilities to achieve their goals. For preventing such attacks, we need even smarter security mechanism which act proactively and intelligently. Intrusion Detection System is the solution of such requirement. Many techniques have been used to implement IDS. These technique basically used in the detector part of IDS such as Neural Network, Clustering, Pattern Matching, Rule Based, Fuzzy Logic, Genetic Algorithms and many more. To improve the performance of an IDS these approaches may be used in combination to build a hybrid IDS so that benefits of two o more approaches may be combined.
Technology is being on progress since the evolution and currently the main area of research is au... more Technology is being on progress since the evolution and currently the main area of research is automation technology. SMS Based Home Automation System is the earlier technology that came in existence. Each technology has several limitations. This paper emphasizes on the limitations of this technology and some advancement in automation technology to overcome those limitations. This design is presented to overcome the user non-friendly behavior limitation of SMS based automation devices and mobility of internet/gprs and embedding the two technologies. This also focuses on comparison with existing technology. The main idea of paper is to provide user friendly interface.
2019 International Conference on contemporary Computing and Informatics (IC3I)
Everyday large volume of data is gathered from different sources and are stored since they contai... more Everyday large volume of data is gathered from different sources and are stored since they contain valuable piece of information. The storage of data must be done in efficient manner since it leads in difficulty during retrieval. Text data are available in the form of large documents. Understanding large text documents and extracting meaningful information out of it is time-consuming tasks. To overcome these challenges, information in the form of text are summarized in with an objective to get relevant knowledge with the help of text mining tools. Summarized text will have reduced size as compared to original one. In this paper, we have tried to highlight major techniques for extracting important information from a given text with the help of topic modeling, key phrase extraction and summary generation. For topic modelling LSI and NMF method is used, weighted TF-IDF method is used for key phrase extraction while text summary is generated by using LSA and Text Rank method.
Text mining refers to the process of deriving high-quality information from text. A number of app... more Text mining refers to the process of deriving high-quality information from text. A number of approaches have been developed to represent and classify text documents. Most of the approach try to achieve good classification performance by considering a document only by words. Suitable method should be used for mapping text to best features. In this paper, performance analysis of three different supervised algorithms, as a text classifier, on the basis of two different feature representation methods-Count Vector and Term Frequency Inverse Document Frequency method is discussed.
This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the... more This paper discusses different issues of Wireless S ensor Network (WS N) and the relevance of the Elliptic curve y cryptography. S ecurity in WS N is a greater challenge in WS N due to the processing limitations of sensor nodes and nature of wireless links. Extensive use of WS Ns is giving rise to different types of threats. To defend against the threats proper security schemes are required. Traditionally security is implemented through hardware or software and is generally achieved through cryptographic methods. Limited area, nature of links, limited processing, power and memory of WS Ns leads to strict constraints on the selection of cryptographic techniques. Elliptic Curve Cryptography (ECC) is the best candidate due to its smaller key size. High security despite of smaller key size results in area and power efficient crypto systems.
International Journal of Computer Applications, 2013
Back propagation(BP) is used to solve real world problems which use the concept of multilayer per... more Back propagation(BP) is used to solve real world problems which use the concept of multilayer perceptron(MLP). BP have the disadvantage of trapped in local minima, slow convergence rate and more error prone. To optimize BP Algorithm, Particle swarm optimization(PSO) and Genetic algorithm(GA) is used. Limitation of PSO_Hill and PSO_A* is overcomes when these algorithms are combined and on the basis of strength of these two algorithm we proposed a new PSO_Hill_A* algorithm which is used to optimize and enhance learning process in terms of convergence rate and accuracy. GA is a kind of method to simulate and to search the optimal solution, GA can have four operations including Encoding, selecting, crossover and Mutation. To optimize and improve BP, we proposed two architecture: 1) Use of PSO_Hill_A* before and after hidden layer. 2) Use of GA before and after hidden layer.
International Journal of Computer Applications, 2014
Wireless Sensor Networks (WSNs) has foreseen big changes in data gathering, processing and dissem... more Wireless Sensor Networks (WSNs) has foreseen big changes in data gathering, processing and disseminating for monitoring specific applications such as emergency services, disaster management, and military applications etc. Since large number sensor nodes are deployed to monitor a vast field, where the operational conditions are most often harsh or even hostile so security mechanism in WSN is a greater challenge in WSN. Sensor networks pose unique challenges because of their inherent limitations in communication and computing. Sensor networks are vulnerable to security attacks due to the broadcast nature of transmission. The threats against WSN can be reduced by proper security measures. One of the commonly used methods is the use of cryptographic algorithm. This paper proposes mechanisms for Key Predistribution and mutual Authentication protocol in sensor networks using ECC with respect to constraints of WSN.
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Papers by Asha Mishra