Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071588
Pallavi Shede, S. Mane
Present paper gives overview of leakage current sensing techniques. As it is important to monitor and maintain the leakage current at the lower side by engineers and electric companies, this paper describes the highlighted concepts of leakage current for general electrical devices or instruments. In addition to this, various methods of measuring leakage current are reviewed. It also reports the current sensors in accordance with principle in order to mention their positives and negatives. Whereas some of the current sensing techniques rise with the new principles, for example Hall-effect sensors and fluxgate sensor or advanced technologies such as magneto resistance effect sensing and fiber-optic techniques which provide alternatives in current sensing, almost at affordable price than traditional techniques just like shunt resistors. In addition to this, the system will be modified with transmitter block and receiver block which are connected to leakage current sensor and remote controller respectively. This can be used for data processing and storage of data.
{"title":"Leakage current sensing techniques","authors":"Pallavi Shede, S. Mane","doi":"10.1109/SSPS.2017.8071588","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071588","url":null,"abstract":"Present paper gives overview of leakage current sensing techniques. As it is important to monitor and maintain the leakage current at the lower side by engineers and electric companies, this paper describes the highlighted concepts of leakage current for general electrical devices or instruments. In addition to this, various methods of measuring leakage current are reviewed. It also reports the current sensors in accordance with principle in order to mention their positives and negatives. Whereas some of the current sensing techniques rise with the new principles, for example Hall-effect sensors and fluxgate sensor or advanced technologies such as magneto resistance effect sensing and fiber-optic techniques which provide alternatives in current sensing, almost at affordable price than traditional techniques just like shunt resistors. In addition to this, the system will be modified with transmitter block and receiver block which are connected to leakage current sensor and remote controller respectively. This can be used for data processing and storage of data.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129376527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071599
Preeti P. Thakre, V. Sahare
Live migration is the process used in virtualization environment of datacenters in order to take the benefit of zero downtime during system maintenance. But during migrating live virtual machines along with system files and storage data, network traffic gets increases across network bandwidth and delays in migration time. There is need to reduce the migration time in order to maintain the system performance by analyzing and optimizing the storage overheads which mainly creates due to unnecessary duplicated data transferred during live migration. So there is need of such storage device which will keep the duplicated data residing in both the source as well as target physical host i.e. NAS. The proposed hash map based algorithm maps all I/O operations in order to track the duplicated data by assigning hash value to both NAS and RAM data. Only the unique data then will be sent data to the target host without affecting service level agreement (SLA), without affecting VM migration time, application downtime, SLA violations, VM pre-migration and downtime post migration overheads during pre and post migration of virtual machines.
{"title":"VM live migration time reduction using NAS based algorithm during VM live migration","authors":"Preeti P. Thakre, V. Sahare","doi":"10.1109/SSPS.2017.8071599","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071599","url":null,"abstract":"Live migration is the process used in virtualization environment of datacenters in order to take the benefit of zero downtime during system maintenance. But during migrating live virtual machines along with system files and storage data, network traffic gets increases across network bandwidth and delays in migration time. There is need to reduce the migration time in order to maintain the system performance by analyzing and optimizing the storage overheads which mainly creates due to unnecessary duplicated data transferred during live migration. So there is need of such storage device which will keep the duplicated data residing in both the source as well as target physical host i.e. NAS. The proposed hash map based algorithm maps all I/O operations in order to track the duplicated data by assigning hash value to both NAS and RAM data. Only the unique data then will be sent data to the target host without affecting service level agreement (SLA), without affecting VM migration time, application downtime, SLA violations, VM pre-migration and downtime post migration overheads during pre and post migration of virtual machines.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122435684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071580
Mohammed G. Vayada, Hepi R. Patel, B. Muduli
In recent scenario, the hardware design is becoming a very complex task because programmable hardware like FPGA has become complex with regards to the increasing number of transistors. In this paper, an overview of tool for model based hardware design is mentioned. This tool enable to describe an algorithm in a model based description without going in to complex low-level VHDL or Verilog description. It is efficient in translating model based description to HDL automatically. These kind of high level tools bring hardware implementation such as FPGA to a wider aspects with increasing designing productivity. In this paper an image security model using Matlab-Simulink with Xilinx system generator is developed. The use is to secure image, i.e. secret image is kept behind the cover image. The concealed image is imposible to retrive from the cover image and user can only see cover image.
{"title":"Hardware software co-design simulation modeling for image security concept using Matlab-Simulink with Xilinx system generator","authors":"Mohammed G. Vayada, Hepi R. Patel, B. Muduli","doi":"10.1109/SSPS.2017.8071580","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071580","url":null,"abstract":"In recent scenario, the hardware design is becoming a very complex task because programmable hardware like FPGA has become complex with regards to the increasing number of transistors. In this paper, an overview of tool for model based hardware design is mentioned. This tool enable to describe an algorithm in a model based description without going in to complex low-level VHDL or Verilog description. It is efficient in translating model based description to HDL automatically. These kind of high level tools bring hardware implementation such as FPGA to a wider aspects with increasing designing productivity. In this paper an image security model using Matlab-Simulink with Xilinx system generator is developed. The use is to secure image, i.e. secret image is kept behind the cover image. The concealed image is imposible to retrive from the cover image and user can only see cover image.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"305 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121466350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071637
M. Kannan, Selvakumar Chinnappan, C. Krishnamoorthy
In the process control field, nodes of WSN are deployed to receive the data. Efficient data collection is difficult and it depends on routing, power supply and remote location of node. To overcome the routing problem a new Bio-Inspired mechanism Ant Star Fuzzy (ASF) is proposed. ASF is a reliable and dynamic protocol, capable to provide energy efficient, data collecting routing structure in WSN. Network traffic and fast draining of energy of individual node is avoided. So this will increase the life of the network. ASF optimizes the routing paths even in the case of node drop of failure. It provides effective multi-path data transmission and reliable communication. The main objective is to increase the life span of network, during effective data communication in an efficient manner. This paper defines implementation of WSN and comparison of its performance with AODV, ACOAODV routing protocol based on ASF algorithm is done in terms of packet delivery ratio, throughput and energy level. Performance of ASF algorithm compare with conventional algorithms gives improved results.
{"title":"Ant star fuzzy routing for industrial wireless sensor network","authors":"M. Kannan, Selvakumar Chinnappan, C. Krishnamoorthy","doi":"10.1109/SSPS.2017.8071637","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071637","url":null,"abstract":"In the process control field, nodes of WSN are deployed to receive the data. Efficient data collection is difficult and it depends on routing, power supply and remote location of node. To overcome the routing problem a new Bio-Inspired mechanism Ant Star Fuzzy (ASF) is proposed. ASF is a reliable and dynamic protocol, capable to provide energy efficient, data collecting routing structure in WSN. Network traffic and fast draining of energy of individual node is avoided. So this will increase the life of the network. ASF optimizes the routing paths even in the case of node drop of failure. It provides effective multi-path data transmission and reliable communication. The main objective is to increase the life span of network, during effective data communication in an efficient manner. This paper defines implementation of WSN and comparison of its performance with AODV, ACOAODV routing protocol based on ASF algorithm is done in terms of packet delivery ratio, throughput and energy level. Performance of ASF algorithm compare with conventional algorithms gives improved results.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126358051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071572
Ninad N. Dafale, R. Naskar
In today's digital world, images are utilized as a method of communication in all spheres of life. Counter Forensics is the art and science of impeding and misleading forensic analysis of digital images. Camera sensor pattern noise is efficient in blind image source device identification. In this paper, we deliver an attack on digital images, where we completely remove the traces of sensor pattern noises of their source devices, so as to deceive forensic investigations. Next, we substitute the sensor pattern of a given image with that of a different (wrong) source device, such that it now appears to the forensic analyst, that the image was produced by device B, whereas originally it was produced by A. Our experimental results prove that high correlation is achieved between a tampered image and a wrong device, suggesting considerably high degree of anonymity, hence misleading forensics investigation.
{"title":"Sensor pattern noise based source anonymization","authors":"Ninad N. Dafale, R. Naskar","doi":"10.1109/SSPS.2017.8071572","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071572","url":null,"abstract":"In today's digital world, images are utilized as a method of communication in all spheres of life. Counter Forensics is the art and science of impeding and misleading forensic analysis of digital images. Camera sensor pattern noise is efficient in blind image source device identification. In this paper, we deliver an attack on digital images, where we completely remove the traces of sensor pattern noises of their source devices, so as to deceive forensic investigations. Next, we substitute the sensor pattern of a given image with that of a different (wrong) source device, such that it now appears to the forensic analyst, that the image was produced by device B, whereas originally it was produced by A. Our experimental results prove that high correlation is achieved between a tampered image and a wrong device, suggesting considerably high degree of anonymity, hence misleading forensics investigation.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131167760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071629
S. Sripriya, V. Divya, T. Babu
A Building Management System otherwise known as Building Automation System (BAS), is a Computer based control system installed in buildings that controls and monitors buildings mechanical and electrical equipments such as ventilation, lighting, power systems and security systems. A building management system for METRO includes inputs from the systems like HVAC (Heating Ventilation Air Conditioning), Lifts Escalators, UPS and Fire Alarm and Detection System etc. A BMS system uses a PLC controller along with SCADA suite to monitor and control all the systems included in the Metro. BMS provides Automatic Fault Detection System and diagnosis strategies for building energy performance.
{"title":"Building management system in metro rail","authors":"S. Sripriya, V. Divya, T. Babu","doi":"10.1109/SSPS.2017.8071629","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071629","url":null,"abstract":"A Building Management System otherwise known as Building Automation System (BAS), is a Computer based control system installed in buildings that controls and monitors buildings mechanical and electrical equipments such as ventilation, lighting, power systems and security systems. A building management system for METRO includes inputs from the systems like HVAC (Heating Ventilation Air Conditioning), Lifts Escalators, UPS and Fire Alarm and Detection System etc. A BMS system uses a PLC controller along with SCADA suite to monitor and control all the systems included in the Metro. BMS provides Automatic Fault Detection System and diagnosis strategies for building energy performance.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132825614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071624
P. Kalaivani, R. P. Kumar, J. Thrshan, R. S. Kolapan
Road accidents have always been freak and unexpected, almost 1.3 million lives have been claimed by motor vehicle based accidents till now. Accidents itself is a rectifiable phenomenon which could be partially averted by proper precaution and care. Using the ARDUINO series of Microcontrollers with compatible sensors and components, the accidents could be reduced in an efficient way. Whenever there is an obstacle while driving, this sensor enables the driver to know the obstacle or other vehicles heading the same way in case of a divider-less road. This kind of sensing provides the driver with a warning to slow down or change his current position far ahead from the event of an accident.
{"title":"Smart collision avoidance and driver alert recognition (SCADAR) system","authors":"P. Kalaivani, R. P. Kumar, J. Thrshan, R. S. Kolapan","doi":"10.1109/SSPS.2017.8071624","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071624","url":null,"abstract":"Road accidents have always been freak and unexpected, almost 1.3 million lives have been claimed by motor vehicle based accidents till now. Accidents itself is a rectifiable phenomenon which could be partially averted by proper precaution and care. Using the ARDUINO series of Microcontrollers with compatible sensors and components, the accidents could be reduced in an efficient way. Whenever there is an obstacle while driving, this sensor enables the driver to know the obstacle or other vehicles heading the same way in case of a divider-less road. This kind of sensing provides the driver with a warning to slow down or change his current position far ahead from the event of an accident.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129805387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071621
Shreya Lal, S. Behera, Dr. Prabira Kumar Sethy, A. Rath
Classification of fruits is an onerous and tedious task because of countless number of fruits. The traditional approach for detection and classification of fruit and its maturity level is based on the naked eye observation by the experts, which is both time consuming and causes eye fatigue. Advance techniques in image processing and machine learning helps to automatic classify and count the fruits, accurately, quickly and non-destructively. A method to automatic detect and classify apple fruit maturity level, whether it is mature or immature based on its color features has been proposed. Images of the apple are resized and Image Processing Techniques are applied for the extraction of apple color components (R, G, B). Artificial Neural Network is used as a classifier to identify and count the mature and immature applesusingcolor components. The proposed model has an accuracy of 98.1%, when all the three attributes are used as an input.
{"title":"Identification and counting of mature apple fruit based on BP feed forward neural network","authors":"Shreya Lal, S. Behera, Dr. Prabira Kumar Sethy, A. Rath","doi":"10.1109/SSPS.2017.8071621","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071621","url":null,"abstract":"Classification of fruits is an onerous and tedious task because of countless number of fruits. The traditional approach for detection and classification of fruit and its maturity level is based on the naked eye observation by the experts, which is both time consuming and causes eye fatigue. Advance techniques in image processing and machine learning helps to automatic classify and count the fruits, accurately, quickly and non-destructively. A method to automatic detect and classify apple fruit maturity level, whether it is mature or immature based on its color features has been proposed. Images of the apple are resized and Image Processing Techniques are applied for the extraction of apple color components (R, G, B). Artificial Neural Network is used as a classifier to identify and count the mature and immature applesusingcolor components. The proposed model has an accuracy of 98.1%, when all the three attributes are used as an input.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071650
S. Sasikala, D. R. Devi
With the increase in recent development in hardware and software technologies, streaming data is used everywhere in today's environment and it is a very difficult task to store, process, investigate and visualize huge volumes of data. One of the most important and challenging issue in the data stream domain is the classification of the big datasets. However the conventional classification methods developed to run in a streaming environment with high use of memory constraints and longer execution running time. Another three major important issues in the data stream classification methods are huge length, conception drift and Feature Selection (FS). In this review paper, we consider the difficult problem of FS algorithms for streaming data, in which the size of streaming data for the feature set is unknown, primary to an inflexible demand in computation constraints, and not every feature is available from classifier model. In order to solve this difficulty, Swarm Intelligence (SI) algorithms are performed on the high dimensionality and streaming big dataset samples which result in increase classification accuracy, less memory consumption and lesser running time when compared to the existing streaming FS algorithms on various datasets. The proposed SI based FS algorithms overcomes the difficulty of the traditional FS algorithms.
{"title":"A review of traditional and swarm search based feature selection algorithms for handling data stream classification","authors":"S. Sasikala, D. R. Devi","doi":"10.1109/SSPS.2017.8071650","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071650","url":null,"abstract":"With the increase in recent development in hardware and software technologies, streaming data is used everywhere in today's environment and it is a very difficult task to store, process, investigate and visualize huge volumes of data. One of the most important and challenging issue in the data stream domain is the classification of the big datasets. However the conventional classification methods developed to run in a streaming environment with high use of memory constraints and longer execution running time. Another three major important issues in the data stream classification methods are huge length, conception drift and Feature Selection (FS). In this review paper, we consider the difficult problem of FS algorithms for streaming data, in which the size of streaming data for the feature set is unknown, primary to an inflexible demand in computation constraints, and not every feature is available from classifier model. In order to solve this difficulty, Swarm Intelligence (SI) algorithms are performed on the high dimensionality and streaming big dataset samples which result in increase classification accuracy, less memory consumption and lesser running time when compared to the existing streaming FS algorithms on various datasets. The proposed SI based FS algorithms overcomes the difficulty of the traditional FS algorithms.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130184026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071641
A. Abdulasik, Dr.K.Suriyakrishnaan
The main objective of designing the project is provide good scalability and increase networks lifespan. Sensor networks faces consequences such as insufficient amount of resources and they are susceptible to environmental condition, thus decreasing lifespan of sensor node. To resolve such issues multi user multiple-input/output (MU-MIMO) system is established in that multi cluster heads are implemented in each cluster to facilitate dual data uploading and to balance workload. Wireless sensor networks which works as a sensor nodes senses the data and SenCar collects information from environment. Then data is forwarded to sink node from SenCar via single or multiple hops. WSN is proved to be a effective in fields like medical, military, home etc. But authentication is essential in such fields. To provide authentication sink generates questions based on selection of SenCar node. An intruder might come and collect whole data in each cluster. To avoid such arrival of intruder, sink uploads the answer to SenCar node for multiple cluster head location based questions.
{"title":"Improvement of network lifetime with security and load balancing mobile data clustering for wireless sensor networks","authors":"A. Abdulasik, Dr.K.Suriyakrishnaan","doi":"10.1109/SSPS.2017.8071641","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071641","url":null,"abstract":"The main objective of designing the project is provide good scalability and increase networks lifespan. Sensor networks faces consequences such as insufficient amount of resources and they are susceptible to environmental condition, thus decreasing lifespan of sensor node. To resolve such issues multi user multiple-input/output (MU-MIMO) system is established in that multi cluster heads are implemented in each cluster to facilitate dual data uploading and to balance workload. Wireless sensor networks which works as a sensor nodes senses the data and SenCar collects information from environment. Then data is forwarded to sink node from SenCar via single or multiple hops. WSN is proved to be a effective in fields like medical, military, home etc. But authentication is essential in such fields. To provide authentication sink generates questions based on selection of SenCar node. An intruder might come and collect whole data in each cluster. To avoid such arrival of intruder, sink uploads the answer to SenCar node for multiple cluster head location based questions.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128092708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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