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2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)最新文献

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S-SEECH secured - Scalable Energy Efficient Clustering Hierarchy Protocol for Wireless Sensor Network 面向无线传感器网络的S-SEECH安全可扩展节能聚类层次协议
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684176
R. Sandhya, N. Sengottaiyan
{"title":"S-SEECH secured - Scalable Energy Efficient Clustering Hierarchy Protocol for Wireless Sensor Network","authors":"R. Sandhya, N. Sengottaiyan","doi":"10.1109/SAPIENCE.2016.7684176","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684176","url":null,"abstract":"Most of the Wireless Sensor Networks (WSNs) are designed for dedicated applications and more 60% of their energy is wasted in data transmission. Hence, energy efficient routing protocols are required to find the efficient route to minimize the communication overhead. Security is another important factor in WSN. Wireless Sensor Networks (WSNs) need effective security mechanisms because these networks are usually deployed in hostile, unattended environments where the speed and accuracy of data collection is very important. In this study, we propose an energy aware heuristic-based routing protocol scheme to provide energy efficiency and security in WSNs.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129469347","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}
引用次数: 13
Descriptive analysis of Hash Table based Intrusion Detection Systems 基于哈希表的入侵检测系统的描述性分析
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684112
Saumya Raj, Dr. Rajesh
{"title":"Descriptive analysis of Hash Table based Intrusion Detection Systems","authors":"Saumya Raj, Dr. Rajesh","doi":"10.1109/SAPIENCE.2016.7684112","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684112","url":null,"abstract":"Security and the confidentiality during the data transfer are the important metric in the network design. A group of sequential actions to assure the data confidentiality refers the intrusion. Intrusion in network gathers the information related to unauthorized access, and the exploitation of several vulnerabilities raised by attacks. This paper presents the detailed survey of strategies involved in the implementation of Intrusion Detection Systems (IDS) in the network. The survey categorized into five phases namely, IDS, data mining based IDS, multi-agent based IDS, Distributed Hash Table (DHT), and Internet Protocol (IP) based hash table. First phase discusses the structure of IDS with machine learning techniques such as Bayesian classifier, knowledge based, etc. Second, a data mining based IDS conveys how the reliability and security of IDS are improved compared to previous IDS. In the third phase, multi agent based IDS presents the status of coordination issues, false alarm rates and detection rates on application of multiple agents. Finally, a hash table mechanisms (Distributed Hash Table (DHT) & Internet Protocol (IP) based hash table) into the network to improve the matching efficiencies and computational speed. This survey conveys the difficulties in the traditional methods, namely, storage overhead, less matching efficiency, and adaptive nature (dynamically updating of hash tables) and false positive rates. The prediction of attackers or mis-behaving requests and the construction of adaptive reputation constitutes the main problems in IDS that lead to less efficiency. The observation from the survey lead to the stone of extension of Distributed Hash Table (DHT) with fuzzy based rules in order to overcome the difficulties in traditional research works.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130036965","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}
引用次数: 4
A new efficient watershed based color image segmentation approach 一种新的基于分水岭的彩色图像分割方法
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684157
Dibya Jyoti Bora, A. Gupta, F. Khan
{"title":"A new efficient watershed based color image segmentation approach","authors":"Dibya Jyoti Bora, A. Gupta, F. Khan","doi":"10.1109/SAPIENCE.2016.7684157","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684157","url":null,"abstract":"Color image segmentation is an emerging topic in current image processing research. There exist different techniques for the same. Region based approach like watershed algorithm is one of them. But, watershed approach normally results in problems like over segmentation, noise, etc. In this paper, an efficient approach for the color image segmentation is proposed. Here, the input image is converted from RGB to HSV. Then, V channel is extracted from the converted image and normalized between 0 and 1. Otsu's thresholding is applied on the normalized image. The resultant image is then finally segmented with watershed algorithm. The result obtained from the proposed approach is found to be better in comparison to that obtained from the classical watershed algorithm.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125940757","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}
引用次数: 3
VIBGYOR indexing technique for image mining 用于图像挖掘的VIBGYOR索引技术
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684150
Balvant Tarulatha, Namrata Shroff, M. Chaudhary
{"title":"VIBGYOR indexing technique for image mining","authors":"Balvant Tarulatha, Namrata Shroff, M. Chaudhary","doi":"10.1109/SAPIENCE.2016.7684150","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684150","url":null,"abstract":"The numbers of digital images are increasing day by day and mining from large databases is becoming harder & harder. Indexing image data based on text is tiresome and error prone. If the indexing based on low-level feature of the image then it may reduce the workload and mining become faster. In this research paper we propose an indexing technique which indexes the digital images in the database by the highest color percentage. The images will be automatically classified by its own low-level feature i.e. Color. Implementation of this technique will be benefits the image mining.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122316482","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}
引用次数: 7
Rank based efficient task scheduler for cloud computing 基于秩的高效云计算任务调度程序
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684151
Kalpana Ettikyala, Y. V. Latha
{"title":"Rank based efficient task scheduler for cloud computing","authors":"Kalpana Ettikyala, Y. V. Latha","doi":"10.1109/SAPIENCE.2016.7684151","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684151","url":null,"abstract":"Cloud data centers have become crucial infrastructure for computing and data storage that facilitate the development of varied services offered by the cloud. In every datacenter, thousands of virtual servers or virtual machines run at any instance of time which hosts many tasks and in parallel cloud system should keep receiving the batches of task requests. In this context, out of many powered on servers only few targeted servers should fulfill batch of incoming tasks. Hence, task scheduling is an important issue which greatly influences the performance of cloud. The main objective of the scheduling algorithms in cloud environment is to utilize the resources efficiently while balancing the load between resources, to get the minimum execution time. In this paper we designed a rank based efficient task scheduler which effectively utilizes resources and provides high performance than spaceshared and timeshared task schedulers. This algorithm has been tested using CloudSim toolkit and results were compared with spaceshared and timeshared task schedulers.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113043","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}
引用次数: 11
A systematic approach for brain abnormality identification from biomedical images 基于生物医学图像的脑异常识别系统方法
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684175
Rupal Snehkunj, Ashish Jani
{"title":"A systematic approach for brain abnormality identification from biomedical images","authors":"Rupal Snehkunj, Ashish Jani","doi":"10.1109/SAPIENCE.2016.7684175","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684175","url":null,"abstract":"Since many years the brain disease has affected many lives. The mortality rate has not reduced despite of consistent efforts have been made to overcome the problems of brain abnormality. Brain abnormalities (Infections, trauma, seizures, and tumors, hemorrhage (stroke) and others) identification from medical images is challenging and time consuming because of manual or semi-automated approaches. The field needs automatic detection systems. The framework proposed in this paper will fulfill the requirement by classifying certain abnormalities which are malignant and benign in nature. Also, the system will assist the radiologist in accurate prediction of the progression of brain abnormalities which will help the society to save many lives.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134257796","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}
引用次数: 1
Survey on Histogram Equalization method based Image Enhancement techniques 基于直方图均衡化方法的图像增强技术综述
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684156
C. R. Nithyananda, A. Ramachandra, Preethi
{"title":"Survey on Histogram Equalization method based Image Enhancement techniques","authors":"C. R. Nithyananda, A. Ramachandra, Preethi","doi":"10.1109/SAPIENCE.2016.7684156","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684156","url":null,"abstract":"Image Enhancement is the process of improving the image quality for better visibility of images. The visibility and look of image will be decided by human eyes, which varies from person to person. The images resulted by quality measures made by hardware and software may not be always good and are not having natural look. Many methods are introduced to enhance images. Histogram Equalization is the method in which, the histograms of the input images are altered to obtain the enhanced images. In this paper, we studied various methods of Histogram Equalization, the different types are briefly explained and placed in chronological order in table.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132138634","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}
引用次数: 13
A data hiding technique based on magic squares 一种基于魔方的数据隐藏技术
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684144
Sujitha Kurup, Anjana Rodrigues, A. Bhise
{"title":"A data hiding technique based on magic squares","authors":"Sujitha Kurup, Anjana Rodrigues, A. Bhise","doi":"10.1109/SAPIENCE.2016.7684144","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684144","url":null,"abstract":"Steganography, the study of invisible communication, deals with ways of hiding the existence of the communicated data in unsuspected digital media, such that it remains confidential. The objectives to be considered in the steganography methods are high capacity, imperceptibility and robustness. In this paper, a new data hiding scheme based on magic square blocks is proposed to obtain better image quality and higher embedding capacity while scrambling the secret image using magic square provides security. In the proposed method, a secret digit is embedded into each cover pixel pair with the help of a reference matrix consisting of connected magic square blocks. The experimental results evaluated on 6 cover images show that the new scheme can enhance the security significantly compared with other spatial domain based approaches preserving higher visual quality of stego images at the same time.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121253397","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}
引用次数: 1
Speech encryption based on four-dimensional hyperchaotic system 基于四维超混沌系统的语音加密
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684153
F. J. Farsana, K. Gopakumar
{"title":"Speech encryption based on four-dimensional hyperchaotic system","authors":"F. J. Farsana, K. Gopakumar","doi":"10.1109/SAPIENCE.2016.7684153","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684153","url":null,"abstract":"This paper presents speech encryption based on four-dimensional hyperchaotic systems. Higher order chaotic systems can generate pseudo random numbers (PRN) of more complex dynamical properties. Hyper chaotic sequence is proofed with good randomness and unpredictability. In this approach, the speech scrambles are compressed by DCT to reduce residual intelligibility. Coefficients are then masked by PRN to eliminate true sense of original speech signals. Various analysis such as key space, correlation, signal to noise ratio (SNR), and autocorrelation have been also carried out. The results give good correlation and SNR, which validates that the proposed scheme is efficient compared to conventional lower dimensional chaotic cryptosystems. Since the algorithm is simple and four-dimensional, the proposed method is computationally less complex and highly secure against brute-force attack.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116392881","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}
引用次数: 6
A.R.G.O.S: Alertness Rating Gamma Brainwave Observation System 警戒等级伽玛脑波观察系统
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684158
Dhavalkumar H. Joshi, U. Jaliya, D. Thakore
{"title":"A.R.G.O.S: Alertness Rating Gamma Brainwave Observation System","authors":"Dhavalkumar H. Joshi, U. Jaliya, D. Thakore","doi":"10.1109/SAPIENCE.2016.7684158","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684158","url":null,"abstract":"Many accidents in the industry and on the road occurs because of the drowsiness of machine operators or drivers and it results into loss of lives and economy. This factors can be reduced if the drowsy operators or drivers can be identified. This research is conducted for the identification of driver's drowsiness and fatigue using EEG signals and ocular artifacts. Here Neurosky® Mindwave Device has been used to get raw electroencephalogram (EEG) signals from the human brain. On different time intervals then a threshold algorithm is used for the analysis on the real-time data acquired from the Neurosky® Mindwave Device and then Band Pass Filters are utilized to pass particular waves from the basic Gamma Brainwaves: Alpha, Beta, Gamma and Delta. After simulating the scenario in MATLAB we have created a real-time embedded system (A.R.G.O.S.) which provides the alertness alarm if the fatigue state is higher than some value and driver is drowsy. This system works with approximate 1 sec of latency and 96% accuracy.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130223150","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}
引用次数: 3
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