下一代Pub Date : 2016-10-01DOI: 10.1109/INCITE.2016.7857617
N. Hitaswi, K. Chandrasekaran
{"title":"A bio-inspired model to provide data security in cloud storage","authors":"N. Hitaswi, K. Chandrasekaran","doi":"10.1109/INCITE.2016.7857617","DOIUrl":"https://doi.org/10.1109/INCITE.2016.7857617","url":null,"abstract":"The demand for cloud computing is increasing rapidly because of the advantages it provides to the customers like, pay as you use, self-serving, elastic, sharing of resources, ease of use, and accessibility. Due to the increase in the usage of the technology, there exists a high chance of compromising the security of the data being stored on the cloud. The major hindrance in the usage of the technology is the security concerns which accompany it. This increases the demand for a robust security mechanism to protect the data on the cloud. So as to overcome this drawback of cloud computing, encrypting the data to be stored on the cloud is one of the solutions. As part of this paper, a security mechanism to improve the security of data in cloud storage is suggested. The security mechanism used is inspired by the bio-inspired genetic algorithm. The inspiration behind the proposed security model is an amalgamation of genetic algorithm and attribute based encryption. As per the methodology proposed the data need to be encrypted before being stored on the cloud. This way the cloud service provider is unaware of the data being stored and even if the data is compromised to some third party, there is no information leakage.","PeriodicalId":59618,"journal":{"name":"下一代","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80355442","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}
下一代Pub Date : 2016-10-01DOI: 10.1109/INCITE.2016.7857621
Manmeet Kaur, N. Bawa
{"title":"Alignment based method using clustering and distance evaluation for construction of phylogenetic tree","authors":"Manmeet Kaur, N. Bawa","doi":"10.1109/INCITE.2016.7857621","DOIUrl":"https://doi.org/10.1109/INCITE.2016.7857621","url":null,"abstract":"Due to the addition of more and more data in the field of proteomics, the computational methodology needs to be very efficient. The most resistant part of molecular sequence is functionally more important to the molecule. Various alignment techniques are analyzed to ensure the reliability of sequence alignment. For the proposed work Multiple Sequence Alignment is used which is a part of evolutionary history. MSA aligns multiple sequences at a time by finding homologous correspondence between each individual sequence position. Various Medicago Sativa varieties are loaded from NCBI databank. Based on the alignment of these, for the divided parts of the dataset, Phylogenetic Trees are constructed. Using advance pruning techniques, a single tree is formed from the previously generated trees. By applying the threshold conditions, closely related sequences are obtained. For optimal sequence alignment shift operations are applied in both directions.","PeriodicalId":59618,"journal":{"name":"下一代","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77680509","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}
下一代Pub Date : 2016-10-01DOI: 10.1109/INCITE.2016.7857600
Awadhesh Kumar Singh, A. K. Singh
{"title":"Centroid-based primary user localization in Cognitive Radio Network using RSS","authors":"Awadhesh Kumar Singh, A. K. Singh","doi":"10.1109/INCITE.2016.7857600","DOIUrl":"https://doi.org/10.1109/INCITE.2016.7857600","url":null,"abstract":"The information about the positions of the primary users (PUs) is imperative for the functioning of Cognitive Radio Networks (CRNs) as it may turn out to be advantageous for improving the utilization of spectrum and also for avoiding the detrimental intervention. Extant Range-based techniques fail to work in some scenarios i.e. If the condition required for the application of trilateration method is not fulfilled which means the circle drawn for the SUs have no common point of intersection between them. Through this work we are moving one step further in making the CRN work more efficiently by presenting a Centroid based licensed user localization technique to get the location of PU (i.e. the licensed user) using RSS. The proposed method counts on the information obtained from three SUs and the Centroid concept to accomplish the localization process.","PeriodicalId":59618,"journal":{"name":"下一代","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85420818","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}
下一代Pub Date : 2016-10-01DOI: 10.1109/INCITE.2016.7857624
Anita Thakur, M. Malik, Nishtha Phutela, P. Khare, Prashant Mor
{"title":"CBCT image noise reduction and enhancement using Bi-Histogram method with bent activation function","authors":"Anita Thakur, M. Malik, Nishtha Phutela, P. Khare, Prashant Mor","doi":"10.1109/INCITE.2016.7857624","DOIUrl":"https://doi.org/10.1109/INCITE.2016.7857624","url":null,"abstract":"Dental, oral and maxillofacial region are very sensitive so low radiation imaging technique like Cone Beam Computed Tomography (CBCT) is useful for investigation of diseases. But due to low radiation, quality of images is not fine they have noise and low contrast in visual impression. So for dentistry diagnostic purpose it is important to pre-process the CBCT image. This paper focuses on improvement of contrast, brightness and noise reduction of dental CBCT images by using Bi Histogram Equalization technique with bent activation function and adaptive median filter for noise reduction. The output image has been analyzed and evaluated using peak value ratio in term of Signal versus Noise (PSNR) and matrix of Structure in term of Similarity Index (SSIM). From the experimental results, it has been found that the adaptive median and Bi histogram with bent activation function has a better noise and enhancement capability as compare to convectional histogram method.","PeriodicalId":59618,"journal":{"name":"下一代","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87341217","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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