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Titlebook: Digital Connectivity – Social Impact; 51st Annual Conventi S. Subramanian,R. Nadarajan,Shina Sheen Conference proceedings 2016 Springer Nat

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書目名稱Digital Connectivity – Social Impact
副標(biāo)題51st Annual Conventi
編輯S. Subramanian,R. Nadarajan,Shina Sheen
視頻videohttp://file.papertrans.cn/280/279180/279180.mp4
概述Includes supplementary material:
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Digital Connectivity – Social Impact; 51st Annual Conventi S. Subramanian,R. Nadarajan,Shina Sheen Conference proceedings 2016 Springer Nat
描述.This book constitutes the refereed proceedings of the 51st Annual Convention of the Computer Society of India, CSI 2016, held in Coimbatore, India, in December 2016...The?23 revised papers presented were carefully reviewed and selected from 74 submissions. The theme of CSI 2016, Digital Connectivity - Social Impact, has been selected to highlight the importance of technology in solving social problems and thereby creating a long term impact on society.?The papers are organized in topical sections on information science; computational intelligence; network computing; IT for society..
出版日期Conference proceedings 2016
關(guān)鍵詞artificial intelligence; authentication; data security; image processing; image segmentation; signal proc
版次1
doihttps://doi.org/10.1007/978-981-10-3274-5
isbn_softcover978-981-10-3273-8
isbn_ebook978-981-10-3274-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2016
The information of publication is updating

書目名稱Digital Connectivity – Social Impact影響因子(影響力)




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Gary D. Bouma,Rod Ling,Douglas Prattto authenticate a node. As a first step towards this objective, a lightweight identity based signature for authentication of the sensor nodes is proposed in this paper. The scheme uses “fingerprint”, i.e. a lifetime secure memory fraction in the sensor nodes as a parameter for signature generation.
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Malware Detection Using Higher Order Statistical Parameters as skewness and kurtosis are calculated at the each sub region of band pass frequency image. The region which has the highest skewness and kurtosis value is marked as the malware file. The detection performance of the proposed method has been evaluated by using 1300 portable executable files. The d
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Authentication in Wireless Sensor Networks Using Dynamic Identity Based Signaturesto authenticate a node. As a first step towards this objective, a lightweight identity based signature for authentication of the sensor nodes is proposed in this paper. The scheme uses “fingerprint”, i.e. a lifetime secure memory fraction in the sensor nodes as a parameter for signature generation.
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