DocumentCode
691815
Title
Secure Distribution of Big Data Based on BitTorrent
Author
Limin Xiao ; Chunjie Xu ; Jingchao Qin ; Guangjun Qin ; Mingfa Zhu ; Li Ruan ; Zhiyao Wang ; Mingquan Li ; Dongyu Tan
Author_Institution
State Key Lab. of Software Dev. Environ., Beihang Univ., Beijing, China
fYear
2013
fDate
21-22 Dec. 2013
Firstpage
82
Lastpage
90
Abstract
Recently, big data becomes more and more widespread on the Internet, as various P2P protocols, especially BitTorrent, make great contribution. Accompanied with BitTorrent spreading, however, malicious activities, divulging sensitive data and other security problems arise. Relative researches and analyses indicate that existing means of protecting P2P network are sophisticated but intricate when distributing big data, leading inefficiency of implementation. In this paper, a scheme to distribute big data securely and efficiently on BitTorrent network is proposed, which can be implemented in server, authorizing peers´ admittances and actions, hence protecting sensitive data in the network. To achieve this goal, identity verification and cipher system are embedded into BitTorrent protocol, enabling the server to regulate and keep trace of peers´ behaviors and sensitive data. The experimental results show the functional effectiveness of this scheme, as well as acceptable overhead on server.
Keywords
Big Data; Internet; authorisation; cryptography; peer-to-peer computing; protocols; BitTorrent network; BitTorrent protocol; Internet; P2P network protection; P2P protocol; big data secure distribution; cipher system; identity verification; malicious activities; peer action authorization; peer admittance authorization; peer behavior; security problems; sensitive data protection; server overhead; Big data; Ciphers; Peer-to-peer computing; Protocols; Servers; big data distribution; encryption; security;
fLanguage
English
Publisher
ieee
Conference_Titel
Dependable, Autonomic and Secure Computing (DASC), 2013 IEEE 11th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-3380-8
Type
conf
DOI
10.1109/DASC.2013.42
Filename
6844342
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