TY - JOUR
T1 - A pollution-resistant method for reprogramming (PRMR) in wireless sensor networks
AU - Zhang, Yu
AU - Zhou, Xingshe
AU - Law, Y. W.
AU - Palaniswami, Marimuthu
PY - 2011/6
Y1 - 2011/6
N2 - Aim. The existing security network reprogramming protocols in the open literature are, in our opinion, insufficient for a new generation of network coding-based reprogramming protocols. Therefore we propose our PRMR method that is resistant to pollution attacks (denial-of-service attacks aimed at polluting encoded packets). Sections 1, 2 and 3 explain the core idea of our PRMR method, which employs a combinatorial technique to decode data packets under pollution attacks and a neighbor classification system to isolate the polluters, and which consists of: (1) the combinatorial technique includes the Merkle hash tree and the pair-wise key scheme; (2) the reception node requests a new encoded packet from a neighbor node again and again until the reception node collects enough encoded packets that contain at least φ number of uncorrupted encoded packets to classify node types and to identify suspected polluters; the polluter identification engine is given in Fig. 2. Section 4 uses 12 types of random topological structure to distribute 19 pages of code image to 40 m × 40 m WSN that is composed of 50 nodes to simulate our PRMR method; the simulation results, given in Figs. 4 and 5, and their analysis show preliminarily that: (1) when 20% of the nodes in a 6-degree WSN are polluters, our PRMR method takes only twice as much time to disseminate reprogrammed data as when there is no pollution attack; (2) the decoding times per page per node are 70% more than those without pollution attack.
AB - Aim. The existing security network reprogramming protocols in the open literature are, in our opinion, insufficient for a new generation of network coding-based reprogramming protocols. Therefore we propose our PRMR method that is resistant to pollution attacks (denial-of-service attacks aimed at polluting encoded packets). Sections 1, 2 and 3 explain the core idea of our PRMR method, which employs a combinatorial technique to decode data packets under pollution attacks and a neighbor classification system to isolate the polluters, and which consists of: (1) the combinatorial technique includes the Merkle hash tree and the pair-wise key scheme; (2) the reception node requests a new encoded packet from a neighbor node again and again until the reception node collects enough encoded packets that contain at least φ number of uncorrupted encoded packets to classify node types and to identify suspected polluters; the polluter identification engine is given in Fig. 2. Section 4 uses 12 types of random topological structure to distribute 19 pages of code image to 40 m × 40 m WSN that is composed of 50 nodes to simulate our PRMR method; the simulation results, given in Figs. 4 and 5, and their analysis show preliminarily that: (1) when 20% of the nodes in a 6-degree WSN are polluters, our PRMR method takes only twice as much time to disseminate reprogrammed data as when there is no pollution attack; (2) the decoding times per page per node are 70% more than those without pollution attack.
KW - Combinatorial technique
KW - Neighbor classification system
KW - Network coding
KW - Pollution attack
KW - Reprogramming
KW - Simulation
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=79960985655&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:79960985655
SN - 1000-2758
VL - 29
SP - 443
EP - 448
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 3
ER -