Large Scale Topology Discovery for Public IPv6 Networks

2008 ◽  
Author(s):  
Zhenshan Liu ◽  
Junyong Luo ◽  
Qingxian Wang
Keyword(s):  
Large Scale ◽  
Topology Discovery ◽  
Ipv6 Networks

Vehicles joint UAVs to acquire and analyze data for topology discovery in large-scale IoT systems

2020 ◽  
Vol 13 (5) ◽  
pp. 1720-1743 ◽  
Author(s):  
Haojun Teng ◽  
Kaoru Ota ◽  
Anfeng Liu ◽  
Tian Wang ◽  
Shaobo Zhang
Keyword(s):  
Large Scale ◽  
Topology Discovery ◽  
Analyze Data

scholarly journals Evaluation of a Large-Scale Topology Discovery Algorithm

2006 ◽  
pp. 193-204 ◽  
Author(s):  
Benoit Donnet ◽  
Bradley Huffaker ◽  
Timur Friedman ◽  
kc claffy
Keyword(s):  
Large Scale ◽  
Topology Discovery

Internet Worm Modeling and Analysis in IPv6 Networks

2011 ◽  
Vol 268-270 ◽  
pp. 1514-1519
Author(s):  
Fei Su ◽  
Wen Jing Xu ◽  
Zhao Wen Lin ◽  
Yan Ma
Keyword(s):  
Defense Mechanisms ◽  
Large Scale ◽  
Local Network ◽  
Modeling And Analysis ◽  
Next Generation Internet ◽  
Internet Worm ◽  
Ipv6 Network ◽  
Worm Model ◽  
Ipv6 Networks ◽  
Scanning Strategies

With the development of IPv6, it is taken as a natural cover to defend against Internet worm due to its huge address space. We demonstrate that an intelligent worm can compromise the IPv6 network according to using adaptive means. Based on the analysis of the scanning strategies in IPv6 network and correlative typical propagation technologies, a general worm model named Next Generation Internet worm model (NGIWM) is established for analyzing the propagation of IPv6 worm which is made up of three layers. The three layers have the function to accelerate the spread of NGIWM, and make NGIWM has the capability to form large scale of prevalence. The result indicates the rationality of scanning strategies and the effectiveness of the propagation compared to IPv4 network worm. The simulation shows that the implementation of NGIWM has the potential to become a major threat to IPv6 network. The performance of the worm depends heavily on domain name generator algorithm and scanning strategies in local network. We also analyze the effect of experiment parameters on the model in the simulation part. In the future, detailed implementation of the proposed model and more defense mechanisms are to be studied.

scholarly journals Deployment of an Algorithm for Large-Scale Topology Discovery

2006 ◽  
Vol 24 (12) ◽  
pp. 2210-2220 ◽  
Author(s):  
B. Donnet ◽  
P. Raoult ◽  
T. Friedman ◽  
M. Crovella
Keyword(s):  
Large Scale ◽  
Topology Discovery

scholarly journals Efficient algorithms for large-scale topology discovery

2005 ◽  
Vol 33 (1) ◽  
pp. 327-338 ◽  
Author(s):  
Benoit Donnet ◽  
Philippe Raoult ◽  
Timur Friedman ◽  
Mark Crovella
Keyword(s):  
Large Scale ◽  
Efficient Algorithms ◽  
Topology Discovery
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