Algorithms for Network Topology Discovery using End-to-End Measurements

2008 ◽  
Author(s):  
Laurent Bobelin ◽  
Traian Muntean
Keyword(s):  
Network Topology ◽  
Topology Discovery ◽  
End To End

Event Driven Network Topology Discovery and Inventory Listing Using REAMS

2015 ◽  
Vol 94 (3) ◽  
pp. 415-430 ◽  
Author(s):  
Amir Azodi ◽  
Feng Cheng ◽  
Christoph Meinel
Keyword(s):  
Network Topology ◽  
Topology Discovery ◽  
Event Driven

scholarly journals Behavior Anomaly Detection in SDN Control Plane: A Case Study of Topology Discovery Attacks

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Li-Der Chou ◽  
Chien-Chang Liu ◽  
Meng-Sheng Lai ◽  
Kai-Cheng Chiu ◽  
Hsuan-Hao Tu ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Network Topology ◽  
Rank Correlation ◽  
Network Routing ◽  
Security Protocol ◽  
Topology Discovery ◽  
Detection Mechanism ◽  
Spearman’S Rank Correlation ◽  
Flooding Attacks ◽  
Man In The Middle

Software-defined networking controllers use the OpenFlow discovery protocol (OFDP) to collect network topology status. The OFDP detects the link between switches by generating link layer discovery protocol (LLDP) packets. However, OFDP is not a security protocol. Attackers can use it to perform topology discovery via injection, man-in-the-middle, and flooding attacks to confuse the network topology. This study proposes a correlation-based topology anomaly detection mechanism. Spearman’s rank correlation is used to analyze the network traffic between links and measure the round-trip time of each LLDP frame to determine whether a topology discovery via man-in-the-middle attack exists. This study also adds a dynamic authentication key and counting mechanism in the LLDP frame to prevent attackers from using topology discovery via injection attack to generate fake links and topology discovery via flooding attack to cause network routing or switching abnormalities.

scholarly journals General Identifiability Condition for Network Topology Monitoring with Network Tomography

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4125 ◽  
Author(s):  
Shengli Pan ◽  
Zongwang Zhang ◽  
Zhiyong Zhang ◽  
Deze Zeng ◽  
Rui Xu ◽  
...  
Keyword(s):  
Network Topology ◽  
Network Monitoring ◽  
Time Varying ◽  
Network Tomography ◽  
Accurate Knowledge ◽  
Cross Traffic ◽  
End To End ◽  
The Cross

Accurate knowledge of network topology is vital for network monitoring and management. Network tomography can probe the underlying topologies of the intervening networks solely by sending and receiving packets between end hosts: the performance correlations of the end-to-end paths between each pair of end hosts can be mapped to the lengths of their shared paths, which could be further used to identify the interior nodes and links. However, such performance correlations are usually heavily affected by the time-varying cross-traffic, making it hard to keep the estimated lengths consistent during different measurement periods, i.e., once inconsistent measurements are collected, a biased inference of the network topology then will be yielded. In this paper, we prove conditions under which it is sufficient to identify the network topology accurately against the time-varying cross-traffic. Our insight is that even though the estimated length of the shared path between two paths might be “zoomed in or out” by the cross-traffic, the network topology can still be recovered faithfully as long as we obtain the relative lengths of the shared paths between any three paths accurately.

Constella: A Complete IP Network Topology Discovery Solution

2007 ◽  
pp. 425-436 ◽  
Author(s):  
Fawad Nazir ◽  
Tallat Hussain Tarar ◽  
Faran Javed ◽  
Hiroki Suguri ◽  
Hafiz Farooq Ahmad ◽  
...  
Keyword(s):  
Network Topology ◽  
Topology Discovery ◽  
Ip Network

SNMP-based enterprise IP network topology discovery

2010 ◽  
Vol 21 (3) ◽  
pp. 169-184 ◽  
Author(s):  
Suman Pandey ◽  
Mi-Jung Choi ◽  
Young J. Won ◽  
James Won-Ki Hong
Keyword(s):  
Network Topology ◽  
Topology Discovery ◽  
Ip Network
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