Traditional network routing protocol exhibits high statics and singleness, which provide significant advantages for the attacker. There are two kinds of attacks on the network: active attacks and passive attacks. Existing solutions for those attacks are based on replication or detection, which can deal with active attacks; but are helpless to passive attacks. In this paper, we adopt the theory of network coding to fragment the data in the Software-Defined Networks and propose a network coding-based resilient multipath routing scheme. First, we present a new metric named expected eavesdropping ratio to measure the resilience in the presence of passive attacks. Then, we formulate the network coding-based resilient multipath routing problem as an integer-programming optimization problem by using expected eavesdropping ratio. Since the problem is NP-hard, we design a Simulated Annealing-based algorithm to efficiently solve the problem. The simulation results demonstrate that the proposed algorithms improve the defense performance against passive attacks by about 20% when compared with baseline algorithms.
|Title of host publication||Proceedings - IEEE Symposium on Computers and Communications|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - Jun 2019|
|Event||2019 IEEE Symposium on Computers and Communications, ISCC 2019 - Barcelona, Spain|
Duration: 29 Jun 2019 → 3 Jul 2019
|Name||Proceedings - IEEE Symposium on Computers and Communications|
|Conference||2019 IEEE Symposium on Computers and Communications, ISCC 2019|
|Period||29/06/19 → 3/07/19|
Bibliographical noteFunding Information:
VIII.ACKNOWLEDGEMENT This work was supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China under Grant 61521003, the National Key Research and Development Plan under Grant 2016YFB0800101, the National Natural Science Foundation of China under Grant 61602509, the National Key Research and Development Program of China under Grant 2018YFB1003700, the Beijing Natural Science Foundation under Grant Z170003.
© 2019 IEEE.
- integer-programming optimization
- network coding
- Software-Defined Networks