文献类型：期刊文献

英文题名：Magic Train: Design of Measurement Methods against Bandwidth Inflation Attacks

作者：Zhou, Peng[1];Chang, Rocky K. C.[2];Gu, Xiaojing[3];Fei, Minrui[1];Zhou, Jianying[4]

机构：[1]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China;[2]Hong Kong Polytech Univ, Dept Comp, Hong Kong, Hong Kong, Peoples R China;[3]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[4]Inst Infocomm Res, Singapore 138632, Singapore

年份：2018

卷号：15

期号：1

起止页码：98

外文期刊名：IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING

收录：;EI(收录号：20180404670110);WOS:【SCI-EXPANDED(收录号:WOS:000427527100009)】；

基金：The authors would like to thank the Prof. Ioannis Avramo-poulos, the two anonymous reviewers and the editors from TDSC for their constructive comments on this paper. The work was partially supported by National Natural Science Foundation of China under Grant Nos. 61502293, 61533010 and 61205017, the Key Project of Science and Technology Commission of Shanghai Municipality under Grant No. 14JC1402200, and Shanghai Key Laboratory of Power Station Automation Technology. This work is done mostly when P. Zhou was with The Hong Kong Polytechnic University. X. Gu is the corresponding author.

语种：英文

外文关键词：Network measurement; network security; packet train

摘要：Bandwidth measurement is important for many network applications and services, such as peer-to-peer networks, video caching and anonymity services. To win a bandwidth-based competition for some malicious purpose, adversarial Internet hosts may falsely announce a larger network bandwidth. Some preliminary solutions have been proposed to this problem. They can either evade the bandwidth inflation by a consensus view (i.e., opportunistic bandwidth measurements) or detect bandwidth frauds via forgeable tricks (i.e., detection through bandwidth's CDF symmetry). However, smart adversaries can easily remove the forgeable tricks and report an equally larger bandwidth to avoid the consensus analyses. To defend against the smart bandwidth inflation frauds, we design magic train, a new measurement method which combines an unpredictable packet train with estimated round-trip time (RTT) for detection. The inflation behaviors can be detected through highly contradictory bandwidth results calculated using different magic trains or a train's different segments, or large deviation between the estimated RTT and the RTT reported by the train's first packet. Being an uncooperative measurement method, magic train can be easily deployed on the Internet. We have implemented the magic train using RAW socket and LibPcap, and evaluated the implementation in a controlled testbed and the Internet. The results have successfully confirmed the effectiveness of magic train in detecting and preventing smart bandwidth inflation attacks.