TY - GEN
T1 - Accurate traffic replay based on interactive sequence and timestamp
AU - Wu, Hao
AU - Liu, Hongri
AU - Wang, Bailing
AU - Xin, Guodong
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - Existing traffic replay methods are mainly aim to generate a large number of network traffic per unit time, which neglect the time's authenticity of replay traffic. In order to generate the network traffic which is exactly the same as the real traffic in the target network, including packet's numbers, payloads, interactive orders and time series, this paper proposes a traffic replay method based on packet's interactive sequence and timestamp. Firstly, zero-copy technology is used to capture network traffic in real network, Then the flows are processed by data processing operations such as de-duplicating, ip-address mapping and filtering. Finally, network traffic is generated accurately in the target network by the replay program. The experimental results show that the traffic which is generated by our methods is completely consistent with the original traffic at packet's numbers, payloads, interaction orders. In addition, the similarity of the interaction time is averaged at 99.9%, which confirms that this method is correct and feasible.
AB - Existing traffic replay methods are mainly aim to generate a large number of network traffic per unit time, which neglect the time's authenticity of replay traffic. In order to generate the network traffic which is exactly the same as the real traffic in the target network, including packet's numbers, payloads, interactive orders and time series, this paper proposes a traffic replay method based on packet's interactive sequence and timestamp. Firstly, zero-copy technology is used to capture network traffic in real network, Then the flows are processed by data processing operations such as de-duplicating, ip-address mapping and filtering. Finally, network traffic is generated accurately in the target network by the replay program. The experimental results show that the traffic which is generated by our methods is completely consistent with the original traffic at packet's numbers, payloads, interaction orders. In addition, the similarity of the interaction time is averaged at 99.9%, which confirms that this method is correct and feasible.
KW - component
KW - interactive sequence
KW - timestamp
KW - traffic replay
UR - https://www.scopus.com/pages/publications/85049089539
U2 - 10.1109/ICCSN.2017.8230282
DO - 10.1109/ICCSN.2017.8230282
M3 - 会议稿件
AN - SCOPUS:85049089539
T3 - 2017 9th IEEE International Conference on Communication Software and Networks, ICCSN 2017
SP - 1107
EP - 1110
BT - 2017 9th IEEE International Conference on Communication Software and Networks, ICCSN 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Communication Software and Networks, ICCSN 2017
Y2 - 6 May 2017 through 8 May 2017
ER -