Research on attack scenario reconstruction method based on causal knowledge discovery

In order to discover the attack pattern from the distributed alert data and construct the attack scene,a method of finding the attack scene from the alert data generated by intrusion detection system was studied.Current research suffer from the problem that causal knowledge is complex and difficult...

Full description

Saved in:
Bibliographic Details
Main Authors: Di FAN, Jing LIU, Jun-xi ZHUANG, Ying-xu LAI
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2017-04-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00148
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1841530232591351808
author Di FAN
Jing LIU
Jun-xi ZHUANG
Ying-xu LAI
author_facet Di FAN
Jing LIU
Jun-xi ZHUANG
Ying-xu LAI
author_sort Di FAN
collection DOAJ
description In order to discover the attack pattern from the distributed alert data and construct the attack scene,a method of finding the attack scene from the alert data generated by intrusion detection system was studied.Current research suffer from the problem that causal knowledge is complex and difficult to understand and it is difficult to automatically acquire the problem.An attack scenario reconstruction method based on causal knowledge discovery was proposed.According to the process of KDD,the sequence set of attack scenes was constructed by the correlation degree of IP attributes among alert data.Time series modeling was adopted to eliminate the false positives to reduce the attack scene sequence.Finally,causal relationship between the alert data was found by using probability statistics.Experiments on the DARPA2000 intrusion scenario specific data sets show that the method can effectively identify the multi-step attack mode.
format Article
id doaj-art-a218eb7dd5ea491daabaf2c40265f2f7
institution Kabale University
issn 2096-109X
language English
publishDate 2017-04-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-a218eb7dd5ea491daabaf2c40265f2f72025-01-15T03:05:42ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2017-04-013586859550327Research on attack scenario reconstruction method based on causal knowledge discoveryDi FANJing LIUJun-xi ZHUANGYing-xu LAIIn order to discover the attack pattern from the distributed alert data and construct the attack scene,a method of finding the attack scene from the alert data generated by intrusion detection system was studied.Current research suffer from the problem that causal knowledge is complex and difficult to understand and it is difficult to automatically acquire the problem.An attack scenario reconstruction method based on causal knowledge discovery was proposed.According to the process of KDD,the sequence set of attack scenes was constructed by the correlation degree of IP attributes among alert data.Time series modeling was adopted to eliminate the false positives to reduce the attack scene sequence.Finally,causal relationship between the alert data was found by using probability statistics.Experiments on the DARPA2000 intrusion scenario specific data sets show that the method can effectively identify the multi-step attack mode.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00148intrusion detectionalert correlationtime series modelingattack scenario reconstruction
spellingShingle Di FAN
Jing LIU
Jun-xi ZHUANG
Ying-xu LAI
Research on attack scenario reconstruction method based on causal knowledge discovery
网络与信息安全学报
intrusion detection
alert correlation
time series modeling
attack scenario reconstruction
title Research on attack scenario reconstruction method based on causal knowledge discovery
title_full Research on attack scenario reconstruction method based on causal knowledge discovery
title_fullStr Research on attack scenario reconstruction method based on causal knowledge discovery
title_full_unstemmed Research on attack scenario reconstruction method based on causal knowledge discovery
title_short Research on attack scenario reconstruction method based on causal knowledge discovery
title_sort research on attack scenario reconstruction method based on causal knowledge discovery
topic intrusion detection
alert correlation
time series modeling
attack scenario reconstruction
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00148
work_keys_str_mv AT difan researchonattackscenarioreconstructionmethodbasedoncausalknowledgediscovery
AT jingliu researchonattackscenarioreconstructionmethodbasedoncausalknowledgediscovery
AT junxizhuang researchonattackscenarioreconstructionmethodbasedoncausalknowledgediscovery
AT yingxulai researchonattackscenarioreconstructionmethodbasedoncausalknowledgediscovery