APT Logic-based Causality Analysis of Terrorist Incidents

doi:10.3969/j.issn.1671-1122.2017.09.022

Abstract

Abstract:

In recent years, terrorist incidents have occurred frequently in the world, which seriously threatens the safety of the international community. The analysis of terrorist incidents has become a hot topic in the field of content security. APT logic proposes a reasoning model for causal relationships of temporal events by establishing rules, which has been widely used in many fields. On the basis of previous works, this paper propose a flexible and extensible causality analysis algorithm of terrorist incidents based on APT logic, and uses the data from the Global Terrorism Database to investigate the causal relationships between terrorist attacks conducted by the ISIS. The paper tests the results and gets some causal relationships between some of the terrorist attacks, which provide help for the study of terrorist incidents.

Key words: causality analysis, APT logic, event analysis, ISIS, terrorist incident

CLC Number:

TP393

Yuhui WANG, Zehua ZENG, Jiahui SHEN, Tianshu FU. APT Logic-based Causality Analysis of Terrorist Incidents[J]. Netinfo Security, 2017, 17(9): 93-97.

Figures/Tables 2

References 13

[1]	CHEN H, REID E, SINAI J, et al.Terrorism Informatics: Knowledge Management and Data Mining for Homeland Security[A]// Integrated Series in Information Systems[M].New York:Springer Publishing Company, Incorporated, 2008.
[2]	LAFREE G, DUGAN L.Introducing the Global Terrorism Database[J]. Terrorism and Political Violence, 2007, 19(2): 181-204.
[3]	LAFREE G.The Global Terrorism Database: Accomplishments and Challenges[J]. Perspectives on Terrorism, 2010, 4(1):24-46.
[4]	王晓东. 事件关联分析在信息安全综合预警中的运用[J]. 信息网络安全, 2005(12):54-55.
[5]	STANTON A, THART A, JAIN A, et al.Mining for Causal Relationships: A Data-Driven Study of the Islamic State[C]// ACM. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '15), August 10 - 13, 2015 . Sydney, NSW, Australia. New York:ACM,2015:2137-2146.
[6]	SUPPES P.A Probabilistic Theory of Causality[M]. Amsterdam: North-Holland Publishing Company, 1970.
[7]	FERNBACH P M, DARLOW A, SLOMAN S A.Asymmetries in Predictive and Diagnostic Reasoning[J]. Journal of Experimental Psychology: General, 2011, 140(2): 168.
[8]	何一青. 一种基于有向二分图模型和贝叶斯网络的入侵检测方法[J]. 信息网络安全, 2012(8):108-111.
[9]	TRUEBLOOD J S, BUSEMEYER J R.A Quantum Probability Model of Causal Reasoning[J]. Frontiers in Psychology, 2012, 3(3):138.
[10]	KLEINBERG S, MISHRA B.The Temporal Logic of Causal Structures[C]//AUAI. Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI '09), June 18 - 21, 2009. Montreal, Quebec, Canada . Arlington: AUAI Press,2009 :303-312.
[11]	KLEINBERG S.A Logic for Causal Inference in Time Series with Discrete and Continuous Variables[C]//IJCAI.Proceedings-International Joint Conference on Artificial Intelligence, July 16 - 22, 2011. Barcelona, Catalonia, Spain. palo alto: AAAI Press,2011: 943-950.
[12]	尹璐, 李斌, 陈立章,等. 基于因果关系的网络安全事件传导路径分析方法[J]. 信息网络安全, 2013(5):35-37.
[13]	SHAKARIAN P, PARKER A, SIMARI G, et al.Annotated Probabilistic Temporal Logic[J]. ACM Transactions on Computational Logic (TOCL), 2011, 12(2): 14.

[1]	Xu ZHAO, Guangqiu HUANG, Yanpeng CUI, Mingming WANG. Improvement of Selection Operator in Multithreading Model for Multimedia Packets in NIDS [J]. Netinfo Security, 2018, 18(10): 45-50.
[2]	Qingyi TIAN, Baoshun LI. Research on Electronic Data Forensics of Small Unmanned Aerial Vehicle [J]. Netinfo Security, 2017, 17(9): 85-88.
[3]	Man ZHAN, Hequn XIAN, Shuguang ZHANG. Research on Identity Authentication Technology Based on Gravity Sensor [J]. Netinfo Security, 2017, 17(9): 58-62.
[4]	Ben QI, Mengdi WANG. A Method Using Information Gain and Naive Bayes to Extract Network Situation Information [J]. Netinfo Security, 2017, 17(9): 54-57.
[5]	Xiaowen DA, Limin MAO, Mingjie WU, Min GUO. Research on a Vulnerability Location Technology Based on Patch Matching and Static Taint Analysis [J]. Netinfo Security, 2017, 17(9): 5-5.
[6]	Weiyang XU, Yao LI, Yong TANG, Baosheng WANG. Research on Cross-architecture Vulnerabilities Searching in Binary Executables [J]. Netinfo Security, 2017, 17(9): 21-25.
[7]	Min GUO, Yingming ZENG, Jinli YAO, Xiaowen DA. The Analysis of Software Behavior Security Based on Big Data Samples [J]. Netinfo Security, 2017, 17(9): 153-156.
[8]	Xuan HAN, Yamin LIU. Research on the Consensus Mechanisms of Blockchain Technology [J]. Netinfo Security, 2017, 17(9): 147-152.
[9]	Shunshun FU, Yijun GU, Dahan ZHANG, Fanpeng MENG. Overlapping Community Detection Algorithm Based on Improved MCMC Method [J]. Netinfo Security, 2017, 17(9): 138-142.
[10]	Juanjuan CHENG, Fangyu ZHENG, Jingqiang LIN, Jiankuo DONG. High-performance Implementation of Curve25519 on GPU [J]. Netinfo Security, 2017, 17(9): 122-127.
[11]	WANG Zihan, WANG Yuhui, WANG Lei, WANG Xin. Research on a Topic Evolution Analysis System of Emergency Based on Social Media [J]. 信息网络安全, 2017, 17(9): 98-102.
[12]	Ping WANG, Zhiping ZHOU. An Improved RFID Ownership Transfer Protocol Based on Cloud [J]. Netinfo Security, 2017, 17(8): 60-68.
[13]	Yanwei TIAN, Songru YANG, Jie LI. Research on Risks and Countermeasures of Wireless WiFi Key APP [J]. Netinfo Security, 2017, 17(7): 80-84.
[14]	Zixian XU, Jian LUO, Nan MENG, Xiangnan ZHAO. Research on Configuration Software for Industrial Control System [J]. Netinfo Security, 2017, 17(7): 73-79.
[15]	Yifang ZHAO, Dongmei ZHANG. A Network Topology Discovery Algorithm Resistant to Routing Spoofing [J]. Netinfo Security, 2017, 17(7): 52-58.