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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (10): 9-14    DOI: 10.11925/infotech.2096-3467.2018.0708
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Using Bayes Theory to Classify Counter Terrorism Intelligence
Li Yongnan()
School of Criminal Investigation and Counter Terrorism, People’s Public Security University of China, Beijing 100038, China
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Abstract  

[Objective] This study modifies Naive Bayes Classifier according to the features of counterterrorism intelligence, aiming to provide a simple and practical way to categorize these data. [Methods] Firstly, we deleted the outliers of terrorism related data, discretized continuous attributes, as well as finished reduction of data with high level correlation. Secondly, we computed conditional probabilities of different attributes. Lastly, we classified new sample dataset based on maximum posteriori hypothesis. [Results] After categorizing the data, we raised probability threshold to partially offset the influence of the data dependence. Only some data of high-level sensitivity needs to be process manually. [Limitations] This method has some restrictions on data independence. In practice, it must be combined with other classification method such as decision tree to cover more intelligence data, and provide information for early warning. [Conclusions] The proposed method, which increases the efficiency of intelligence analysis, is ease of use and has fewer restrictions on the intelligence analysts.

Key wordsBayes Theory      Naive Bayes      Maximum Posteriori Hypothesis      Counter Terrorism Intelligence      Data Mining     
Received: 03 July 2018      Published: 12 November 2018
ZTFLH:  G359 D631  

Cite this article:

Li Yongnan. Using Bayes Theory to Classify Counter Terrorism Intelligence. Data Analysis and Knowledge Discovery, 2018, 2(10): 9-14.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0708     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I10/9

特殊行为轨迹 年龄 特殊外表/穿着 非法集会 性别 涉恐等级
私藏枪支 17 参 加 1
18 穿特殊标记衣物 不参加 1
19 参 加 2
涉嫌洗钱 33 参 加 3
67 戴特殊标记物品 参 加 3
62 不参加 3
65 不参加 2
私藏枪支 38 穿特殊标记衣物 不参加 1
涉嫌洗钱 60 戴特殊标记物品 参 加 1
39 戴特殊标记物品 参 加 3
43 穿特殊标记衣物 不参加 2
涉嫌洗钱 47 穿特殊标记衣物 不参加 1
私藏枪支 49 戴特殊标记物品 参 加 1
涉嫌洗钱 62 参 加 2
涉嫌洗钱 19 戴特殊标记物品 参 加 1
28 不参加 3
私藏枪支 30 戴特殊标记物品 参 加 1
33 不参加 3
20 参 加 3
涉嫌洗钱 27 穿特殊标记衣物 不参加 1
特殊行为轨迹 年龄层 特殊外表/穿着 非法集会 涉恐等级
私藏枪支 青少年 参 加 1
青少年 穿特殊标记衣物 不参加 1
私藏枪支 中壮年 穿特殊标记衣物 不参加 1
涉嫌洗钱 老 年 戴特殊标记物品 参 加 1
涉嫌洗钱 中壮年 穿特殊标记衣物 不参加 1
私藏枪支 中壮年 戴特殊标记物品 参 加 1
涉嫌洗钱 青少年 戴特殊标记物品 参 加 1
私藏枪支 中壮年 戴特殊标记物品 参 加 1
涉嫌洗钱 中壮年 穿特殊标记衣物 不参加 1
涉恐等级条件 涉恐属性 属性值 概率
1 特殊行为轨迹 私藏枪支 4/9
涉嫌洗钱 4/9
1/9
年龄层 老年 1/9
青少年 3/9
中壮年 5/9
特殊外表/穿着 穿特殊标记衣物 4/9
戴特殊标记物品 4/9
1/9
非法集会 参加 5/9
不参加 4/9
2 特殊行为轨迹 3/4
涉嫌洗钱 1/4
年龄层 老年 2/4
中壮年 1/4
青少年 1/4
特殊外表/穿着 穿特殊标记衣物 1/4
3/4
非法集会 参加 2/4
不参加 2/4
3 特殊行为轨迹 涉嫌洗钱 1/7
6/7
特殊外表/穿着 戴特殊标记物品 2/7
5/7
年龄层 老年 2/7
青少年 1/7
中壮年 4/7
非法集会 参加 4/7
不参加 3/7
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