计算机科学
无人机
无线
钥匙(锁)
协议(科学)
二进制数
联想(心理学)
逆向工程
匹配(统计)
数据挖掘
精确性和召回率
计算机网络
人工智能
计算机安全
电信
医学
哲学
统计
遗传学
替代医学
算术
数学
认识论
病理
生物
程序设计语言
作者
Ran Ji,Haifeng Li,Chaojing Tang
标识
DOI:10.1109/cis.2016.0076
摘要
Unmanned Aerial Vehicles (UAVs) are increasingly popular. As a result of the tremendous number of UAVs, especially recreational UAVs, regulation becomes a challenge we are confronted with. Protocol reverse engineering offers a way to understand and regulate the drones effectively. Extracting keywords is an indispensable fundamental work for protocol reverse engineering. However, to the best of our knowledge, there are few works in the literature that openly address the issues of extracting keywords of UAVs communication protocols. In this paper, we propose a framework to extract keywords from the binary data collected from wireless communication channels of UAVs. Firstly, we capture the binary streams and segment into frames. And then we find frequent sequences utilizing multi-pattern matching algorithms. After that, we extract keywords based on frequency and analyze the association rules among these key words. Our experimental results show that 8-bit sequences such as 0x20, 0x60, 0x01, 0x09, 0xFF, 0x0A, 0x0D, 0x7D, 0x1F, 0x51, 0x49, etc. are keywords. And our framework identify frames of UAVs with a precision rate about 88% and a recall rate of around 87%.
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