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Research and Development of Wireless Protocol Automatic Analyzer
Woorim Bang, Youngbae Jeon, Shinwoo Shim, Kwangsoo Kim, Ji Won Yoon
http://doi.org/10.5626/JOK.2019.46.8.852
Automatic Protocol Reverse Engineering (APRE) defines automatic analysis of the format, semantics, and parameters of an unknown protocol. APRE can be used to detect malware that is distributed on the network, or for security and suitability verification of protocols that have been defined own their own. Conventional APRE studies have been conducted mostly on text-based protocols and wired protocols. As the number of wireless devices increases, there is an increasing need for a protocol analyzer for wireless protocols. Therefore, in this paper, research and development of the protocol automatic analyzer were performed by considering the characteristics of the wireless protocols. For the analysis of the wireless protocol, this study analyzed the messages in binary units. We propose a method to calculate the message distance by assigning a weight according to the packet acquisition time interval to perform clustering among similar messages. As a result of collecting and analyzing the messages according to the IEEE 802.11 protocol using the proposed method, we could correctly classify 95.1% message types among 800messages, and the degree of conciseness was 3.6. By using one of the existing APRE tools, Netzob, 92.1% precision was obtained with the conciseness of 3.5. Consequently, the proposed method showed better performance than Netzob.
ENF based Detection of Forgery and Falsification of Digital Files due to Quadratic Interpolation
http://doi.org/10.5626/JOK.2018.45.3.311
Recently, the use of digital audio and video as proof in criminal and all kinds of litigation is increasing, and scientific investigation using digital forensic technique is developing. With the development of computing and file editing technologies, anyone can simply manipulate video files, and the number of cases of manipulating digital data is increasing. As a result, the integrity of the evidence and the reliability of the evidence Is required. In this paper, we propose a technique for extracting the Electrical Network Frequency (ENF) through a grid of power grids according to the geographical environment for power supply, and then performing signal processing for peak detection using QIFFT. Through the detection algorithm using the standard deviation, it was confirmed that the video file was falsified with 73% accuracy and the forgery point was found.
Analysis System for SNS Issues per Country based on Topic Model
As the use of SNS continues to increase, various related studies have been conducted. According to the effectiveness of the topic model for existing theme extraction, a huge number of related research studies on topic model based analysis have been introduced. In this research, we suggested an automation system to analyze topics of each country and its distribution in twitter by combining world map visualization and issue matching method. The core system components are the following three modules; 1) collection of tweets and classification by nation, 2) extraction of topics and distribution by country based on topic model algorithm, and 3) visualization of topics and distribution based on Google geochart. In experiments with USA and UK, we could find issues of the two nations and how they changed. Based on these results, we could analyze the differences of each nation"s position on ISIS problem.
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