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    請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/28459


    題名: 以決策樹偵測殭屍網路之研究
    HTTP Botnet detection using decision tree
    作者: 鄧氏金銀
    貢獻者: 資訊管理學系
    關鍵詞: Botnet detection
    HTTP botnet
    Data mining
    C & C channels
    HTTP header field
    日期: 2014-06
    上傳時間: 2014-10-07 16:47:00 (UTC+8)
    摘要: 以決策樹偵測殭屍網路之研究
    Botnet is the most dangerous and widespread threat among the diverse forms of malware internet-attacks nowaday. A botnet is a group of damaged computers connected via Internet which are remotely accessed and controlled by hackers to make various network attacks. Malicious activities include DDoS attack, spam, click fraud, identity theft and information phishing. The most basic characteristic of botnets is the use of command and control channels to communicate with botnet and through which bonet can be updated and command. Botnet has become a common and effective tool used by Botmaster in many cyber-attacks. Recently malicious botnets develop to HTTP botnets instead of typical IRC botnets. HTTP botnets is the latest generations of Botnet ,and it use the standard HTTP protocol to contact with their bots. By using the normal HTTP traffic, the bots is consider as normal users of the networks, and the current network security systems cannot detect out them. To solve this problem, a method based on network behavior analysis system was evolved to improve modify and adding new features to the current methods of detecting HTTP-based Botnets and their bots.
    顯示於類別:[資訊管理學系暨資訊管理研究所 ] 博碩士論文

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