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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/3645

    Title: 高互動型Honeypot 風險控管之研析
    The Study on Risk Management for High Interaction Honeypot
    Authors: 王平
    Keywords: 誘捕罐
    Risk analysis
    Intuitionistic Fuzzy Set
    Fuzzy ranking
    Date: 2007-10-20
    Issue Date: 2009-08-15 18:14:53 (UTC+8)
    Abstract: 誘捕網路系統(Honeynet) 可有效降低IDS (Intrusion Detection System) 的高誤報率。透過對駭客行為觀察與病毒的特徵分析,誘捕網路系統可對攻擊事件發出早期警告,提供網路更堅實的保護。然而,駭客亦發展工具以反偵測、破壞,並嘗試加以佔領誘捕網路系統,對其他網路發動攻擊。傳統的風險分析方法著重於危害事件機率的計算及金錢的損失;事實上,面對網際網路不斷變化的危害事件,管理者通常無法蒐集充足的資訊,以分析誘捕網路系統的弱點,進行威脅事件機率的估算。因此本研究假設在缺乏完整的資訊情況,針對誘捕網路系統,提出一個模糊風險分析模式。其運用直覺式模糊集合(Intuitionistic Fuzzy Set, IFS)及模糊排序(fuzzy ranking)指標,發展一套以自然語言基礎的多準則風險分析模式,動態研判誘捕系統的風險等級。Honeynet has successfully employed todecrease the false-alarm rate of IDS. Toeffectively provide an early alarm ofdangers in attack events for protecting thesecurity of organizations, Honeynet isdesigned to capture and analyse the hackerbehaviour and virus signature. However,hackers also develop the anti-honeytechniques and tools to detect, destroy andcompromised against Honeynet forattacking the other networks. In fact, it isquite difficult for users to collect adequateevents to estimate the full vulnerabilities andprobability of threats in the Internet, due tothe rapid change of the emerging maliciousattack and the new computer’svulnerabilities. Therefore, a fuzzy riskassessment model is developed to evaluatethe risk of Honeynet under incompleteinformation. The Intuitionistic Fuzzy Set(IFS) and fuzzy ranking index is introducedto form a multiple criteria decision-making analysis model using natural language forassisting managers to estimate its risk rank.
    Appears in Collections:[資訊管理系所] 研究計畫

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