使用AP-TED检测网络钓鱼攻击变化

Sophie Le Page, G. Bochmann, Q. Cui, J. Flood, Guy-Vincent Jourdan, Iosif-Viorel Onut
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引用次数: 3

摘要

众所周知,许多网络钓鱼攻击都是以前的网络钓鱼攻击的变体。我们在这里评估应用Pawlik和Augsten最近实现的树编辑距离(AP-TED)计算作为比较dom和识别类似网络钓鱼攻击实例的方法的可行性。我们还将这种树方法与现有的一种使用标签向量之间的距离来衡量钓鱼网站之间相似性的方法进行了比较。我们观察到,没有一种距离方法可以完美地检测所有类型的网络钓鱼攻击变体。我们发现树形方法对计算设备的要求更高,但它能更好地区分与已知攻击的相似性。我们还介绍了一种方法,在计算树上的成对编辑距离时,相对于对所有数据的AP-TED计算,可以减少99.4%的计算量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using AP-TED to Detect Phishing Attack Variations
It is well known that many phishing attacks are variations of previous phishing attacks. We evaluate here the feasibility of applying Pawlik and Augsten's recent implementation of Tree Edit Distance (AP-TED) calculations as a way to compare DOMs and identify similar phishing attack instances. We also compare this tree method with an existing method that uses the distance between tag vectors to quantity similarity between phishing sites. We observe that no single distance method perfectly detects all types of phishing attack variations. We find that the tree method is more demanding for computing equipment, but it better discriminates the similarity with known attacks. We also introduce a method to reduce the volume of calculations by 99.4% when calculating pairwise edit distance on trees with respect to AP-TED calculations on all data.
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