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Inferring Java Security Policies through Dynamic Sandboxing

机译:通过动态沙箱推断Java安全策略

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摘要

Complex enterprise and server-level applications are often written in Java because of its reputation for security. The Java policy language allows users to specify very fine-grained and complex security policies. However, this expressiveness makes it difficult to determine the correct policy with respect to the principle of least privilege. We describe a method for automatically learning the minimum security policy called dynamic sandboxing. A minimal sandbox (security policy) is inferred by observing program execution and expressed in the standard Java policy language. The minimum policy stops Java exploits and learning the policy does not cripple performance, allowing applications to run normally during training.
机译:复杂的企业和服务器级应用程序由于其在安全方面的声誉而经常用Java编写。 Java策略语言允许用户指定非常细粒度和复杂的安全策略。但是,这种表现力使得很难根据最小特权原则确定正确的策略。我们描述了一种自动学习最小安全策略的方法,称为动态沙箱。通过观察程序执行来推断出最小的沙箱(安全策略),并以标准Java策略语言表示。最低策略可阻止Java攻击,并且了解该策略不会削弱性能,从而使应用程序在培训期间能够正常运行。

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