Mark-and-sweep garbage collection in multilevel secure object-oriented database systems

Chiampichetti, Alessandro; Bertino, Elisa; Mancini, Luigi V.

doi:10.1007/3-540-58618-0_74

Cited by 1 publication

(1 citation statement)

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“…Rent collection has also been used to prevent side-channel attacks in a multi-level system [38]. Bertino et al also tackle the problem of designing a garbage collector for a multi-level secure heap [10,19]. These systems are primarily concerned with covert communication channels between tasks of different security levels that are allows to share objects references; by observing when objects are or are not garbage collected, information can be covertly passed.…”

Section: Language-based Resource Accountingmentioning

confidence: 99%

Garbage collector memory accounting in language-based systems

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Rudys

Wallach

Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405)

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Language run-time systems are often called upon to safely execute mutually distrustful tasks within the same runtime, protecting them from other tasks' bugs or otherwise hostile behavior. Well-studied access controls exist in systems such as Java to prevent unauthorized reading or writing of data, but techniques to measure and control resource usage are less prevalent. In particular, most language run-time systems include no facility to account for and regulate heap memory usage on a per-task basis. This oversight can be exploited by a misbehaving task, which might allocate and hold live enough memory to cause a denial-of-service attack, crashing or slowing down other tasks. In addition, tasks can legitimately share references to the same objects, and traditional approaches that charge memory to its allocator fail to properly account for this sharing. We present a method for modifying the garbage collector, already present in most modern language runtime systems, to measure the amount of live memory reachable from each task as it performs its regular duties. Our system naturally distinguishes memory shared across tasks from memory reachable from only a single task without requiring incompatible changes to the semantics of the programming language. Our prototype implementation imposes negligible performance overheads in a variety of benchmarks, yet provides enough information for the expression of rich policies to express the limits on a task's memory usage.

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Section: Language-based Resource Accountingmentioning

confidence: 99%