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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a>
Software that covertly monitors user actions, also known as spyware, has become a first-level security threat due to its ubiquity and the difficulty of detecting and removing it. Such software may be inadvertently installed by a user that is casually browsing the web, or may be purposely installed by an attacker or even the owner of a system. This is particularly problematic in the case of utility computing, early manifestations of which are Internet cafes and thin-client computing. Traditional<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11602897_31">doi:10.1007/11602897_31</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ky56oqtjbjdebk4pgkdgub7czm">fatcat:ky56oqtjbjdebk4pgkdgub7czm</a> </span>
more »... trusted computing approaches offer a partial solution to this by significantly increasing the size of the trusted computing base (TCB) to include the operating system and other software. We examine the problem of protecting a user accessing specific services in such an environment. We focus on secure video broadcasts and remote desktop access when using any convenient, and often untrusted, terminal as two example applications. We posit that, at least for such applications, the TCB can be confined to a suitably modified graphics processing unit (GPU). Specifically, to prevent spyware on untrusted clients from accessing the user's data, we restrict the boundary of trust to the client's GPU by moving image decryption into GPUs. This allows us to leverage existing capabilities as opposed to designing a new component from scratch. We discuss the applicability of GPU-based decryption in the two scenarios. We identify limitations due to current GPU capabilities and propose straightforward modifications to GPUs that will allow the realization of our approach.
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