LS2 is the logic to reason about the property of trusted computing. However, it lacks the capability of modeling the isolation provided by virtualization which is often involved in previous trusted computing system. W...
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Trusted platform module (TPM) has little computation capability, and it is the performance bottleneck of remote attestation. In the scenario where the server is the attestation-busy entity which answers attestation re...
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Discovering the relationship between protein sequence pattern and protein secondary structure is important for accurately predicting secondary structure of protein sequence. A protein secondary structure pattern dicti...
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In recent years, large amounts of uncertain data are emerged with the widespread employment of the new technologies, such as wireless sensor networks, RFID and privacy protection. According to the features of the unce...
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There are hundreds or thousands of web data sources providing data of relevance to a particular domain on the Web, so how to find a suitable set of sources quickly to integrate from a number of sources is becoming mor...
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In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filte...
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In many areas, a lot of data have been modeled by graphs which are subject to uncertainties, such as molecular compounds and protein interaction networks. While many real applications, for example, collaborative filtering, fraud detection, and link prediction in social networks etc, rely on efficiently answering k-nearest neighbor queries (kNN), which is the problem of computing the most "similar" k nodes to a given query node. To solve the problem, in this paper a novel method based on measurement of SimRank is proposed. However, because graphs evolve over time and are uncertainly, the computing cost can be very high in practice to solve the problem using the existing algorithms of SimRank. So the paper presents an optimization algorithm. Introducing path threshold, which is suitable in both determined graph and uncertain graph, the algorithm merely considers the local neighborhood of a given query node instead of whole graph to prune the search space. To further improving efficiency, the algorithm adopts sample technology in uncertain graph. At the same time, theory and experiments interpret and verify that the optimization algorithm is efficient and effective.
Access control is essential to computer security, especially in an open, distributed, networked communication environment. Modern access control model such as UCON aims at accommodating general requirements. Tradition...
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Access control is essential to computer security, especially in an open, distributed, networked communication environment. Modern access control model such as UCON aims at accommodating general requirements. Traditional one such as BLP focuses on specific properties, e.g. confidentiality. Both of these two realms have their limitations. Taking UCON and BLP as case study, this paper explores mutual support of modern and traditional access control models. It investigates BLP's adaptable characteristic in the UCON perspective. First, it constructs properties in the UCON language to manifest the BLP adaptability, which shows that the BLP adaptability can be ensured to function correctly by the UCON framework. Further, it proposes a formal specification for the BLP adaptability under the UCON framework with the Temporal Logic of Actions, which demonstrates that the BLP adaptability is in good consistency with the UCON model. The significance of the paper is twofold. On the one hand, it exhibits that adaptable quality of the traditional BLP model may be ensured theoretically by the philosophy of modern access control. On the other hand, it enriches the real sense of modern access control models by strengthening the power of traditional access control models.
Recommender systems have been accepted as a vital application on the web by offering product advice or information that users might be interested in. Despite its success, similarity-based collaborative filtering suffe...
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