Charles Nicholas

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Distributed Intrusion Detection Systems (DIDS) offer an alternative to centralized intrusion detection. Current research indicates that a distributed intrusion detection paradigm may afford greater coverage, consequently providing an increase in security. In some cases, DIDS offer an alternative to centralized analysis, consequently improving scalabity.(More)
We describe an implementation and experiments with a low-distortion randomized projection algorithm [LINI94] that can reduce the number of dimensions in the data by a considerable amount. The performance of the randomized algorithm is compared with that of a popular technique-Principal Component Analysis (PCA). The experiments show that the randomized(More)
Identifying parallel corpora can be an important step in a variety of tasks related to information retrieval. However, at present to identify parallel corpora requires human experts to examine the texts and evaluate their respective contents. We assume in this research that texts which are translations of each other have similarities in their semantic(More)
Malware classification using machine learning algorithms is a difficult task, in part due to the absence of strong natural features in raw executable binary files. Byte n-grams previously have been used as features, but little work has been done to explain their performance or to understand what concepts are actually being learned. In contrast to other work(More)
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