Keyboard layout errors and homoglyphs in cross-language queries impact our abil-ity to correctly interpret user informa-tion needs and offer relevant results. We present a machine learning approach to correcting these errors, based largely on character-level n-gram features. We demonstrate superior performance over rule-based methods, as well as a signif-icant reduction in the number of queries that yield null search results. 1

The trend towards common user packet switched networks has increased the need for the provision of adequate end-to-end security techniques in order to protect the data of individual groups of network users. The techniques which can be employed in order to provide adequate end-to-end security measures are considered in this paper frc,mamilitary perspective, where the security requirements are particularly stringent. The paper concludes with a consideration of the practical application of these security techniques in an experimental military packet switched network.