Highly Space Efficient Blacklisting
作者： Marián Kühnel , Ulrike Meyer
DOI: 10.1007/978-3-319-07995-0_48
关键词:
摘要: Many recent mobile devices have CPU units comparable to desktop computers while the storage capacity they offer is significantly reduced, often by a factor of one hundred. This restriction crucial for most current blacklisting solutions which good performance but suffer from large memory consumption. In order improve situation, we propose novel solution operating on compressed lists. For compression, adapt tabular Quine-McCluskey algorithm based concept reduced masks. guarantees that blacklist never larger than original one. l entries in and k prime implicants with highest degree n our optimized top-down reduction requires at + 2 instead kl. Evaluations prove space efficient network address data can save up 74,43% space.
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