823 research outputs found
Classifying Web Exploits with Topic Modeling
This short empirical paper investigates how well topic modeling and database
meta-data characteristics can classify web and other proof-of-concept (PoC)
exploits for publicly disclosed software vulnerabilities. By using a dataset
comprised of over 36 thousand PoC exploits, near a 0.9 accuracy rate is
obtained in the empirical experiment. Text mining and topic modeling are a
significant boost factor behind this classification performance. In addition to
these empirical results, the paper contributes to the research tradition of
enhancing software vulnerability information with text mining, providing also a
few scholarly observations about the potential for semi-automatic
classification of exploits in the existing tracking infrastructures.Comment: Proceedings of the 2017 28th International Workshop on Database and
Expert Systems Applications (DEXA).
http://ieeexplore.ieee.org/abstract/document/8049693
Delta bloom filter compression using stochastic learning-based weak estimation
Substantial research has been done, and sill continues, for reducing the bandwidth requirement and for reliable access to the data, stored and transmitted, in a space efficient manner. Bloom filters and their variants have achieved wide spread acceptability in various fields due to their ability to satisfy these requirements.
As this need has increased, especially, for the applications which require heavy use of the transmission bandwidth, distributed computing environment for the databases or the proxy servers, and even the applications which are sensitive to the access to the information with frequent modifications, this thesis proposes a solution in the form of compressed delta Bloom filter.
This thesis proposes delta Bloom filter compression, using stochastic learning-based weak estimation and prediction with partial matching to achieve the goal of lossless compression with high compression gain for reducing the large data transferred frequently
- …