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Web Content Filtering

Web Content Filtering

Elisa Bertino, Elena Ferrari, Andrea Perego
Copyright: © 2006 |Pages: 21
ISBN13: 9781591405887|ISBN10: 1591405882|ISBN13 Softcover: 9781591405894|EISBN13: 9781591405900
DOI: 10.4018/978-1-59140-588-7.ch006
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MLA

Bertino, Elisa, et al. "Web Content Filtering." Web and Information Security, edited by Elena Ferrari and Bhavani Thuraisingham, IGI Global, 2006, pp. 112-132. https://doi.org/10.4018/978-1-59140-588-7.ch006

APA

Bertino, E., Ferrari, E., & Perego, A. (2006). Web Content Filtering. In E. Ferrari & B. Thuraisingham (Eds.), Web and Information Security (pp. 112-132). IGI Global. https://doi.org/10.4018/978-1-59140-588-7.ch006

Chicago

Bertino, Elisa, Elena Ferrari, and Andrea Perego. "Web Content Filtering." In Web and Information Security, edited by Elena Ferrari and Bhavani Thuraisingham, 112-132. Hershey, PA: IGI Global, 2006. https://doi.org/10.4018/978-1-59140-588-7.ch006

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Abstract

The need to filter online information in order to protect users from possible harmful content can be considered as one of the most compelling social issues derived from the transformation of the Web into a public information space. Despite that Web rating and filtering systems have been developed and made publicly available quite early, no effective approach has been established so far, due to the inadequacy of the proposed solutions. Web filtering is then a challenging research area, needing the definition and enforcement of new strategies, considering both the current limitations and the future developments of Web technologies—in particular, the upcoming Semantic Web. In this chapter, we provide an overview of how Web filtering issues have been addressed by the available systems, bringing in relief both their advantages and shortcomings, and outlining future trends. As an example of how a more accurate and flexible filtering can be enforced, we devote the second part of this chapter to describing a multi-strategy approach, of which the main characteristics are the integration of both list- and metadata-based techniques and the adoption of sophisticated metadata schemes (e.g., conceptual hierarchies and ontologies) for describing both users’ characteristics and Web pages content.

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