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SIREN - Security Information Retrieval and Extraction eNgine

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Advances in Information Retrieval (ECIR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10772))

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Abstract

Domain specific search engines (DSSE) are gaining popularity because of better search relevance and domain specificity. The growth of IT and internet led to the increase of cyber attacks, however, lack of DSSE for Security is making users refer multiple sites for security information. We demonstrate SIREN, a search engine for ‘Information and Cyber Security’ with coverage and classification at subdomain level and ranking search results based on site credibility. As part of our demonstration, we automated identification of seed URLs (34,007) and related child URLs (400,726) of the security domain using Artificial Bee Colony algorithm. Also, we evaluated functional and non-functional parameters of available open source software stack that can be used for building other DSSEs.

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Notes

  1. 1.

    https://www.ncbi.nlm.nih.gov/pubmed/.

  2. 2.

    https://serc.iiit.ac.in/WEBCred/.

  3. 3.

    https://serc.iiit.ac.in/Bhompoo/infosec.html.

References

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  5. Sanagavarapu, L.M., Sarangi, S., Reddy, Y.R., Varma, V.: Fine grained approach for domain specific seed URL extraction. In: HICSS. IEEE (2018, to be published)

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Author information

Authors and Affiliations

  1. International Institute of Information Technology, Gachibowli, Hyderabad, India

    Lalit Mohan Sanagavarapu, Neeraj Mathur, Shriyansh Agrawal & Y. Raghu Reddy

Authors
  1. Lalit Mohan Sanagavarapu
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  2. Neeraj Mathur
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  3. Shriyansh Agrawal
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  4. Y. Raghu Reddy
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Corresponding author

Correspondence to Lalit Mohan Sanagavarapu .

Editor information

Editors and Affiliations

  1. Department of Informatics, Systems, and Communication, University of Milano-Bicocca, Milan, Italy

    Gabriella Pasi

  2. LIP6 – UPMC/CNRS, University Pierre et Marie Curie, Paris, France

    Benjamin Piwowarski

  3. University of Glasgow, Glasgow, United Kingdom

    Leif Azzopardi

  4. Technical University of Vienna, Vienna, Austria

    Allan Hanbury

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Sanagavarapu, L.M., Mathur, N., Agrawal, S., Reddy, Y.R. (2018). SIREN - Security Information Retrieval and Extraction eNgine. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds) Advances in Information Retrieval. ECIR 2018. Lecture Notes in Computer Science(), vol 10772. Springer, Cham. https://doi.org/10.1007/978-3-319-76941-7_81

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  • DOI: https://doi.org/10.1007/978-3-319-76941-7_81

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76940-0

  • Online ISBN: 978-3-319-76941-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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