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Enhancement of Detecting Wicked Website Through Intelligent Methods

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Security in Computing and Communications (SSCC 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 625))

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Abstract

Noticeably, different environments of wicked website include different types of information which could be a threat for all web users such as incitement for hacking sites and encouraging them for spreading notions through learning theft networks, Wi-Fi, websites, internet forums, Facebook, email accounts, etc. The proposed work deals with sites to protect from hacking through designing a method that takes full advantage of machine learning and intelligent systems’ capabilities to realize the informative contents. The ultimate goal of this work of research is to understand the system behavior and determine the best solution to secure the vulnerable users, state and society via Random Forest (RF) and Support Vector Machines (SVM) methods instead of traditional methods. Random Forest exhibited Promising Results in terms of accuracy.

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Author information

Authors and Affiliations

  1. Software and Informatics Engineering, College of Engineering, Salahaddin University-Erbil, Hawler, Kurdistan, Iraq

    Tarik A. Rashid

  2. School of Computer Science, College of Science, University of Sulaimania, Sulaimania, Kurdistan, Iraq

    Salwa O. Mohamad

Authors
  1. Tarik A. Rashid
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  2. Salwa O. Mohamad
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Corresponding authors

Correspondence to Tarik A. Rashid or Salwa O. Mohamad .

Editor information

Editors and Affiliations

  1. IBM ZURICH RESEARCH LABORATORY, IBM ZURICH RESEARCH LABORATORY, RUESCHLIKON, Switzerland

    Peter Mueller

  2. Technology and Management, Indian Institute of Information Technology and Management, Kerala, India

    Sabu M. Thampi

  3. Temple University, New York, New York, USA

    Md Zakirul Alam Bhuiyan

  4. Computer Science, University of Waikato Computer Science, Hamilton, New Zealand

    Ryan Ko

  5. Deakin University , Burwood, Victoria, Australia

    Robin Doss

  6. University of the West of Scotland , Paisley, Glasgow, United Kingdom

    Jose M. Alcaraz Calero

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© 2016 Springer Nature Singapore Pte Ltd.

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Rashid, T.A., Mohamad, S.O. (2016). Enhancement of Detecting Wicked Website Through Intelligent Methods. In: Mueller, P., Thampi, S., Alam Bhuiyan, M., Ko, R., Doss, R., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2016. Communications in Computer and Information Science, vol 625. Springer, Singapore. https://doi.org/10.1007/978-981-10-2738-3_31

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  • DOI: https://doi.org/10.1007/978-981-10-2738-3_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2737-6

  • Online ISBN: 978-981-10-2738-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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