Enhancing big data security through integrating XSS scanner into fog nodes for SMEs gain

Pooja Chaudhary, Brij B. Gupta, Xiaojun Chang, Nadia Nedjah, Kwok Tai Chui

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

Advancement in embedded Nano-technologies empowers IoT technology which serves as the backbone technology for many small and medium enterprises. Evolution of smart devices proved as a supreme source of data, denoted as Big data, that is analyzed to instantly extricate constructive and valuable information that helps the organization in many ways. As it may embrace sensitive information, hence, it turned out to be the fascinating target of multitude of attacks that aims at stealing the information, resulting into privacy breaches. XSS attack is one such security attack that supports the attacker to intrude into user's personal space. Therefore, this paper is focused on designing an approach that detects XSS attack in IoT network to protect the data privacy. It employs Convolution Neural Network (CNN) to detect the XSS attack payload after applying certain data preparation methods. This approach helps in preventing privacy breaches which eventually helps the enterprises in strengthening their bond with their users. The experimental results unveiled that the approach achieves a detection accuracy of 99% after the successful execution of data preparation methods.

Original languageEnglish
Article number120754
JournalTechnological Forecasting and Social Change
Volume168
DOIs
Publication statusPublished - Jul 2021

Keywords

  • Big data security
  • Convolution neural network
  • Fog computing
  • Small-and-medium enterprise
  • XSS attack

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