Paper Title

EIRA - A Cyberbot

Authors

Madhuvanthi S , Amirithavarshini G

Keywords

Information Security, Security Knowledge Framework

Abstract

Artificial intelligence (AI), speech recognition systems (ASR), and machine learning advancements have made it possible to create clever computer programmes known as chat bots. The user can type commands into chat bots' text-based user interfaces and receive responses in text and text to speech. Chatbots often serve as stateful services, remembering past commands and possibly even conversations. In numerous fields, including customer service, sales, and marketing, a variety of chatbots have been proposed to deliver various functions. In the area of information security, chatbots are not currently being evaluated for use as advisors. However, most people, particularly common users with no technological expertise, are ignorant of numerous information security-related topics. As a result, we suggested in this article a chatbot that serves as an information security advisor. A knowledge base with a JSON file is used by the suggested advisor. By providing correct advice based on many viewpoints from information security experts, such a chatbot might increase awareness in the subject of information security, among other benefits.

How To Cite

"EIRA - A Cyberbot", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.d306-d309, March-2023, Available :https://ijnrd.org/papers/IJNRD2303341.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : d306-d309

Other Publication Details

Paper Reg. ID: IJNRD_188753

Published Paper Id: IJNRD2303341

Downloads: 000118897

Research Area: Computer Science & Technology 

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303341

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303341

About Publisher

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

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