IntelShield Integrating Artificial Intelligence in Cyber Threat Intelligence (CTI) Tool to Detect Real Time Threats

Recent scenarios of companies are struggling with complex vulnerabilities.Hence, there is need of an Automated tool to overcome the longest time frame to cover the gap from forensics and cybercrime.This paper presents an innovative approach to automating Cyber Threat Intelligence processes designed to ingest, analyze, display and respond to emerging threats in real time.Formerly, CTI used to rely heavily on manual methods for collecting, interpreting and analyzing data which was not only time consuming but also prone to inefficiencies, especially when rapid information dissemination is critical.IntelShield integrates multiple open-source intelligence feeds, does real time active network monitoring, severity scoring, triggers automated alerts via SMS using Twilio and displays threats on a user friendly dashboard.It also employs Natural Language Processing(NLP) to extract indicators of compromise (IOCs) from unstructured sources such as security blogs, reports, and dark web forums.Machine learning techniques are used to classify, prioritize, and correlate IOCs based on their severity and contextual relevance.This research highlights the transformative potential of AI-driven technologies to enhance both the speed and accuracy of CTI.

Publication Details

Journal
IJARCCE
Published
2025-05-30
DOI
https://doi.org/10.17148/ijarcce.2025.145120
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

IntelShield Integrating Artificial Intelligence in Cyber Threat Intelligence (CTI) Tool to Detect Real Time Threats

IJARCCE
Network Security and Intrusion Detection
article

IntelShield Integrating Artificial Intelligence in Cyber Threat Intelligence (CTI) Tool to Detect Real Time Threats

article en

Abstract

Recent scenarios of companies are struggling with complex vulnerabilities.Hence, there is need of an Automated tool to overcome the longest time frame to cover the gap from forensics and cybercrime.This paper presents an innovative approach to automating Cyber Threat Intelligence processes designed to ingest, analyze, display and respond to emerging threats in real time.Formerly, CTI used to rely heavily on manual methods for collecting, interpreting and analyzing data which was not only time consuming but also prone to inefficiencies, especially when rapid information dissemination is critical.IntelShield integrates multiple open-source intelligence feeds, does real time active network monitoring, severity scoring, triggers automated alerts via SMS using Twilio and displays threats on a user friendly dashboard.It also employs Natural Language Processing(NLP) to extract indicators of compromise (IOCs) from unstructured sources such as security blogs, reports, and dark web forums.Machine learning techniques are used to classify, prioritize, and correlate IOCs based on their severity and contextual relevance.This research highlights the transformative potential of AI-driven technologies to enhance both the speed and accuracy of CTI.

IJARCCEVol. 14(5)
Openalex Percentile: Top 87%
Network Security and Intrusion Detection
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