International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI Powered Solution for Securing Domain Name System (DNS): Malicious URL Detection and Counter Measures |
|---|---|
| ABSTRACT | Cyber threats such as phishing, domain spoofing, and malicious hosting have significantly increased with the rapid expansion of online services. Detecting suspicious and malicious domains has become a crucial requirement for individuals, enterprises, and cybersecurity systems. This paper presents the Domain Security Analyzer, an automated AI-assisted framework designed to evaluate and classify domain security risks using WHOIS information, DNS records, IP metadata, and threat intelligence. The system integrates multiple external intelligence sources including WHOIS lookup, DNS resolvers, IP geolocation APIs, and the IPQualityScore (IPQS) reputation engine to construct a multilayered domain security assessment. An AI-based heuristic reasoning model further interprets domain properties and provides human-readable security insights. The application is implemented using a Flask-based backend, Python libraries, and a frontend dashboard supporting OTP-based authentication, automated report delivery, and PDF generation. Evaluation results demonstrate that the system effectively identifies malicious or misconfigured domains, provides accurate classifications, and produces meaningful analysis summaries. The proposed solution enhances automation, improves reliability, and can be extended for enterprise-level cybersecurity monitoring. |
| AUTHOR | PROF. MADHU N HIREMATH, CHANDANA L S, NIHARIKA V, KAVANA M V, VAIBHAV M Assistant Professor, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India UG Student, Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312009 |
| pdf/9_AI Powered Solution for Securing Domain Name System (DNS) Malicious URL Detection and Counter Measures.pdf | |
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