CYBER GUARD - A COMPREHENSIVE MULTIVECTOR SECURITY ANALYSIS

J sangeeta, A shiva Kumar, A Deekshitha Reddy, Arshad Afnan, A Revanth Yadav

doi:10.62643/

Authors

J sangeeta, A shiva Kumar, A Deekshitha Reddy, Arshad Afnan, A Revanth Yadav Author

DOI:

https://doi.org/10.62643/

Keywords:

Cybersecurity, multi-vector threat detection, Phishing detection, Malware analysis, Machine learning, Optical character recognition, Web security, Threat intelligence, Virus Total, Flask-based systems

Abstract

The exponential growth of internet usage and digital communication has significantly increased the risk of cyber threats
targeting users across multiple platforms. Modern cyberattacks are no longer limited to a single medium but are distributed
across various data formats such as textual messages, malicious URLs, embedded content in images, QR codes, and mobile
applications. Traditional security tools, however, remain largely specialized, focusing on isolated threat vectors, which
results in fragmented and incomplete protection. This research presents Cyber Guard, a comprehensive multi-vector
cybersecurity framework designed to address these limitations by providing a unified threat detection system capable of
analyzing diverse input formats within a single platform.The proposed system integrates multiple detection mechanisms,
including signature-based analysis for identifying known attack patterns, machine learning models for detecting previously
unseen suspicious behavior, optical character recognition (OCR) techniques for extracting hidden textual content from
images and QR codes, and cloud-based threat intelligence through VirusTotal APIs for validating executable files such as
APKs. This layered approach enhances detection accuracy and minimizes false positives while maintaining efficient
processing times. The system is implemented as a lightweight web application using Flask and modular Python libraries,
ensuring scalability, portability, and ease of deployment. Experimental observations indicate that combining heterogeneous
detection techniques significantly improves threat identification compared to standalone approaches. The platform also
emphasizes usability by presenting results in a simplified and interpretable manner, making it accessible to both technical
and non-technical users. Overall, Cyber Guard contributes to the development of integrated cybersecurity solutions that are
capable of addressing the evolving landscape of multi-format digital threats