International Journal Of Imaging

Abstract

ENHANCING CYBERSECURITY USING PYTHON AND MACHINE LEARNING

Author: Trishala , Shiva Sai Udutha , Kiran Kumar , Mrs. Ch. Pravalika

Abstract:

Cybersecurity has become a critical concern in the digital age, with an increasing number of cyber threats targeting individuals and organizations. Traditional security mechanisms, such as rule-based systems and firewalls, are often insufficient to detect and mitigate sophisticated cyberattacks. This paper explores the role of Python and Machine Learning (ML) in enhancing cybersecurity by automating threat detection, anomaly detection, and predictive security measures. Python, with its extensive libraries such as Scikit-learn, TensorFlow, and PyTorch, provides a robust environment for implementing ML models that can analyse vast amounts of security data, identify patterns, and detect potential threats in real-time. ML techniques, including supervised and unsupervised learning, enable the classification of malware, phishing attempts, and network intrusions with high accuracy. Additionally, deep learning models enhance cybersecurity by recognizing complex attack patterns and adapti