Proactive Cyber Defense: Utilizing AI for Early Threat Detection and Risk Assessment

Authors

  • Bharat Reddy Maddireddy Voya Financials, sr.IT security Specialist, Email: Rbharath.mr@gmail.com Author
  • Bhargava Reddy Maddireddy Voya Financials, sr, network security Engineer, Email: bhargavr.cisco@gmail.com Author

Keywords:

Proactive, Cyber, Defense, AI, Threat Detection, Risk Assessment, Early, Utilizing, Artificial Intelligence

Abstract

In the ever-evolving landscape of cybersecurity, early threat detection and risk assessment are paramount for proactive defense strategies. This paper presents a comprehensive exploration of utilizing artificial intelligence (AI) techniques for proactive cyber defense, focusing on early threat detection and risk assessment. Through a multi-faceted approach integrating machine learning (ML), deep learning (DL), and data analytics, this study aims to enhance organizations' capabilities in identifying and mitigating cyber threats before they escalate into full-blown attacks. The methodology involves the collection and analysis of diverse data sources, including network traffic logs, system activity logs, and threat intelligence feeds. ML algorithms, such as anomaly detection and classification models, are deployed to detect abnormal patterns and behaviors indicative of potential threats. DL models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are utilized for in-depth analysis of complex data structures and temporal dependencies. Additionally, data analytics techniques, including clustering and correlation analysis, provide insights into the relationships between different cybersecurity events and their potential impact on organizational security posture. The results demonstrate the effectiveness of the proposed AI-driven approach in early threat detection and risk assessment. ML algorithms achieve high accuracy in identifying anomalous activities, enabling security teams to proactively intervene and mitigate potential risks. DL models excel in capturing subtle patterns and trends in large-scale data, enhancing the organization's ability to detect sophisticated cyber threats. Furthermore, data analytics techniques reveal actionable insights into the underlying causes of security incidents, facilitating informed decisionmaking and risk prioritization. In conclusion, proactive cyber defense, empowered by AI technologies, offers a proactive and adaptive approach to cybersecurity. By leveraging advanced AI techniques for early threat detection and risk assessment, organizations can stay ahead of cyber adversaries and effectively protect their digital assets and infrastructure. This paper underscores the importance of integrating AI into cybersecurity practices and highlights the potential for AI-driven proactive defense strategies to mitigate cyber risks in today's dynamic threat landscape.

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Published

2020-12-12

How to Cite

Proactive Cyber Defense: Utilizing AI for Early Threat Detection and Risk Assessment. (2020). International Journal of Advanced Engineering Technologies and Innovations, 1(2), 64-83. https://ijaeti.com/index.php/Journal/article/view/321

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