In the digital age, cybersecurity plays a crucial role in protecting personal and organizational data from evolving cyber threats. With increasing reliance on the internet for activities like online transactions, communication, and data storage, cyber-attacks have become more sophisticated, targeting both individuals and businesses. This paper explores the significance of cybersecurity in everyday life, focusing on various types of cyber-attacks such as phishing, malware, denial-of-service (DoS), and man-in-the-middle (MITM) attacks. Traditional security methods are no longer sufficient to combat these advanced threats, necessitating the integration of Artificial Intelligence (AI) in cybersecurity. AI-powered cybersecurity solutions leverage machine learning and deep learning algorithms to detect, prevent, and respond to cyber threats in real time. These techniques enhance threat detection by analyzing patterns, identifying anomalies, and predicting potential attacks before they occur. AI-driven tools, such as Intrusion Detection Systems (IDS), anomaly detection, and behavioral analysis, significantly improve cybersecurity measures by automating responses and reducing human intervention. This paper also highlights AI-based threat prevention strategies, including malware detection, phishing prevention, and intrusion prevention, which help secure networks, systems, and personal devices. While AI in cybersecurity presents challenges such as false positives and algorithmic transparency, its advantages in enhancing security resilience outweigh the limitations. As cyber threats continue to evolve, integrating AI-driven security solutions is essential for individuals and organizations to safeguard their digital assets and maintain data integrity in an increasingly interconnected world
Keyword: Cybersecurity, AI, cybercrime, machine learning, Threat Detection, Fraud Detection