Challenges in AI-Based Malware Detection

Despite its advantages, AI-driven malware detection faces several challenges that cybersecurity experts must address:

Challenges:

• Data Quality: AI requires extensive datasets for accurate detection, and poor-quality data can reduce effectiveness.
• Adversarial Attacks: Cybercriminals are developing techniques to manipulate AI models and bypass detection.
• Computational Resources: AI-powered security systems require high processing power, making them expensive to maintain.
• Privacy Concerns: AI relies on access to large amounts of user data, raising ethical and legal concerns.

To overcome these challenges, continuous advancements in AI algorithms, threat intelligence sharing, and regulatory frameworks are necessary.