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As AI adoption grows, the cybersecurity challenges associated with it have evolved as well. To ensure that AI can be used securely, it is important for companies to incorporate security into their AI projects and workflows from the beginning. This is known as secure by design. As security becomes a core component of the AI design process, it is less likely that it will be weaponized by cybercriminals.

Cyberattacks leverage a variety of tools to target organizations, including social engineering attacks that utilize the targeted behavior of employees. These cyberattacks rely on the customization capabilities of AI to help attackers research, concept, and execute their attack plan. Using data scraping, AI can help attackers gather and analyze information to create personalized and highly relevant attacks that are more effective at achieving their goals.

Endpoint Protection

The use of AI in endpoint detection and response (EDR) is transforming how the industry approaches cybersecurity, enabling organizations to detect threats faster, more accurately, and with greater depth. By leveraging advanced analytics, AI-enabled solutions can analyze massive datasets and heavy network traffic, identifying anomalies and alerting teams of potential risks. This allows cybersecurity professionals to focus on high-risk threats and reduce alert fatigue by automating routine tasks.

To improve the effectiveness of their AI-powered solutions, cybersecurity teams should look for generative AI technologies that can automatically respond to new or existing security incidents. This will enable them to quickly detect, categorize, and remediate the threat without requiring human intervention. Additionally, cybersecurity leaders must ensure that they can trace the provenance, lineage, and evolution of their AI models.