The security operations community constantly seeks advancements in incident response.
Consolidating security telemetry data, upgrading your organization's cybersecurity posture, and integrating with various artificial intelligence and machine learning engines are essential to combatting adversarial AI and ML models.
Hackers also invest in AI and ML with predictive analytics to help develop their cyberattack tools, increase their attack automation capabilities globally, and optimize their ability to collect ransom in Bitcoin and other cryptocurrencies faster and more securely.
Hacker-enabled adversarial AI attacks take various forms.
Hackers continue to strengthen their email phishing by enabling AI to help better adjust their various attack vectors based on real-time analysis of the current campaign.
Adversarial AI extends many functionalities to hackers, including creating complex and yet effective kill chains against supply chains.
Legacy security operations without AI will not stop adversarial AI attacks.
Before adversarial AI attacks, most SecOps teams used basic behavior-based analytics, human intervention, and a combination of static and dynamic signature updates across their firewalls, IPS, and antivirus solutions.
Adversarial AI nullifies the ability of legacy cybersecurity protection capabilities to stop next-generation sophisticated attacks.
AI tools empower hackers to alter their attack campaigns faster, making their victims' ability to react even more challenging.
Hackers using AI tools can change where the attacks will occur, who is being targeted, and how the velocity of the attack should be.
These attack techniques become altered when they detect that the surface of their victims' attack has changed.
Many security vendors, including Trustifi, Cisco, Palo Alto, and Microsoft, incorporated AI into their solutions to help combat adversarial attacks.
Several security solutions, including email security from Trustifi, extended detection and response from Palo Alto, observability from Cisco/Splunk, and OpenAI within Microsoft 365, help organizations use AI to improve security response times, address the increase in suspicious activities, and reduce the potential damage from zero-day attacks.
A successful function of AI for cyber defense is leveraging a centralized collection of security telemetry information from the entire organization's hosts, endpoints, network devices, and cloud instances.
AI-powered automation tools allow SecOps engineers to focus more on strategy and creating executable automated functions instead of responding to each attack.
Here are some other positive takeaways of enabling security automation powered by AI:. The cybersecurity industry powered by AI is happening now.
Hackers continue to find innovative and profitable ways to exploit their victims using AI. Businesses wanting to meet compliance mandates, lower their cyber insurance premiums, and reduce their security operations costs need to invest in AI for cyber defense.
Moving your organization to a proactive approach toward its security model requires the adoption of AI and ML. As AI-enabled attacks become more common, your AI defensive strategy is ideally positioned to stay ahead of the hackers.
Rohan's experience in security operations automation extends well into the enablement of artificial intelligence machine learning and developing next-generation security orchestration automation and response functions.
This Cyber News was published on securityboulevard.com. Publication date: Sun, 30 Jun 2024 06:43:05 +0000