2. New defenses in the cybersecurity landscape in the AI era
New defenses in the cybersecurity landscape are AI tools that automate mundane tasks to reduce daily human intervention and accelerate the detection of anomalies and patterns posing potential cyber threats to eliminate unknown vulnerabilities , especially when identifying zero-day vulnerabilities. Additionally, AI defenses can automate the process of patching vulnerabilities, minimizing risk for hackers. In this regard, Gartner predicts that by extending the assurance of directors and officers due to their direct involvement in the process, corporate spending on combating misinformation will exceed $500 billion, cannibalizing 50% of marketing and cybersecurity budgets by 2028.
A. Deploy AI-powered defenses: Deploying AI-based defenses can help cybersecurity professionals combat advanced vulnerabilities. Real-time threat detection is the advantage that AI can leverage to establish a robust cybersecurity system. With the help of AI-based cybersecurity solutions, defense products leverage machine learning algorithms, learn patterns from the past, and predict future attacks.
b. Outreach Program: Organizations and individuals should organize and establish robust security awareness programs to counter AI-assisted social engineering. Education and training can enable individuals to identify phishing attempts, refrain from sharing sensitive information, and adhere to online security best practices. Additionally, implementing multi-factor authentication and regularly updating security protocols can further reduce the risk of successful social engineering attacks.
c. Access management and the principle of least privilege: Through access management, processes and technologies are used to manage and control user access to systems, applications and data, ensuring that sensitive information is accessible only to authorized individuals. The principle of least privilege is a security concept that involves granting users only the permissions necessary to perform related business functions. This method also minimizes the risk of data breaches by limiting users’ ability to access sensitive information or systems.
D. Ethical development of AI: Developers must incorporate ethical considerations when developing AI systems, respecting transparency, accountability and fairness. Conducting regular assessments and audits of these systems can eliminate the risk of biases and vulnerabilities detected by malicious actors.
E. Information sharing and collaboration: Collaboration between cybersecurity experts, industry leaders and AI researchers can play a central role in thwarting rapidly evolving AI-based threats. By pooling knowledge about potential vulnerabilities, emerging attack methods and innovative countermeasures, shared knowledge can proactively strengthen defenses and create a dynamic and adaptable shield against future challenges.
