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Cybersecurity skills
In demand
AI/ML Security Implementation: Cybersecurity professionals will need to secure AI/ML models against adversarial attacks, such as data poisoning and model evasion. Expertise in securing AI frameworks like TensorFlow, PyTorch, and building robust AI pipelines will be essential.
Security Automation and Scripting: Mastery of scripting languages like Python and Bash, as well as tools like Ansible, will be crucial for automating security tasks. Familiarity with SOAR platforms (e.g., Torq, Splunk Phantom) will help streamline threat detection and incident response workflows.
Threat Intelligence and Analysis with AI Tools: Proficiency in using AI-driven tools like Darktrace, Crowdstrike Falcon, and QRadar will be in high demand to analyze and respond to AI-identified threats. Cybersecurity experts will need strong skills in interpreting AI-generated insights and implementing AI-enhanced defense strategies.
Cybersecurity skills
Out of demand
Manual Log Analysis and Threat Detection: As AI-driven tools take over log analysis and anomaly detection, manual threat hunting will become less relevant. Cybersecurity professionals will rely more on AI-powered solutions to handle vast amounts of data efficiently.
Network-Centric Security Models: As AI-driven systems and cloud environments expand, traditional network-centric security approaches, like monitoring internal traffic and securing physical networks, will become less relevant. The focus will shift toward AI-enhanced endpoint security and data protection at the application level, reducing reliance on network boundaries.
Signature-Based Antivirus Tools:
Signature-based detection tools, which rely on known malware patterns, will be replaced by AI-driven behavior analysis and heuristic detection. AI can detect novel and evolving threats, making traditional antivirus solutions less effective.
Use AI to find out how your skills match up the the changing demands of the AI-driven market: