The cybersecurity world could be a constant battle to remain one step prior to the opposite aspect. Attackers unendingly develop new ways in which to interrupt into a system and acquire around its defenses, whereas the great guys should unrelentingly fix these weaknesses and build defenses against new sorts of attacks.
- Crowdsourced Labeling: Taps into the data of large groups to help you label information as benign or malicious
- Active Learning: Uses human consultants to select out and identify the most critical data
- Semi-Supervised Learning: Involves training models on small numbers of previously labeled data and allowing them to use this information to mark other data
- Transfer Learning: Uses AI models trained on copious amounts of labeled information to mark info and solve a new problem type
- GANs: Generate simulated attacks to teach AI systems to identify and respond to real attacks
- Cybersecurity is an ever-evolving field, and it’s about to undergo a massive shift with the growing prevalence of AI models and the emergence of AI attacks. Organizations should take the time now to protect their AI systems from potential future threats.