Despite revolutionizing cybersecurity, artificial inteligence is not entirely free of challenges. One set of problems arises from the fact that, on the one hand, it helps people accelerate their searches for threats by sifting through huge datasets and identifying anomalies in behavior, while, on the other hand, it enables attackers to innovate more intelligent versions of their malware and phishing threats.
Positive Effects:
Threat Detection: AI in SIEM systems, for example, can easily detect any unusual behavior using machine learning, thus flagging possible threats in real time.
Predictive Analytics: AI can forecast the probable vulnerabilities and attacks that might occur based on past events.
Automation: Reduces manual workload through automation of repetitive tasks, such as log analysis.
Negative Impact:
AI-Based Attacks: Various social engineering attacks using deepfake generators and automated phishing kits create more believable attacks.
Bias and False Positives: Ill-trained AI causes false alarms or may even fail to alert about serious threats.
This is the support that AI gives to security; however, as defenders innovate, so do attackers. Finding the right balance between these two is very important to ensure that a safer digital future is possible.
Top comments (0)