How Machine Learning Is Transforming Security As We Know It
73% of businesses have adopted security technology that incorporates AI. Machine learning is transforming security as we know it and providing more efficiency and accuracy in security processes.
Human error is an essential factor to consider when planning your security strategy, and AI can provide more accuracy for security professionals when analyzing security data. Keep reading to learn more about the AI security revolution and what it means for security professionals.
Machine Learning For Recognition
Machine learning is a helpful tool that allows security professionals to implement biometrics to secure their facilities from intruders. One of the most significant risks of a security system is the potential for an unauthorized person to steal access credentials and use them to enter the facility without triggering an alert. To prevent this from happening, security professionals must perform identity verification. However, monitoring the CCTV camera feed alongside access logs would be extremely time-consuming.
Integrating machine learning with smart building technologies, such as door intercom systems, for recognition allows security professionals to automate the identity verification process with facial recognition and voice recognition. Without AI, security professionals would have to manually verify the identity of users entering the facility, which would take up most, if not all, of their time. AI helps to automate this process and improve general security efficiency.
Machine Learning For Threat Detection
Machine learning can help security professionals detect your cloud-based security threats and any threats to physical security. Security professionals can automate data observation by integrating machine learning with security tools.
The machine learning software will analyze data to detect abnormalities and anomalous data. When the software detects anomalous data, it will alert security staff, allowing them to respond quickly and investigate the issue. The tool finds malware in encrypted traffic entering your network to spot potential security threats and notify security staff. Machine learning reduces manual effort in monitoring security data, helping detect internal and external security threats.
Machine Learning For Forecasting
Machine learning helps businesses to forecast demand based on existing data for more business intelligence. The forecasting capability of machine learning allows businesses to create accurate predictions for cyber attack rates and prepare their security strategy in line with these predictions. This information can be precious to security professionals, allowing them to create more efficient systems and save time and money.
Machine learning can also help security professionals to predict occupancy levels based on existing data. Occupancy management software collects occupancy data based on access control events. Over time, security professionals can use the machine learning feature of occupancy management software to predict occupancy level fluctuations and adjust their security strategy to account for peak occupancy levels, including implementing crowd control measures.
Machine Learning For More Efficiency
Machine learning helps you to automate workflows based on security incidents. Security professionals can implement machine learning to create workflows that adhere to their existing incident response policies and procedures if a threat is detected in the system.
These workflows are then assigned to an available security team member for efficient response. Handling workflow assignment manually is time-consuming and slows down incident response. By automating the process, you can ensure your security policies are enforced without additional manual input. With the repetitive nature of these events, machine learning helps to avoid wasted time and allows security professionals to achieve excellent ROI on their staff’s time.
Machine learning is quickly becoming an invaluable tool in any effective security strategy. Security professionals can benefit from implementing machine learning to eliminate manual security tasks. Additionally, machine learning provides more accuracy in threat detection, allowing security professionals to automate the monitoring of security data and receive notifications if a security threat occurs.