Behavior-based security is a proactive approach to security in which all relevant activity is monitored so that deviations from normal behavior patterns can be identified and dealt with quickly. As machine learning continues to improve, this approach to security management is expected to play an important role in securing computing at the edge of the network. Traditional security software is signature-oriented: the software monitors data streams and compares data in transit to signatures in an anti-virus vendor's library of known threats. Behavior-based security programs work a little differently -- they monitor data streams too, but then they compare data stream activity to a baseline of normal behavior and look for anomalies. Behavior-based security products use applied mathematics and machine learning to flag events that are statistically significant. While there may still be instances where an organization needs to choose between signature-based and anomaly-based security software, there is a broad range of intrusion detection and prevention products that combine both approaches. Depending upon its capabilities, a behavior-based security software product may be marketed as a network behavior anomaly detection (NBAD) product, a behavior-based intrusion detection product, a behavior threat analysis (BTA) product or a user behavior analytics (UBA) product. Continue reading... |
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