Find out in this report how the two Intrusion Detection and Prevention Software (IDPS) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Fortinet FortiGate IPS is a highly effective intrusion detection and prevention solution. It is designed to secure a user’s system from end to end and ensure that users are equipped to handle even the most sophisticated threats. Organizations across a wide variety of industries trust IPS to help them prevent unwanted intrusions from harming their networks.
Fortinet FortiGate IPS Benefits
Some of the ways that organizations can benefit by choosing to deploy Fortinet FortiGate IPS include:
Fortinet FortiGate IPS Features
Reviews from Real Users
Fortinet FortiGate IPS is a highly effective solution that stands out when compared to many of its competitors. Two major advantages are the powerful zero-day protection features and the way it manages to compete with even its fiercest competitors.
Srahavan A., the CEO of a computer software company, said, “We like signature-based anomaly detection and zero-day protection features. For zero-day protection, we use Cloud Sandboxing, so whenever the zero-day threat occurs, it automatically sends it to its Cloud Sandbox. After getting information from Cloud Sandbox, then the intrusion is defined.”
Sachin V., a network administrator said, “We've found the most valuable feature to be the very user-friendly interface... It has a good set of UTM features, a good bandwidth shaping mechanism, and other features. It has efficient algorithms and it competes well with Palo Alto and TechPoint.”
Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.
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