Splunk User Behavior Analytics and Trellix Intrusion Prevention System are part of the cybersecurity sector. Splunk has the upper hand with its cost-effectiveness and advanced integration, while Trellix offers robust threat prevention despite its higher costs.
Features: Splunk features advanced machine learning for user behavior analysis, seamless integration with existing security structures, and enhanced threat detection capabilities. Trellix focuses on real-time threat prevention with extensive threat intelligence and network defense layers.
Room for Improvement: Splunk could enhance its threat prevention measures, reduce complexity in analytics, and improve its real-time monitoring capabilities. Trellix might work on better cost management, improve integration with external tools, and enhance user interface friendliness.
Ease of Deployment and Customer Service: Splunk supports efficient deployment, integrating smoothly with other security tools, and offers strong user support. Trellix provides a straightforward installation with dedicated customer service, focusing on direct support, though its integration flexibility could be improved.
Pricing and ROI: Splunk's initial cost is justified by its operational security analytics return, offering a favorable cost-benefit ratio. Trellix's higher initial spend is balanced by its security measures, promising considerable long-term ROI despite initial expenses.
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.
Block More Intrusions
Stop new and unknown attacks with signature-based and signature-less intrusion prevention systems. Signature-less intrusion detection finds malicious network traffic and stops attacks where no signatures exist.
Unify Virtual and Physical Security
Support network virtualization across private and public cloud platforms to scale security and evolve with changing IT dynamics.
Maximize Security and Performance
Scale hardware performance to speeds up to 100 Gbps and leverage data from multiple products.
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