Cisco IOS Security and Splunk User Behavior Analytics compete in the network security and analytics category. Splunk may have the upper hand with its rapid data analysis capabilities and user-friendly dashboards.
Features: Cisco IOS Security is robust with features like AAA, VPN, and firewall options, providing scalability. It includes IPS, IPsec, and content filtering, essential for comprehensive protection. Splunk User Behavior Analytics offers rapid log analysis and powerful threat detection. Its data indexing and modular design are valuable, with intuitive dashboards providing quick insights.
Room for Improvement: Cisco IOS Security needs improved ACL management and IPS capabilities. Users look for better automation and a simplified CLI. Splunk's pricing and setup complexity are criticized. Users request improved integration, flexibility, and clearer licensing models.
Ease of Deployment and Customer Service: Cisco IOS Security is mainly on-premises, with users valuing strong technical support despite some concerns about complexity. Splunk’s on-premises and cloud deployments face challenges with pricing transparency, yet customer service is satisfactory.
Pricing and ROI: Cisco IOS Security is priced for medium to large enterprises, with high licensing costs but a positive ROI due to its security features and scalability. Splunk is seen as expensive, with frequent licensing changes complicating budgeting. However, it reduces operational costs and enhances threat detection efficiency, making the investment worthwhile for many.
The solution can save costs by improving incident resolution times and reducing security incident costs.
The support quality is excellent for paid tiers, following enterprise-grade SLAs with proactive support and deep expertise.
Mission-critical offering a dedicated team, proactive monitoring, and fast resolution.
Splunk's technical support is amazing.
Splunk User Behavior Analytics is highly scalable, designed for enterprise scalability, allowing expansion of data ingestion, indexing, and search capabilities as log volumes grow.
I find Cisco IOS Security to be a very stable product.
With built-in redundancy across zones and regions, 99.9% uptime is achievable.
Splunk User Behavior Analytics is a one hundred percent stable solution.
Splunk User Behavior Analytics is highly stable and reliable, even in large-scale enterprise environments with high log injection rates.
Global reach allows deployment of apps and services closer to users worldwide, but data sovereignty concerns exist and region selection must align with compliance requirements.
I encountered several issues while trying to create solutions for this advanced version, which seem unrelated to query or data issues.
High data ingestion costs can be an issue, especially for large enterprises, as Splunk charges based on the amount of data processed.
Reserved instances with one or three-year commitments offer lower rates, providing up to 70% savings.
Comparing with the competitors, it's a bit expensive.
The pricing is based on the amount of data processed, and it is considered a high-level investment for enterprises.
This solution, called Network Access Controller, handles authentication, authorization, and accounting for devices accessing the network.
I also utilize it for anomaly detection and behavior analysis, particularly using Splunk's machine learning environment.
Splunk User Behavior Analytics is known for its advanced analytics and data correlation capabilities, which help in detecting patterns, anomalies, and security threats.
The best features in Splunk User Behavior Analytics include anomaly detection, behavioral profiling, and risk scoring and prioritization functionality.
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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