The network intrusion detection and prevention system (IDPS) appliance market is composed of stand-alone physical and virtual appliances that inspect defined network traffic either on-premises or in the cloud. They are often located in the network to inspect traffic that has passed through perimeter security devices, such as firewalls, secure Web gateways and secure email gateways. IDPS devices are deployed in-line and perform full-stream reassembly of network traffic. They provide detection via several methods — for example, signatures, protocol anomaly detection, behavioral monitoring or heuristics, advanced threat defense (ATD) integration, and threat intelligence (TI). When deployed in-line, IDPSs can also use various techniques to detect and block attacks that are identified with high confidence; this is one of the primary benefits of this technology. Next-generation IDPSs have evolved in response to advanced targeted threats that can evade first-generation IDPSs.
Network firewalls secure traffic bidirectionally across networks. Although these firewalls are primarily deployed as hardware appliances, clients are increasingly deploying virtual appliance firewalls, cloud-native firewalls from infrastructure as a service (IaaS) providers, and firewall as a service (FWaaS) offerings hosted directly by vendors. Capabilities of network firewalls include: Application awareness and control Intrusion detection and prevention Advanced malware detection Logging and reporting
Gartner defines the security and information event management (SIEM) market by the customer’s need to analyze event data in real time for early detection of targeted attacks and data breaches, and to collect, store, investigate and report on log data for incident response, forensics and regulatory compliance. SIEM technology aggregates event data produced by security devices, network infrastructure, systems and applications. The primary data source is log data, but SIEM technology can also process other forms of data, such as network telemetry. Event data is combined with contextual information about users, assets, threats and vulnerabilities. The data may be normalized, so that events, data and contextual information from disparate sources can be analyzed for specific purposes, such as network security event monitoring, user activity monitoring and compliance reporting. The technology provides real-time analysis of events for security monitoring, query and long-range analytics for historical analysis.
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