Security services are the first line of defense for keeping your business safe from attacks. They do this by proactively monitoring the premises, checking IDs at entrance gates and checkpoints, and watching CCTV.
However, they can be prone to high false positives and negatives. To reduce this, they must leverage advanced threat detection technologies.
Unlike signature-based detection methods, behavioral analysis focuses on identifying changes in behavior patterns. This can be done by continuously monitoring internal users, network traffic, and endpoint activity to identify anomalies and detect unknown threats that may have already entered the enterprise.
By establishing a baseline of user normal behavior, the solution can identify deviations from this norm that could indicate malware or other malicious activities. This can include the types of data accessed by each user, the types of security services in network security, the times of day they typically access this information, and where they work from daily.
This can be combined with threat correlation analytics to provide security teams comprehensive visibility into potential attacks and their broader context, reducing the time between threat identification and mitigation. It can also automatically take actions such as changing firewall rules, isolating affected systems, or deploying antimalware on an infected endpoint.
Identifying threats requires more than just blocking known malware and attack signatures. The more proactive threat detection and response (TDIR) aims to continuously monitor networks, systems, and digital assets to spot anomalous activity in near real-time. This enables organizations to spot known and unknown threats that bypass traditional prevention measures.
A centralized monitoring system is the foundation for threat detection and response. Security services like SIEM, network traffic analysis (NTA), and endpoint detection and response (EDR) are highly effective at collecting data from across the enterprise and providing threat analytics and alerts. However, they are limited in their ability to detect evasive threats that move between silos.
IT teams can get many alerts, making it challenging to prioritize and solve issues quickly. That’s why many security solutions include a topographic map that shows dependencies so IT staff can quickly pinpoint the source of performance degradation.
Intrusion Detection & Prevention
Security teams need to be able to detect and respond to threats quickly. However, they must also be able to turn threat intelligence into protection. An Intrusion Detection and Prevention System (IDPS) can automate the process of transforming threat intelligence into more robust security policies to protect applications, users, data, and systems.
An IDS operates like a surveillance camera, monitoring network traffic and alerting when something looks suspicious or out of the ordinary. It can use either signature-based detection or anomaly-based detection. Signature-based detection compares activity to a library of known attack patterns and can effectively stop previously identified threats. Anomaly-based detection monitors for deviations from normal behavior and can be more effective at catching brand-new attacks that evade signature-based detection.
An IPS is more proactive than an IDS, acting to prevent detected threats from doing any harm. It can do this by terminating an attacker’s session, changing the security setup of network devices to prevent hackers from accessing them, or simply modifying the content of attacks to scrub out dangerous components.
Next-Generation Firewalls (NGFW)
Firewalls are deployed at the network perimeter and filter incoming and outgoing traffic based on security policies. Unlike traditional firewalls that use ports and protocols, NGFWs utilize deep packet inspection (DPI) to examine each packet for context and inspect higher-order TCP/IP communication layers for application, user, and content identification, encryption detection, and data leakage prevention.
In addition to the enhanced network protection provided by firewalls, NGFWs also offer unified threat management (UTM) services that protect organizations against malware and other threats. These include sandboxing that analyzes suspicious files in a secure environment, machine learning algorithms that proactively identify and stop unknown threats, and threat intelligence integration to ensure up-to-date protection. NGFWs also provide a centralized management console that simplifies security monitoring and policy configuration. This helps reduce infrastructure complexity and saves time and money. Sangfor NGFWs also integrate with our threat intelligence platform, Neural-X, to provide continuous, real-time protection against sophisticated attacks.
Advanced Malware Protection (AMP)
As cyber-attacks have become stealthier and more sophisticated, network security solutions must go beyond point-in-time detection capabilities.
AMP continuously monitors and analyzes file activity at the edge, on endpoints, and in the cloud to detect stealthy threats that may evade front-line defenses. AMP’s threat analysis includes:
- One-to-one signature matching.
- Fuzzy fingerprinting.
- Machine learning to identify potentially malicious files.
It then correlates these discrete events into coordinated, multistage attacks and identifies the threat’s behavior across devices and over time.
AMP’s advanced sandboxing capabilities help to quickly and accurately identify, contain, and remediate threats that have been able to evade prevention technologies.
Application Visibility & Control (AVC)
Modern applications often use complex protocols that do not map to traditional port numbers and can evade existing access controls by changing ports and hiding their identity. To address these challenges, application-aware security services classify traffic flows to provide visibility and enforce business-intent policies.
AVC uses stateful deep packet inspection (DPI) to detect a wide range of applications and utilizes techniques like statistical classification, socket caching, service discovery, auto-learning, and DNS as an authoritative source (DNS-AS). It supports more than 1000 native applications with its embedded monitoring agent that measures transaction time, latency, and packet loss/jitter for TCP applications and voice/video applications.
AVC also supports NetFlow to export application usage and performance statistics to network management tools. This data is used for analytics, billing, and security policies. This provides the context for application-aware policies that optimize bandwidth and improve application performance.
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