Commonly used technical means for threat detection include:
Signature-based Detection: This method relies on a database of known threat signatures (e.g., malware hashes, attack patterns). It compares incoming traffic or files against these signatures to identify matches.
Anomaly-based Detection: This approach establishes a baseline of normal behavior (e.g., network traffic patterns, user activity) and flags deviations as potential threats.
Behavioral Analysis: Monitors the actions of users, applications, or systems over time to detect suspicious activities, such as privilege escalation or unauthorized access attempts.
Heuristic Analysis: Uses rules or algorithms to identify threats based on suspicious characteristics, even if the threat is not previously known.
Network Traffic Analysis (NTA): Inspects network packets to detect malicious communications, such as command-and-control (C2) traffic or lateral movement.
Endpoint Detection and Response (EDR): Monitors endpoints (e.g., laptops, servers) for suspicious activities, such as malware execution or unauthorized changes.
Security Information and Event Management (SIEM): Aggregates logs from multiple sources (e.g., firewalls, servers) to correlate events and detect complex threats.
For cloud environments, Tencent Cloud offers services like Host Security (HSM) for endpoint protection, Cloud Workload Protection (CWP) for server security, and Cloud Security Center (SSC) for unified threat detection and response. These tools leverage the above techniques to safeguard cloud infrastructure.