As attackers get more sophisticated, they become more adept at bypassing security measures and breaching the network perimeter while spying, spreading, and stealing within the network. As attackers circumvent the automatic defences of firewalls and signature-based defences, security teams have been forced to rely on time-consuming manual investigations and post-mortem analyses after network harm has occurred.SIEM (Security Information and Event Management) and NDR (Network Detection and Response) are two different types of security tools that have different strengths and weaknesses. In recent years, there has been a trend of organizations moving from SIEM to NDRWhere NDR Provides below benefits
NDR provides deeper visibility into network traffic. SIEMs are primarily focused on collecting and analyzing logs from a variety of sources, but they can't provide the same level of visibility into network traffic as an NDR. NDRs can capture and analyze all network traffic, including encrypted traffic, which can help to identify malicious activity that might otherwise go undetected.
NDR is better at detecting advanced threats. Advanced threats are often designed to evade detection by traditional security tools, such as SIEMs. NDRs, on the other hand, are specifically designed to detect these types of threats by using machine learning and other advanced techniques.
NDR is easier to deploy and manage. SIEMs can be complex and difficult to deploy and manage, especially in large organizations. NDRs, on the other hand, are typically easier to deploy and manage, which can save organizations time and money.
How NDR Improves the User Experience NDR saves time and effort while allowing security teams to respond before a network breach causes data loss. This allows for quick, real-time investigations by displaying the devices that represent the most danger to the network based on NDR analysis and automatically correlating those investigations with logs created by other devices.A new model of threat detection LinkShadow uses artificial intelligence to identify attacks in real time by analysing the underlying behaviour of attackers from the network's perspective. This network behavioural analysis detects risks without the use of signatures or reputation lists, allowing security teams to discover new, bespoke, or unknown threats, as well as assaults that do not rely on malware, such as hostile insiders or compromised users. This intelligence is applied to all phases of an assault, including command-and-control traffic, internal reconnaissance, lateral movement, and data exfiltration.
