Network detection and response (NDR) refers to a category of
network security products that detect abnormal system
behaviors by continuously analyzing
network traffic. NDR solutions apply
behavioral analytics to inspect raw
network packets and
metadata
Metadata (or metainformation) is "data that provides information about other data", but not the content of the data itself, such as the text of a message or the image itself. There are many distinct types of metadata, including:
* Descriptive ...
for both internal (east-west) and external (north-south) network communications.
Description
NDR is delivered through a combination of
hardware and
software
Software consists of computer programs that instruct the Execution (computing), execution of a computer. Software also includes design documents and specifications.
The history of software is closely tied to the development of digital comput ...
sensors, along with a software or
SaaS management console. Organizations use NDR to detect and contain malicious post-breach activity such as
ransomware
Ransomware is a type of malware that Encryption, encrypts the victim's personal data until a ransom is paid. Difficult-to-trace Digital currency, digital currencies such as paysafecard or Bitcoin and other cryptocurrency, cryptocurrencies are com ...
or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on
signature-based threat detection. This allows NDR to spot weak signals and unknown threats from network traffic, like
lateral movement or
data exfiltration.
NDR provides visibility into network activities to identify anomalies using
machine learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task ( ...
algorithms.
The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.
Deployment options include physical or virtual sensors. Sensors are typically out-of-band, positioned to monitor network flows without impacting performance. Cloud-based NDR options integrate with IaaS providers to gain visibility across hybrid environments. Ongoing tuning helps reduce false positives. NDR competes against broader platforms like
SIEM and
XDR for security budgets.
NDR can be used to complement EDR's blind spot.
Key capabilities offered by NDR solutions include real-time threat detection through continuous monitoring, rapid incident response workflows to minimize damage, reduced complexity versus managing multiple point solutions, improved visibility for compliance and risk management, automated detection and response, endpoint and user behavior analytics, and integration with
SIEM for centralized monitoring.
History
The origins of NDR trace back to
network traffic analysis (NTA) solutions that emerged around 2019. NTA provided greater visibility into network activities to quickly identify and respond to potential threats.
By 2020, NTA adoption was growing for real-time threat detection. That year, a study found that 87% of organizations used NTA, with 43% considering it a "first line of defense". The NTA market was valued at US$2.9 billion in 2022, and expected to reach US$8.5 billion by 2032. NTA evolved into NDR as a distinct product category. NDR combined detection capabilities with incident response workflows. This enabled detecting and reacting to threats across networks in real time.
Major attacks like
WannaCry in 2017 and the
SolarWinds breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.
Artificial Intelligence applications
The use of
artificial intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of re ...
in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include:
* Improved threat detection: AI can analyze large volumes of data on vulnerabilities, threats, and attack tactics to identify anomalous network activities. This allows NDR to detect emerging attack patterns with greater accuracy and fewer
false positives.
* Alert prioritization: AI models can evaluate the criticality of NDR alerts based on factors like affected assets, exploitability, and potential impact. This enables security teams to triage alerts effectively despite staff shortages.
* Analyst workflow optimization: AI assistants can guide analysts during incident response, suggesting relevant investigation steps based on details of the threat. This amplifies analyst efficiency, especially for junior staff lacking specialized expertise.
* Automated response: Although not yet widely adopted, AI could enable NDR platforms to autonomously execute containment measures like quarantining endpoints. AI would identify and recommend response actions for analyst approval.
* Security team communications: NDR vendors are exploring integrations with natural language AI to generate incident reports and metrics digestible for business leaders, not just technical security staff.
NDR Vendors
According to
Gartner
Gartner, Inc. is an American research and advisory firm focusing on business and technology topics. Gartner provides its products and services through research reports, conferences, and consulting. Its clients include large corporations, gover ...
, NDR vendors include
Cisco
Cisco Systems, Inc. (using the trademark Cisco) is an American multinational digital communications technology conglomerate corporation headquartered in San Jose, California. Cisco develops, manufactures, and sells networking hardware, s ...
, Corelight,
DarktraceLinkShadow ExtraHop,
Fortinet, IronNet, MixMode, Plixer,
Trend Micro, Trellix,
Vectra AI.
References
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See also
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Behavioral analytics
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Endpoint detection and response
Endpoint detection and response (EDR), also known as endpoint threat detection and response (ETDR), is a cybersecurity technology that continually monitors an "endpoint" (e.g. a client device such as a mobile phone, laptop, Internet of things devi ...
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Extended detection and response
Security technology