xIoTz | Managed Cyber Assurance Platform

xiotz NBAD

Network Behavior
Anomaly Detection |

Elevate network security with xIoTz NBAD: AI-driven anomaly detection, threat mitigation, and performance optimization.

AI-Driven Threat Detection

Real-time identification and mitigation of network anomalies using xIoTz-AI engine.

Comprehensive Protocol Monitoring

Monitors diverse network protocols for secure communication and threat prevention.

Early Detection and Response

Proactively detects abnormal behavior, reduces false positives, and enables swift incident response.

network behavior anomaly


xIoTz NBAD Features

Shield your network from hidden threats, leaks, and performance woes with xIoTz NBAD’s watchful intelligence.

malware detection

Malware Detection

Flags suspicious traffic and abnormal data for potential malware.

insider threat detection

Insider Threat Detection

Identifies unusual activities and unauthorized logins for insider threat detection.

Data Exfiltration Detection

Data Exfiltration Detection

Detects patterns of data leaving the network to suspicious destinations.

Network Performance Optimization

Network Performance Optimization

Pinpoints issues for better resource allocation and network performance.

Investigations Forensics

Investigations & Forensics

Offers insights into security breach sources and data breach extents for investigations.

sneak and peek



xIoTz NBAD Benefits

AI-powered xIoTz NBAD guards your network and stops threats before they even knock.

Early Threat Detection

Real-time detection for swift response to potential attacks.

Improved Incident Response

Enhanced insights to mitigate risks and minimize attack impact.

Reduced False Positives

Minimizes false positives with machine learning and statistical analysis.

Cost-Effective & Scalable

Scalable solution, reducing hardware expenses for large networks.

Proactive Security Posture

Continuously monitors network behavior for proactive defense against evolving threats.

Anomaly Identification

Excels in spotting anomalies for prompt response to potential security incidents.

Insight into Normal Network Behavior

Establishes a baseline to distinguish regular activities from suspicious actions, minimizing false positives.

Protection Against Insider Threats

Effectively identifies unusual activities, securing networks against internal and external risks.



discussion animate 1

The three basic approaches to anomaly detection are statistical-based, machine learning-based, and knowledge-based methods. These approaches analyze deviations from expected behavior to identify anomalies.

Network Behavior Analysis Intrusion Prevention System (NBA IPS) is designed to prevent and respond to security threats by monitoring and analyzing network behavior. It helps in identifying and stopping anomalous activities that may indicate a cyber attack.

The best method of anomaly detection depends on the specific use case and the type of data being analyzed. Generally, a combination of statistical-based and machine learning-based approaches is often effective.

Challenges with network anomaly detection include dealing with false positives, adapting to evolving threats, handling large volumes of data, and ensuring that the detection methods align with the specific network environment.

Anomaly detection in network analysis involves identifying irregularities or deviations from normal patterns in network traffic. This helps in discovering potential security threats or operational issues within the network.

Anomaly detection focuses on identifying deviations from normal patterns, while behavior detection looks for specific patterns of behavior that may indicate a security threat.

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+91 9019632210


Bengaluru, Karnataka 562125


xIoTz Private Limited


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