# Mathematical Model for Detecting Real-Time Network Traffic

**URL:** <https://scienceactivitycentreiiserpune.discourse.group/t/mathematical-model-for-detecting-real-time-network-traffic/28>\
**Category:** NSD2026\
**Created:** [February 11, 2026, 5:09pm UTC](https://scienceactivitycentreiiserpune.discourse.group/t/mathematical-model-for-detecting-real-time-network-traffic/28 "2026-02-11T17:09:20Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![Aditikalbhor](https://avatars.discourse-cdn.com/v4/letter/a/c68b51/32.png) [@Aditikalbhor](https://scienceactivitycentreiiserpune.discourse.group/u/Aditikalbhor)\
**Post date:** [February 11, 2026, 5:09pm UTC](https://scienceactivitycentreiiserpune.discourse.group/t/mathematical-model-for-detecting-real-time-network-traffic/28/1 "2026-02-11T17:09:20Z")

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Name: Aditi Nitin Kalbhor

School: Government Polytechnic Pune.

Project: Mathematical Modeling and Detection of Abnormal Network Traffic Using Statistical Methods

About your project (explanation):

What is network traffic?  
Network traffic is the flow of data packets between devices over a network.It occurs during browsing, streaming, messaging, and online services.It is generated by users, applications, and background system processes.

What is Abnormal Traffic?

1. **Bad (abnormal) traffic** is traffic that is unusually high, sudden, or unnatural compared to normal network behavior.
2. It creates **traffic spikes** that go far beyond the normal statistical range.
3. It can overload servers and network resources.
4. It causes slow response, service disruption, or downtime.

How this helps overcome the issue?  
It **detects abnormal traffic early** using mathematical rules.

- Early detection gives time to **trigger security controls** (rate limiting, firewall rules, blocking sources).

- It helps admins **identify DDoS-like spikes quickly** instead of manual monitoring.

- It reduces response time during traffic overload incidents.

- It works as a **first-stage warning system** before deeper security filtering.

- It is simple, explainable, and can run continuously on traffic data.

 ![rolling_anomaly_plot](https://canada1.discourse-cdn.com/flex029/uploads/scienceactivitycentreiiserpune/original/1X/ddfeb99c65ffde2da631fad6a14e96d2dc0b28c7.png)

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**Author:** ![saciiserpune](https://yyz1.discourse-cdn.com/flex029/user_avatar/scienceactivitycentreiiserpune.discourse.group/saciiserpune/32/16_2.png) [@saciiserpune](https://scienceactivitycentreiiserpune.discourse.group/u/saciiserpune)\
**Post date:** [February 12, 2026, 4:14am UTC](https://scienceactivitycentreiiserpune.discourse.group/t/mathematical-model-for-detecting-real-time-network-traffic/28/2 "2026-02-12T04:14:20Z")

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**Author:** ![saciiserpune](https://yyz1.discourse-cdn.com/flex029/user_avatar/scienceactivitycentreiiserpune.discourse.group/saciiserpune/32/16_2.png) [@saciiserpune](https://scienceactivitycentreiiserpune.discourse.group/u/saciiserpune)\
**Post date:** [February 15, 2026, 12:53pm UTC](https://scienceactivitycentreiiserpune.discourse.group/t/mathematical-model-for-detecting-real-time-network-traffic/28/3 "2026-02-15T12:53:48Z")

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