Idea - FICS

Anomaly Detection

Team and Contact Details

Student Name School Degree Year Email
Maryam ShafiqueMCSUndergraduateFourthmaryamshafique42@gmail.com
Mazhar AbbasMCSUndergraduateFourthmazhar1abbas11@gmail.com
Muhammad Arslan AslamMCSUndergraduateFourthmarslanaslam7860@gmail.com

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: Anomaly Detection
Slogan: Secure Today For Better Future
Supervisor Name: Waleed Bin Shahid
Supervisor Designation: Associate Professor
Supervisor School: Military College Of Signals, Rawalpindi
Supervisor Department: Information Security
Contact number: 923333305533
Email ID: waleedbinshahid@gmail.com
Abstract:
    NextGen Anomaly Detection Engine detects an anomaly in the network traffic with the help of machine learning and visualizes it to security analyst.
What is the unmet need in society that your idea will fulfill ?
    Current security devices lack in providing Machine Learning and better visualization. Our solution will have the ability to detect and classify network attacks using Machine Learning and their visualization through well-known visualization tools.
Who needs it ? How many would benefit ?
   Any organization which has a computer network and wants to secure its network against cyber attacks.
How will the solution works
    NADE captures live network traffic and extracts useful features using Zeek scripts. Then this traffic is passed to the trained Machine Learning Model which labels it as benign or attack(type of attack). Labeled results are sent to Elastic search for indexing. Kibana will be used as an operational security dashboard to have full visibility of security attacks for the Network Administrator
Who are your competitors ? How is your solution different
    Our competitors are security companies i.e. snort, IBM QRadar and Suricata which are providing similar solutions to secure the network.Our solution is cost-effective and detects advanced attacks with higher accuracy.
Status: new
Entry Date & Time: 2021-01-05 (1726)