FICS 2024 Registrations are now open! Register Now
Idea - FICS

Media Forensics

Team and Contact Details

Student Name School Degree Year Email
Inam Ur RehmanMCSUndergraduateFourth[email protected]
Malik MatiullahMCSUndergraduateFourth[email protected]
Muhammad MusabMCSUndergraduateFourth[email protected]
Talal Arif ShahMCSUndergraduateFourth[email protected]

Inter School Idea ? No
Do you need expertises from another area: Yes
If Yes please provide details of expertises you need: Machine Learning and Cloud Computing

Idea Details

Idea Name: Media Forensics
Slogan: Uncovering the truth behind the pixels
Supervisor Name: Dr Haider Abbas
Supervisor Designation: HoD Information Security Department MCS NUST
Supervisor School: MCS
Supervisor Department: Information Security Department
Contact number: +92 300 9634911
Email ID: [email protected]
Abstract:
    Media forensics is a rapidly growing field that focuses on analysing and detecting digital media content. It involves the examination and analysis of digital images, audio, video, and other digital artifacts to uncover hidden messages, detect digital manipulation, and uncover the truth. Our forensic media project is dedicated to helping individuals detect tempered content.
What is the unmet need in society that your idea will fulfill ?
    With the proliferation of doctored photos and videos and other forms of manipulated content, it is increasingly challenging to verify the accuracy of digital media. This has severe implications for the integrity of public discourse and the ability of individuals to trust what they see online.
Who needs it ? How many would benefit ?
   • Can be used by Law Enforcing Institutes like FIA, CID etc for Cyber Patrolling. • Can be used to ensure the integrity of the digital media content of VIPs, if their content is forged or not. • Can be used in digital forensics to check whether the evidence is fabricated.
How will the solution works
    A fake multimedia detection model uses machine learning techniques to analyze visual content in multimedia files and determine whether they have been altered or manipulated. The model extracts relevant multimedia content features, such as an image's colour and texture information. The model uses the extracted features to classify the multimedia content into two categories: "real" or "fake". The model uses the output of the classification step to make a decision.
Who are your competitors ? How is your solution different
    Cado Security develops a Cloud-based Digital Forensics Platform. Binalyze provides Enterprise Forensics. Artinets enables Automatic Object Detection.
Status: new
Entry Date & Time: 2022-12-10 (2155)