Difference between revisions of "Fall 2025: Cyber Forensics"

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== Logistics ==
 
== Logistics ==
*Class Timings: '''Tuesdays and Thursdays''' 2:30 pm - 3:30 pm and  '''Fridays''' 12:30 pm - 1:30 pm
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*Class Timings: '''Wednesdays''' 1:00 pm - 3:00 pm (5<sup>th</sup> and 6<sup>th</sup> slot)and  '''Thursdays''' 10:45 am - 12:45 pm (3<sup>rd</sup> and 4<sup>th</sup> slot)
*Classroom: R2 and CL-4
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*Classroom: R33
*Lab Timings: '''Mondays''' 3:30 pm - 5:30 pm  
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*Lab Timings: '''Mondays''' 8:45 am - 12:45 pm (1<sup>st</sup> - 4<sup>th</sup>slots)
*Labs: CS Lab 4
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*Labs: CS Lab 5
  
 
== Course Overview ==
 
== Course Overview ==

Revision as of 21:16, 17 August 2025

Logistics

  • Class Timings: Wednesdays 1:00 pm - 3:00 pm (5th and 6th slot)and Thursdays 10:45 am - 12:45 pm (3rd and 4th slot)
  • Classroom: R33
  • Lab Timings: Mondays 8:45 am - 12:45 pm (1st - 4thslots)
  • Labs: CS Lab 5

Course Overview

  • As per the Delhi University Course Guidelines

Lectures

Lecture Topic Lecture Slides Readings
Unit-1 Digital Forensics: 1Intro.pdf Chapter 1 (CB1)
Unit 2 Windows OS Forensics:: 2DMT.pdf Chapter 2 (CB1)
Unit 3 Evidence Recovery:: 3AR.pdf Chapter 6 (CB1)
Unit 4 Investigation:: 4Classification.pdf Chapter 4 (CB1)
Unit 5 Cyber Crimes and Cyber Laws:: Read from Authors' web page Chapter 5 (CB1)

Assignments and Tests

Class Assignments

  • Assignment No. 1,
  • Assignment No. 2,

Tests and Quizzes

  • Test 1 :
  • Test 2 :

Resources

  • R1: Data Mining: Concepts and Techniques, 3nd edition,Jiawei Han and Micheline Kamber.
  • R2: Data Mining: A Tutorial Based Primer, Richard Roiger, Michael Geatz, Pearson Education 2003.
  • R3: Introduction to Data Mining with Case Studies, G.K. Gupta, PHI 2006.
  • R4: Insight into Data mining: Theory and Practice, Soman K. P., DiwakarShyam, Ajay V., PHI 2006