CYBV475 - Cyber Deception Detection

CYBV475
Cyber Deception Detection

Bachelor's Degrees

Cyber Engineering Cyber Law & Policy Defense & Forensics

Certificates

Cybersecurity Security Computing

Course Description

CYBV 475 will provide students with an in-depth investigation into the use of cyber deception techniques in both offensive and defensive operations. The course will focus on the development of new methodologies to create, detect, analyze, and respond to online cyber deception campaigns. Students will use interactive programming exercises to detect and counter fake news; fake images; deep fake video and audio; advanced data hiding methods; covert communications; and covert tagging and tracking methods.  

Learning Outcomes

Upon completion of this course students will be able to: 

  • Identify principles and concepts relating to advanced deception methods, techniques, and objectives 
  • Develop strategies and specific methods to detect, uncover and trace perpetrators that are utilizing deception methods for crowd manipulation, propaganda dissemination or social engineering.  
  • Identify the use of covert communications, data hiding and other advanced methods of clandestine methodologies 
  • Uncover and extract unique features and behaviors that can in turn be used to train machine learning engines for the purpose of generating indications and warnings and/or critical observables 
  • Analyze and expose fake images, audio, video, and textual content 
  • Develop new methods of concealed survivable covert marking technologies that can be used to track and monitor illicit activity  
  • Develop decoys, traps and lures that can be employed to manipulate bad actors in order discover their objectives, techniques, and identities 

Course Objectives

During this course students will: 

  • Perform social media discovery and build a corpus of normal, suspicious, and actions performed by real or fake personas 
  • Utilizes these discoveries for a wide range of analysis that will uncover and differentiate real vs. fake, propaganda vs facts, and covert vs. overt communications 
  • Using Python and ML create possible models that can be used to detect active deception methods 
  • Develop and deploy traps, lures, and decoys to disrupt and identify perpetrators.