The aim of this course is to present and discuss methods, techniques, current best practices and standards commonly followed during the investigation of cases involving digital devices, including mobile phones. The course elaborates on how to handle devices and evidence at the crime scene, how to acquire artifacts from digital devices, how to preserve the integrity of the extractions, how to utilise open source and commercial forensic tools for analysis, how to verify the evidence presented by tools, how to write reports and how an investigator should properly testify in court. In this course, students will learn how to use forensic tools to extract and analyse digital evidence in order to conduct an efficient and high-quality investigation. This will include tools to circumvent security hardening, to acquire more information from challenging devices, to decode, and analyse the artifacts pertinent for any criminal investigation. Finally, this course discusses managerial as well as legal and ethical aspects applicable to digital forensics.
• Describe basic principles of digital forensics and identify the unique challenges involved in mobile forensics.
• Handle the crime scene based on the context and utilise the appropriate best practices, standards and legal provisions.
• Explain and compare various data acquisition and analysis techniques used in digital forensics.
• Explain and compare the internals of Android platforms such as OS architectures and file systems and learn how to circumvent device security hardening.
• Utilise open source and commercial forensics tools.
• Evaluate the evidential value of a digital artifacts and understand the importance of proper evidence handling.
• Document an investigation and properly present evidence to a court of justice.
• Appreciate and comply to applicable legal and ethical provisions
The courses of the Computer Science Department are designated with the letters "CS" followed by three decimal digits. The first digit denotes the year of study during which students are expected to enroll in the course.
First Digit
Advised Year of Enrollment
1,2,3,4
First, Second, Third and Fourth year
5,6
Graduate courses
7,8,9
Specialized topics
Code
Computer Science Area
A1
Computer architecture and microelectronics
A2
Computer systems, parallel and high performance computing
A3
Computer security and distributed systems
A4
Computer networks, mobile computing, and telecommunications
B1
Algorithms and systems analysis
B2
Databases, information and knowledge management
B3
Software engineering and programming languages
B4
Artificial Intelligence and machine learning
C1
Signal processing and analysis
C2
Computer vision and robotics
C3
Computer graphics and human-computer interaction
C4
Βioinformatics, medical informatics, and computational neuroscience
The following pages contain tables (one for each course category) summarizing courses offered by the undergraduate studies program of the Computer Science Department at the University of Crete. Courses with code-names beginning with "MATH" or "PHYS" are taught by the Mathematics Department and Physics Department respectively at the University of Crete.