Course Objectives & Learning Outcomes

• Understand the concept of detection, the profiling subject, profiling techniques, misuse detection, and anomaly detection.

• Understand the concept of static analysis and dynamic analysis.

• Understand the data analysis algorithms: distance function, similarity function, classification, clustering, and machine learning algorithms for security applications.

• Understand the neural network structures and algorithms.

• Understand the usage of language model to analyze security realted data.

• Understand the operation of security-related information systems from the perspective of the data-driven system: intrusion detection system, anomaly detection system, spam mail filter system, and sequence analysis system.

Grading Policy

•  Homework (50%): programming exercises and essays. You MUST see the ACADEMIC INTEGRITY section before taking this class.

• Project (10%): student needs to write an analysis program on a security-related data set to demonstrate their understanding of security issues and data analysis skill. A proposal, a report, a presentation, and GitHub codes are required.

• Midterm (20%)

• Final (20%)

The Problem Solving Through Inquiry and Data Analysis rubric can be found here. You SHOULD read it carefully before submitting your first homework. It allows you to know exactly the way in which you will be assessed, it is helpful in facilitating academic integrity.

Academic Integrity

• Plagiarism is a serious breach of academic trust. In academic work, our words, ideas and programs are the value of our work, so turning in someone else’s work as if it were your own is a form of theft. When you use someone else’s words, ideas, or programs without crediting the source or authorship of those words, ideas, and program, you are plagiarizing. So here’s the bottom line: original work only, credit to ideas, writing, words, or programs from someone other than you. Plagiarized work will automatically receive a “0” or “F” for the assignment.

• Since cheating usually arises out of desperation and everyone has an occasional problem and finishes their work late, this class accepts late homework submission, but with a 15% per day penalty. We encourage you to complete your homework rather than drop it. Any oral discussion with classmates, TA and lecturer are welcomed, but you MUST NOT share any of your code in any form.