Course Syllabus

Please note that the specifics of this Course Syllabus are subject to change. Instructors will notify students of any changes and students will be responsible for abiding them. Even if you print this syllabus, please check the online version often.


This three-credit studio course teaches fundamental data-driven cybersecurity analytics skills using programming skills introduced in other courses (e.g., IST 140). The course will be divided into five modules. The first module introduces data-driven cybersecurity analytics, as well recapping on some of the related security issues covered in previous courses.  The second module gets students prepared for cybersecurity analytics, by gaining familiarity with some data analytics software tools  and platforms such as Python, SIEM, SOAR, etc. The third module focuses on understanding and using some popular machine learning algorithms for cybersecurity analytics.  The fourth module teaches how to apply data analytics processes and machine learning methods to selected cybersecurity problems such as anomaly detection, network traffic analysis, protecting the consumer web and internet-facing APIs, and deploying machine learning systems in production environments. The team project is the fifth module.  In this course, the students will improve their knowledge in cybersecurity analytics tools, methodologies, and processes; and how to apply them to real-world cybersecurity problems.


  • STAT 200, IST 261, CYB 262, SRA 365 concurrent

Entrance into the course follows completion of the required core curriculum.


The purpose of this course is provide students fundamental knowledge and skills of using data analytics and machine learning methods to become more efficient in exploring, visualizing and recognizing the patterns that represent network threats as well as addressing them. Upon completion of this course, students will be able to:

  • Understand and justify the needs for applying data analytics and/or machine learning methods for solving cybersecurity problems.
  • Understand and apply analytical software tools such as Python and TensorFlow  to solve Cybersecurity problems.
  • Apply data exploration and visualization methods to identify potential problems in security data (such as missing, outlier and skewness of data)
  • Prepare data and improve data quality for cybersecurity analytics.
  • Select, apply and evaluate appropriate machine learning methods to model and solve real world cybersecurity problems such as anomaly detection, network traffic analysis, etc.



Graduate Teaching Assistants





  • Chio, C. and Freeman, D. Machine Learning and Security: Protecting Systems with Data and Algorithms, O’Reilly,  1st Edition, 2018. (CF). ISBN-13: 978-1491979907

  • Accessing the Course textbook eBook.

The course textbook is available  as an eBook via Canvas under “Library Resources’. Click on this link then click ‘Starting Library Research’. Now scroll down and click the ‘LionSearch’ link. Now enter the book title ‘Machine Learning and Security: Protecting Systems with Data and Algorithms’ in the search textbox then click the search icon. You can now access the eBook by clicking on the ‘Full Text Online’ link.

Course Resources:

Additional resources will be provided in Canvas. 

Technical requirements

The technical requirements for remote learning can be found here:

Webcam Guidance

During any regular remote instruction, Penn State observes a camera optional approach.  This course may require you to have a webcam for some assessments. Classes and assessments may be conducted using Zoom or other technology selected by your instructor which may use your computer’s webcam or other technologies to communicate, monitor, and/or record classes, class activities, and assessments. Assessments may also be conducted using proctoring software, which may listen to you, monitor your computer screen, view you and your surroundings, and record (including visual and audio recordings)  all activity during the proctoring process. Please contact your instructor if you are unable to comply or have any questions or concerns. The webcam guidance can be found at

Video and audio recordings of class lectures will be part of the classroom activity. The video and audio recording is used for educational use/purposes and only may be made available to all students presently enrolled in the class. For purposes where the recordings will be used in future class session/lectures, any type of identifying information will be adequately removed.





Email Policy

All email communication for this course should use CANVAS Course Mail unless CANVAS is down for an extended period. The instructor will make every attempt to respond to CANVAS Course Mail messages within 24 to 48 hours of receipt.

Assignments & Grading

Course Grading Breakdown
Grading Category Percentage of Final Grade
Labs 30%
Team Project 20%
Exams 15%
Homework Assignments 15%
Group Assignments 5%
Quizzes 15%
TOTAL 100%

The following are minimum cutoffs for each grade:

  • 93.00% = A
  • 90.00% = A-
  • 87.00% = B+
  • 83.00% = B
  • 80.00% = B-
  • 77.00% = C+
  • 70.00% = C
  • 60.00% = D
  • less than 60.00% = F

Course Policies and Expectations

  • Class Attendance

Regular attendance is critical for building on the skills and knowledge developed throughout the class.  Students are expected to attend class and participate in all activities. Students who participate have a more complete understanding of the material presented and are more likely to succeed in the class.  This is true whether your attendance is in person or remote.  Please review the Penn State policy on attendance.

Attending classes is of high importance for building on the skills and knowledge developed through the subject matter covered in this course, and you are therefore urged to attend every class. Class meetings will be devoted to lectures, hands-on labs, group project work, or any other remedial items decided by the instructor. Students are expected to notify the instructional team prior to missing class in order to gain the opportunity to earn possible full points for make-up work.

  • Assignment Submission Policy

Homework assignments and quizzes are due on Sunday at 11:59 p.m. unless otherwise specified (see below). Submit all homework assignments via CANVAS.

Please ensure your homework assignment looks professional, is written professionally, and communicates your ideas clearly. Your writing should be accurate in diction, spelling, punctuation, grammar, and sentence structure. Points will be deducted for not pay attention to assignment instructions.

Please note the following:

  • Assessments (labs, quizzes, and homework assignments) are due on Sunday at 11:59PM (EST) in most cases but that may be subject to change in some cases.
  • The projects deliverables due dates will be provided in class and on Canvas.
  • The final exam will take place towards the end of the semester and the exact date and time will be made available towards the end of the semester.
  • Students may submit late homework with the penalty of 25% deduction for every 12 hours late (up to 2 days) but this is highly discouraged
  • After 2 days, no more late submission is allowed

We anticipate that there may be unforeseen circumstances or medical emergencies that make it difficult to turn in homework assignments on time. Email me in advance if possible about such situations. I will grant you an extension of at most 48 hours for you to submit the homework assignment without penalty. I may request supporting documentation depending on the type of unforeseen circumstance or medical emergency. I urge you not to use such an extension except when there is an emergency.

  • Class cancellations

Class will only be cancelled due to instructor emergencies or campus closures.

  • COVID-19 Accommodations

    • I do acknowledge that you may have legitimate, unavoidable reasons due to illness at this time of the pandemic that prevents you from submitting assignments on time. I will grant you a time extension to submit a homework assignment without penalty. The time extension will depend on your individual circumstances.
    • I will be flexible in accommodating student absences during this pandemic period for those students who become sick or are required to quarantine.
    • You should make every effort to attend class either face-to-face per the schedule provided unless your sick, or remote synchronously.
    • Additionally, students who are feeling ill must stay home and call their health care provider in order to protect the well-being of others. 

Academic Integrity

Penn State and the College of Information Sciences and Technology are committed to maintaining Penn State's policy on Academic Integrity in this and all other courses. We take academic integrity matters seriously and expect you to become a partner to the University/College standards of academic excellence.

For more information, please review these policies and procedures:

You must complete the Academic Integrity (AI) Quiz during the first week of the semester acknowledging various issues related to AI and agreeing to uphold the University/College standards for excellence in education by ensuring that your work is your own and that it is consistent with these policies.


Find extensive information and links to many Penn State and IST resources (including the Penn State libraries, video conferencing tools, technology and software, writing and research, and much more) on the Resources page.


Acting with professional courtesy and sensitivity is always important and especially critical when addressing topics and experiences that may differ including but not limited to race, culture, religion, politics, sexual orientation, gender, gender variance, and nationalities. This class strives to make a safe space for all learners. There is no place for hate and intolerance at Penn State.

Educational Equity/Report Bias Statements

Penn State takes great pride to foster a diverse and inclusive environment for students, faculty, and staff. Acts of intolerance, discrimination, or harassment due to age, ancestry, color, disability, gender, gender identity, national origin, race, religious belief, sexual orientation, or veteran status are not tolerated and can be reported through Educational Equity via the Report Bias webpage (

Counseling and Psychological Services Statement

Many students at Penn State face personal challenges or have psychological needs that may interfere with their academic progress, social development, or emotional wellbeing. The university offers a variety of confidential services to help you through difficult times, including individual and group counseling, crisis intervention, consultations, online chats, and mental health screenings. These services are provided by staff who welcome all students and embrace a philosophy respectful of clients’ cultural and religious backgrounds, and sensitive to differences in race, ability, gender identity and sexual orientation.

Counseling and Psychological Services at University Park  (CAPS)
( 814-863-0395

Counseling and Psychological Services at Commonwealth Campuses

Penn State Crisis Line (24 hours/7 days/week): 877-229-6400
Crisis Text Line (24 hours/7 days/week): Text LIONS to 741741

University Policies

Review current information regarding Penn State policies (including academic integrity, copyrights, counseling and psychological services, disability accommodations, discrimination and harassment, emergencies, military accommodations, trade names, etc.) on the University Policies page.

Course Summary:

Date Details Due