CSE548 Adv Comp Network Sec Syllabus Summer 2021 PDF

Title CSE548 Adv Comp Network Sec Syllabus Summer 2021
Course Adv Comp Network Security
Institution Arizona State University
Pages 15
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File Type PDF
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Summary

CSE548 Adv Comp Network Sec Syllabus Summer 2021...


Description

**Disclaimer** This syllabus is to be used as a guideline only. The information provided is a summary of topics to be covered in the class. Information contained in this document such as assignments, grading scales, due dates, office hours, required books and materials may be from a previous semester and are subject to change. Please refer to your instructor for the most recent version of the syllabus.

Course Syllabus and Course Map Summer 2021 (Session C) CSE 548: Advanced Computer Network Security Instructor Teaching Assistant Virtual Office Hours

Yuli Deng Zhen Zeng, Second TA pending Details provided in Live Events section below and on course’s Live Events page Content Questions Weekly discussion forums Course “Feedback” tool (blue button on every course page) Course Issues Technical Support Coursera Learner Help Center NOTE: Please make sure you are logged in with your ASU email address so that support personnel recognize you as an ASU degree student. Private Support [email protected] NOTE: When sending an email about this class, please include the prefix “CSE 548” in the subject line of your message. Slack Channel https://asu-2214-cse548-44821.slack.com NOTE: This channel is monitored for academic integrity violations. Please use the course’s weekly discussion forums to ask questions about and discuss course material and assignments.

Course Description With its focus on computer network security involving solutions in network virtualization, programmable software networks, applied cryptography, system security, as well as machine learning- and artificial intelligence-based solutions for network intrusion detection, this course explores the necessary tools, techniques, and concepts of network security for modern computer networks. It addresses both emerging technologies and research topics, primarily at the MAC layer and above, and provides not only exposure to burgeoning areas of network security but also handson experience in the virtual networking labs that are essential for advanced computer networks and cybersecurity today and will be into the future. Specific topics covered include: ● Packet filter firewalls ● Network intrusion detection/prevention ● Key management 1

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● Attack analysis using attack graphs and attack trees ● Cloud network security ● Moving target defense in computer networks

Learning Outcomes By completing this course, you will be able to: ● Explain basic security terminologies, models, architectures, and techniques. ● Apply proven methodologies to design secure networks that address enduring and emerging issues. ● Apply network security standards and cryptography algorithms. ● Document the process of designing and implementing secure networking systems. ● Build a secure networking system to counter given network attacks. ● Adhere to standards of computer security ethics. ● Manage a network security establishment effort. ● Assess networking systems to identify security vulnerabilities. ● Represent security system setup and process results in written form.  ● Discuss cutting-edge network security research and development.

Estimated Workload/Time Commitment 20 hours per week

Required Prior Knowledge and Skills Knowledge: Basic computer network concepts such as TCP/IP, packet switching, network services architecture, network protocol stack (MAC layer and above), and basic network security concepts such as encryption/decryption, authentication, access control, identity/key management Skills: Python and HTML are required, while Java, C/C++ programming are beneficial

Technology Hardware

Intel or AMD based computer with 8GB or more memory. NOTE: 6GB is technically sufficient, but performance will be sluggish. If your computer does not have at least 6GB of memory, please notify the instructor. Software

VirtualBox 5.0 or Newer (available at https://www.virtualbox.org/wiki/Downloads). Windows 10, Mac OS X, or Linux 64-bit as base operation system. Knowing how to use the Linux OS is a plus. 2

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For more information about this course’s technology requirements, see the reading titled “Course Projects: Essential Information” in Week 1’s Getting Started module.

Textbook No textbook is required for this course; however, the following textbook is recommended: Software-Defined Networking and Security: From Theory to Practice. Dijiang Huang, Ankur Chowdhary, and Sandeep Pisharody (CRC Press, 2018).

Important Course Dates Class begins: Monday, May 17, 2021 Holiday(s): Monday, May 31 (Memorial Day) and Monday, July 5 (Independence Day observed) – University closed Final exam: Opens Thursday, July 8 12:15 AM Phx; closes/must be completed by Saturday July 10, 11:45 PM Phx (last appointment will be Saturday, July 10, 9:15 PM Phx) Class ends: Saturday, July 9, 2021 Portfolio Inclusion Request for project due: Saturday, July 24, 2021 Grades due: Sunday, July 11, 2021

Course Schedule by Week and Late Work Unless otherwise noted, all graded work is due at 11:59 PM the Sunday ending the week for which it is assigned. Late work: A 25% late penalty will be added each day for graded work submitted after the scheduled due date and time unless prior accommodations have been agreed to for extraordinary circumstances. Week 1

Main Topic

Begin Date

Getting Started and Computer Network Foundations

May 17

End Date/Graded Work Due May 23

3

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2

Security Foundations

May 24

May 30

3

Virtual Networks

May 31

June 6

4

Software-Defined Networks and Network Virtualization

June 7

June 13

5

Security Measurement

June 14

June 20

6

Anomaly Detection

June 21

June 27

7

Moving Target Defense

June 28

July 4

8

Closing the Course

June 5

July 9

8

Course Exam

July 8

July 10

Grade Breakdown Course Work

Quantity

Format

%

Participation/Discussion Forums/Live Events Graded quizzes*

8

Individual

5%

7

Individual

25%

Course Projects**

4

Individual

40% 4

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Exam (final, covers Weeks 1 - 7)

1

Individual

30%

*The system will automatically drop your lowest graded quiz score. **To request approval to include this course’s projects in your final MCS Portfolio, you must include at least three (3) of the projects (but are welcome to include all four), which together will account for at least 30% of your grade, which is the threshold for a project’s eligibility for inclusion as ONE project in the final portfolio.

Grade Scale Consistent with CIDSE policy, you must earn a “C” or better to receive credit for this course. The following cutoffs will be used to generate your letter grade: A+

≥95%

A

≥90%

A-

≥87%

B+

≥84%

B

≥80%

B-

≥77%

C+

≥72%

C

≥67%

D

≥50%

E

< 50%

NOTE: For more information about grading, visit ASU’s Grades & Records webpage.

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Assessment Details and Settings The table below summarizes what you can expect to encounter in the course’s assessments. Content Type

Description

Time Limit # of Feedback Attempts Practice quizzes – Each module includes Knowledge None Unlimited Full (score, Knowledge Check Check practice quizzes, which cover correct/incorrect only each module’s topic. The system choices, may present a different selection of explanations) questions to you after your first attempt. These quizzes do not contribute toward your final score in the class. Practice quizzes – Each unit includes a Unit/Weekly None Unlimited Full (score, Unit/Weekly practice quiz, which covers the entire correct/incorrect unit. These practice quizzes choices, immediately precede the graded explanations) Unit/Weekly quizzes. The system may present a different selection of questions to you after your first attempt. These quizzes do not contribute toward your final score in the class. Graded quizzes – Units 1-7 include one graded quiz that 90 minutes 1 Partial (score and Unit/Weekly covers the entire unit and counts correct/incorrect toward your final score in the course. choices) NOTE: The lowest quiz score will be automatically dropped. Projects You will be required to complete four None n/a Full (score and individual projects throughout the evaluation of the course. These projects will be project’s completed in the virtual networks completeness platform ThoTh Lab. and outcomes) Exams You will have one (1) proctored exam, 135 minutes 1 Limited (score a final, taken in the course with total (2 only) ProctorU, a live, remote proctoring hours plus service that allows students to take 15 minutes exams online while ensuring the start-up with integrity of the exam for the institution. proctor) 6

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The exam will be available for three (3) days. Additional information is provided in the Course Map, Week 1’s “Course Exams” reading, examspecific instructions in Week 8, and the MCS Onboarding Course). ProctorU appointments must be made at least 72 hours prior to exam time to avoid a scheduling fee.

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Live Events/Virtual Office Hours This course will offer several live event/virtual office hour sessions each week, all of which will be hosted on Zoom. These sessions have an open, “drop-in” format to provide everyone an opportunity to meet with the course instructor and/or teaching assistants as well as classmates to ask questions and learn more about course topics and assignments Live events/virtual office hours may be joined using a computer or a mobile device. iOS devices, however, are not fully supported at this time. To join from an iOS device, use the Zoom app and paste in the session URL. Using other mobile operating systems or a computer, simply open the Coursera app, navigate to “Live Events,” and click the active link to join. Event Dates and Times The events are live office hours to answer student questions, attendance is not mandatory. Times shown are Arizona. Day

Sat Sun Mon Tue Wed Thu Fri

Time

Hosted By

Zoom URL

2:00PM to 3:00PM 8:30AM to 10:00AM

Instructor Zhen Zeng

https://asu.zoom.us/j/9362412635 https://asu.zoom.us/j/83560033604

7:00PM to 8:00PM

Instructor

https://asu.zoom.us/j/9362412635

Also watch for announcements and check the Live Events page in the course. Note: These events will be recorded and the instructor’s events will be uploaded to the course by the end of the day following each event. Look for the “Weekly Live Event/Office Hour Recordings” section at the end of each week. For ASU and MCS policies and procedures, refer to the MCS Graduate Handbook.

Course Map Week 1 | Unit 1: Getting Started and Computer Network Foundations Learning Objectives 1.1 Describe computer network infrastructure components and set-up, including network protocol layer models 1.2 Illustrate networking concepts such as devices’ OSI and TCP/IP protocol stack layers and packet encapsulation and decapsulation

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1.3 Differentiate between the uses, network layers, and related concepts of MAC and IP addresses 1.4 Differentiate between IPv6 and IPv4 1.5 Illustrate the use of port number 1.6 Illustrate physical, logical and overlay networks 1.7 Explain the purpose and functionality of computer networking services such as DHCP, ARP, DNS, and NAT 1.8 Illustrate the packet processing procedure of using iptables 1.9 Describe intradomain and interdomain network routing

Modules Module 1: Getting Started Module 2: Computer Network Basics and Infrastructure Module 3: Network Addresses Module 4: Computer Networking Services

Week 1 – To Do ❏ Complete “Get to Know Your Classmates” (discussion forum assignment) ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) ❏ Create your ProctorU account (if you do not already have one) WEEK 1 – Due by 5/23/21 ❏ Getting Started Quiz ❏ Unit 1 Graded Quiz

Week 2 | Unit 2: Security Foundations Learning Objectives 2.1 Explain pros and cons of specific firewall architectures, including those pertaining to deployment 2.2 Differentiate between stateful and stateless firewalls 2.3 Devise effective packet filtering firewalls such as iptables 2.4 Explain metrics intrusion detection and prevention systems such as FN, FP, TP, and TN 2.5 Differentiate among specific sniffing models, protocols, and tools 2.6 Design verifiable snort rules 2.7 Identify cryptology classifications 2.8 Explain cryptographic concepts such as symmetric cipher solutions, hash functions, DiffieHellman key agreement protocol, RSA-based cryptosystem, and key management solutions based on KDC and CA approaches 2.9 Illustrate how to use symmetric and asymmetric crypto approaches to achieve security features such as confidentiality, authentication (origin integrity and data integrity), and their combination

Modules 9

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Module 1: Firewalls Module 2: Intrusion Detection Systems Module 3: Basics of Applied Cryptography

Week 2 – To Do ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) WEEK 2 – Due by 5/30/21 ❏ Unit 2 Graded Quiz ❏ Project 1: Packet Filter Firewall (iptables)

Week 3 | Unit 3: Virtual Networks Learning Objectives 3.1 Explain relationships between physical networks, logical networks, network overlays, and network virtualization 3.2 Explain the concepts of tunneling, switch, bridge, and basic modules of linux bridge and open virtual switch (OVS) 3.3 Illustrate how spanning tree protocol (STP) works 3.4 Explain how VLAN and VxLAN work in different use scenarios 3.5 Describe basic modules of linux bridge and open virtual switch (OVS) 3.6 Describe how L2TP and GRE tunneling protocols work, including running at different network layers and design considerations Illustrate SSL/TLS protocol procedures and achieved security features based on exchanged messages 3.7 Describe IPSec protocol architecture, operations and traffic processing procedure 3.8 Illustrate IKE operation, phases and modes involved in IKE protocols, as well as the uses of security association and security policies 3.9 Explain AH and ESP protocols and their use scenarios Modules Module 1: Virtual Network Foundations Module 2: IP Security

WEEK 3 – To Do ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) WEEK 3 – Due by 6/6/21 ❏ Unit 3 Graded Quiz

Week 4 | Unit 4: Software Defined Networks and Network Function Virtualization CSE548: Advanced Computer Network Security (Summer C, 2021) 5/3/2021 – SUBJECT TO CHANGE.

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Learning Objectives 4.1 Describe the basic functions of routers and routing protocols 4.2 Explain the concept of Software Defined Network (SDN) and its architecture 4.3 Describe Openflow protocol, flow rules, and packet processing using Openflow 4.4 Illustrate how to set up a simple Open Virtual Switch (OVS) network 4.5 Explain the relationship between Network Function Virtualization (NFV) and SDN 4.6 Illustrate how the major open source platforms Openstack and Kubernetes contain SDN and NFV components 4.7 Illustrate SDN and NFV security issues and potential solutions Modules Module 1: Distributed Network Routing Module 2: Network Function Virtualization

WEEK 4 – To Do ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) WEEK 4 – Due by 6/13/21 ❏ Unit 4 Graded Quiz ❏ Project 2: SDN-Based Stateless Firewall

Week 5 | Unit 5: Security Measurement Learning Objectives 5.1 Explain what security measurement refers to 5.1 Explain how to use CVSS security metrics to measure a vulnerability 5.1 Explain the cyber Kill Chain model 5.1 Illustrate how to generate and use a graph-based measurement model 5.1 Evaluate attack scenarios based on given probability assignments of attack graphs, attack trees, and attack countermeasure trees Modules Module 1: Introduction to Models Module 2: Attack Graph and Attack Tree Module 3: Attack Countermeasure Tree

WEEK 5 – To Do ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) WEEK 5 – Due by 6/20/21 ❏ Unit 5 Graded Quiz

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Week 6 | Unit 6: Anomaly Detection Learning Objectives 6.1 Explain anomaly detection 6.2 Differentiate among the three major types of anomalies (point, contextual, and collective) 6.3 Evaluate anomaly detection scenarios 6.4 Illustrate supervised and semi-supervised classification techniques 6.5 Describe the basic concept of neural networks for machine learning 6.6 Use feedforward neural networks (FNN) as an example to illustrate the procedure for establishing an anomaly detection solution 6.7 Use FNN to build a basic anomaly detection model for a given network traffic data set Modules Module 1: Anomaly Detection Models Module 2: Feedforward Neural Networks

WEEK 6 – To Do ❏ Attend and/or watch recorded Live Event/Virtual Office Hour(s) ❏ If you haven’t already, schedule your final exam and complete the system test with ProctorU WEEK 6 – Due by 6/27/21 ❏ Unit 6 Graded Quiz ❏ Project 3: SDN-Based DoS Attacks and Mitigation

Week 7 | Unit 7: Moving Target Defense Learning Objectives 7.1 Explain the motivation for and key concepts of software-defined networking 7.2 Describe primary considerations associated with virtualizing security infrastructure 7.3 Illustrate how to use SDN for MTD 7.4 Illustrate how to use attack graph or MTD countermeasure selection 7.5 Illustrate how to use SDN-based distributed firewall to simplify attack-graph based security analysis/measurement 7.6 Describe the security service function chaining 7.7 Examine the policy checking and resolving for SDN-based security system 7.8 Evaluate methods of defeating port scanning attacks 7.9 Explain the persistence and fast resumption of TCP-based applications 7.10 Illustrate address space layout randomization to counter buffer overflow attacks

Modules CSE548: Advanced Computer Network Security (Summer C, 2021) 5/3/2021 – SUBJECT TO CHANGE.

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Module 1: Introduction to Moving Target Defense Module 2: ...


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