Pitt offers a range of cyber-related courses across disciplines throughout the University.
Here are a few highlighted courses in Spring 2021 from Pitt Cyber Affiliate Scholars:
+ Cybersecurity, Privacy, and Democracy (LAW 5671)
Instructor: Christopher Deluzio (Policy Director, Pitt Cyber)
This course will explore the intersection of cybersecurity issues and democracy. The proliferation of technology in the cyber age has not only collided with existing norms and laws around privacy, but also stressed American democracy in profound ways. The proliferation of algorithmic tools within government and cyber threats to our critical election infrastructure (including digital disinformation and hacking) are among the most pressing challenges that our democracy must confront to preserve popular legitimacy in the face of cyber's growth. By first exploring the legal framework around cybersecurity and privacy, students will have a sufficient grounding to examine these complex issues facing American democracy.
+ IS Security (BMIS 2681)
Instructor: Zia Hydari
The goal of this course is to introduce students to the nomenclature, concepts, and applied techniques of Information Systems (IS) security. The course will introduce students to the body of knowledge needed to earn the Certified Information Systems Security Professional (CISSP) credential. The course will give students insight into the psychology of hackers and hacking, and cover the basics of applied cryptography along with the different types of host and network attacks, how they are done, what firms can do when attacks occur, and how consumers and firms can prevent future attacks. We will look at access control and site security, review networking concepts as they pertain to security issues, look in depth at attack methods, examine the elements of applied cryptography, functionality of firewalls, host security, and discuss methods of handling incident and disaster response. Finally, the course will examine how best to manage and govern the IS security function in an organization.
+ Information Systems Ethics (BUSBIS 1645)
Instructor: Anthony Rodi
This course provides an overview of ethics concepts and decision-making as they are related to Information Systems and Computing. Emphasis is placed on the study of ethical situations and responsibilities of IS professionals around current and emerging technologies in a global setting. Research papers, Case studies and discussion of current ethical events around technology will be used to facilitate discussions in areas including, but not limited to: Cloud Computing, Data protection, Cyber Security, The Digital Divide, Social Media, Intellectual Property, Whistleblowing, Professional Codes of Conduct, Professional liability, Internet freedom in computing and international laws and governance. Invited Subject Matter Experts will conduct informative sessions on key subject matter areas aligned with the course content.
+ Hacking for Defense (ENGR 2811)
Instructor: William Clark or Dan Cole
This course will teach students how to build products and services using lean methods. This will be done by solving real-world military and intelligence community problems. The course uses the lean launchpad platform for entrepreneurship. This is a highly customer-centered hypothesis-test approach to developing a mission modes, and is particularly well-suited for technology startups. It incorporates customer needs and user testing to build a minimum viable prototype. At the conclusion of the course, students will be able to understand the problems/needs of searching for product-market fit; understand all the stakeholders, deployment issues, costs, resources, and ultimate mission value; deliver minimum viable products that match customer needs in an extremely short time; produce a repeatable model that can be used to launch other potential technology solutions.
+ Ethics and Policy in Cyber Space (PIA 2156)
Instructor: Lisa Nelson
Information technology and the information that it generates has increasingly become part of our daily lives shaping our practices, discourses, and institutions in fundamental ways. Personal information is used by consumers, professionals, and organizations to a variety of ends and in a number of different settings. The growing reliance on personal information not only challenges long-standing demarcations between public and private institution in terms of responsibilities, obligations, and limits, but also calls for a reconsideration of how to ensure the protection of long standing civil liberties and civil rights. This course will consider the impact of emerging technologies within existing constitutional, statutory, and international guidelines and will then explore a range of policy solutions for managing the use of personal information in our public and private sectors.
+ Advanced Security and Privacy (INFSCI 1620)
Instructor: Balaji Palanisamy
Network security and cryptographic protocols. Network vulnerabilities, attacks on TCP/IP, network monitoring, security at the link, network and transport layers. Cryptography, e.g., Secret and public key schemes, message authentication codes and key management. WLAN security, IPsec, SSL, and VPNs. E-mail security (PGP, s/mime); Kerberos; x.509 Certificates; AAA and mobile IP; SNMP security; firewalls; filters and gateways. Policies and implementation of firewall policies; stateful firewalls; firewall appliances. Network related physical security, risk management, and disaster recovery/contingency planning issues and housekeeping procedures.
+ Introduction to Information Security (INFSCI 2149)
Instructor: Martin B. Weiss
Introductory information security and privacy course for non-SCI students enrolled in the Graduate Certificate Program in Cybersecurity, Policy and Law. Covers fundamental issues and first principles of security and information assurance, including security policies, models and mechanisms related to confidentiality, integrity, authentication, identification, and availability issues related to information and information systems. The course will introduce students to risk management, security assurance, secure design principles, organizational security policy, legal and ethical issues in security, and standards and methodologies for security evaluation and certification.
+ Cryptography (INFSCI 2170)
Instructor: Prashant Krishnamurthy
Principles of number theory, cryptographic algorithms and cryptanalysis. Steganography, block and stream ciphers, secret key encryption (DES, res, re-n), primes, random numbers, factoring, and discrete logarithms. Public key encryption (RSA, Diffie-Helman, elliptical curve cryptography, n'tru); key management, hash functions (md5, sha-1, ripemd-160, HMAC), digital signatures, certificates and authentication protocols. Cryptanalytic methods (known, chosen plaintext etc.) For secret and public key schemes (linear and differential cryptanalysis, pollard's rho method, number field sieve, etc.).
+ Fairness in Machine Learning (INFSCI 2935)
Instructor: Dr. Yu-Ru Lin
Data-driven models have been increasingly used in many domains to assist in human decision-making that has a significant impact on people’s lives – from job hiring and promotion, college admission, judicial decision, to business or public service delivery. The development of decision aids has been made possible both by voluminous data and new data science tools that can exploit complex structures and patterns in data. This course focuses on both concepts and practice in order to understand and cope with the ethical challenges in data science and data-driven decision making. We will introduce (a) the core concepts of fairness and interpretability mechanism and (b) analytic and technical tools to mitigate emerging problems in the real world. The objective of this course is to prepare future data scientists with the competence to recognize where and understand why (un)fairness and ethical issues arise when applying data science to real-world problems, learn how to conceptualize, measure, and mitigate bias in data-driven decision-making, learn how to evaluate models and make data-driven decision-making more interpretable and explainable, and learn to think critically about data-driven decisions and policy questions and evaluate a project with these concerns in mind.
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