Cybersecurity Course Schedule summer 2019
Cybersecurity courses are restricted to students enrolled in the MICS degree program only.
All times are listed in the Pacific Time Zone (America/Los_Angeles).
This course explores the most important elements beyond technology that shape the playing field on which cybersecurity problems emerge and are managed. The course emphasizes how ethical, legal, and economic frameworks enable and constrain security technologies and policies. It introduces some of the most important macro-elements (such as national security considerations and interests of nation-states) and micro-elements (such as behavioral economic insights into how people understand and interact with security features). Specific topics include policymaking, business models, legal frameworks, national security considerations, ethical issues, standards making, and the roles of users, government, and industry.
This course focuses on both mathematical and practical foundations of cryptography. The course discusses asymmetric and symmetric cryptography, Kerchkoff’s Principle, chosen and known plaintext attacks, public key infrastructure, X.509, SSL/TLS (https), and authentication protocols. The course will include an in-depth discussion of many different cryptosystems including the RSA, Rabin, DES, AES, Elliptic Curve, and SHA family cryptosystems. This course also introduces advanced topics of applied cryptography, including a brief introduction to homomorphic encrypted computation and secure multi-party computation to protect sensitive data during arbitrary computation, cryptocurrency and its cryptographic building blocks, and quantum computing.
The course presents the challenges, principles, mechanisms and tools to make software secure. We will discuss the main causes of vulnerabilities and the means to avoid and defend against them. The focus is on secure programming practice, including specifics for various languages, but also covering system-level defenses (architectural approaches and run-time enforcement). We will also apply software analysis and vulnerability detection tools in different scenarios.
Machine learning is a rapidly growing field at the intersection of computer science and statistics concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. This course provides a broad introduction to the key ideas in machine learning, with a focus on applications and concepts relevant to cybersecurity. The emphasis will be on intuition and practical examples rather than theoretical results, though some experience with probability, statistics, and linear algebra will be important.
Introduction to networking and security as applied to networks. Exercises cover network programming in a language of the student's choice, understanding and analyzing packet traces using tools like wireshark and mitmproxy, as well as applying security principles to analyze and determine network security. After this course, the student will have a fundamental understanding of networking, TLS and security as it applies to networked systems.
This course offers valuable perspective for both the non-technical business manager and the technical cybersecurity or IT manager. It is the vital connector between the technical world of threats, vulnerabilities, and exploits, and the business world of board-level objectives, enterprise risk management, and organizational leadership. Now more than ever, managers have a need and responsibility to understand cyber risk. Just as financial risks and other operational risks have to be effectively managed within an organization, cyber risk has to be managed. It spans far beyond information technology, with broad implications in the areas of organizational behavior, financial risk modeling, legal issues, and executive leadership.
This course surveys privacy mechanisms applicable to systems engineering, with a particular focus on the inference threat arising due to advancements in artificial intelligence and machine learning. We will briefly discuss the history of privacy and compare two major examples of general legal frameworks for privacy from the United States and the European Union. We then survey three design frameworks of privacy that may be used to guide the design of privacy-aware information systems. Finally, we survey threat-specific technical privacy frameworks and discuss their applicability in different settings, including statistical privacy with randomized responses, anonymization techniques, semantic privacy models, and technical privacy mechanisms.
Cybersecurity is a primary national security and public policy concern. The government, military and private sector have various roles and responsibilities with regard to the protection of the cyber domain. In this course, students critically evaluate these roles and responsibilities, the manner in which government networks, systems, and data are secured, and the ability of national and international cybersecurity strategies and partnerships to mitigate the security risks introduced by society’s increased reliance on information.
This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic, students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization.