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- D class assignments for on-campus graduate students are available by emailing email@example.com D class assignments for DEN@Viterbi are available to students enrolled in the Distance Education Network. For more information go to den.usc.edu
Threats to information systems; technical and procedural approaches to threat mitigation; secure system design and development; mechanisms for building secure security services; risk management. Recommended preparation: Background in computer security preferred. Recommended previous courses of study include computer science, electrical engineering, computer engineering, management information systems, and/or mathematics.
|32420D||048||Lecture||6:40-9:20pm||Thursday||11 of 25||Blaine Burnham||RTH105|
|32430D||034||Lecture||6:40-9:20pm||Thursday||4 of 25||Blaine Burnham||DEN@Viterbi|
Application of cryptography and cryptanalysis for information assurance in secure information systems. Classical and modern cryptography. Developing management solutions. Recommended preparation: Previous degree in computer science, mathematics, computer engineering, or informatics; understanding of number theory and programming background are helpful.
|32421D||048||Lecture||3:30-6:10pm||Thursday||10 of 25||Blaine Burnham||WPH205|
Policy as the basis for all successful information system protection measures. Historical foundations of policy and transition to the digital age. Detecting policy errors, omissions and flaws. Recommended preparation: Background in computer security, or a strong willingness to learn. Recommended previous courses of studies include degrees in computer science, electrical engineering, computer engineering, management information systems, and/or mathematics.
|32422D||048||Lecture||12:30-1:50pm||Tue, Thu||6 of 25||Mark Heckman||OHE120||PDF (916724 KB)|
|32432D||034||Lecture||12:30-1:50pm||Tue, Thu||1 of 25||Mark Heckman||DEN@Viterbi||PDF (916724 KB)|
Assurance as the basis for believing an information system will behave as expected. Approaches to assurance for fielding secure information systems that are fit for purpose. Recommended preparation: Prior degree in computer science, electrical engineering, computer engineering, management information systems, and/or mathematics. Some background in computer security preferred.
|32423D||048||Lecture||6:40-9:20pm||Wednesday||10 of 25||Mark Heckman||OHE120||PDF (907792 KB)|
|32433D||034||Lecture||6:40-9:20pm||Wednesday||6 of 25||Mark Heckman||DEN@Viterbi||PDF (907792 KB)|
Analysis of computer security and why systems are not secure. Concepts and techniques applicable to the design of hardware and software for Trusted Systems. Recommended preparation: Prior degree in computer science, mathematics, computer engineering, or informatics; advanced knowledge of computer architecture, operating systems, and communications networks will be valuable.
|32425D||048||Lecture||2:00-3:20pm||Tue, Thu||6 of 25||Roger Schell||RTH217||PDF (249249 KB)|
|32435D||034||Lecture||2:00-3:20pm||Tue, Thu||2 of 10||Roger Schell||DEN@Viterbi||PDF (249249 KB)|
The process of designing, developing and fielding secure information systems. Developing assurance evidence. Completion of a penetration analysis. Detecting architectural weaknesses. Case studies. Recommended preparation: Previous degree in computer science, mathematics, computer engineering, or informatics; moderate to intermediate understanding of the fundamentals of information assurance, and distributed systems and network security. Knowledge and skill in programming.
|32407D||048||Lecture||11:00-12:20pm||Tue, Thu||16 of 25||Roger Schell||OHE100C|
|32437D||034||Lecture||11:00-12:20pm||Tue, Thu||4 of 10||Roger Schell||DEN@Viterbi|
Preservation, identification, extraction and documentation of computer evidence stored on a computer. Data recovery; cryptography; types of attacks; steganography; network forensics and surveillance. Recommended preparation: Previous degree in computer science, mathematics, computer engineering, or informatics; a working understanding of number theory and some programming knowledge will be helpful.
|32408D||048||Lecture||12:30-1:50pm||Tue, Thu||20 of 30||Joseph Greenfield||RTH217||PDF (482504 KB)|
|32438D||034||Lecture||12:30-1:50pm||Tue, Thu||7 of 10||Joseph Greenfield||DEN@Viterbi||PDF (482504 KB)|
Fundamentals of big data informatics techniques. Data lifecycle; the data scientist; machine learning; data mining; NoSQL databases; tools for storage/processing/analytics of large data set on clusters; in-data techniques. Recommended preparation: Basic understanding of engineering and/or technology principles; basic programming skills; background in probability, statistics, linear algebra and machine learning.
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|Seon Kim||THH119||PDF (140624 KB)|
Practical applications of machine learning techniques to real-world problems. Uses in data mining and recommendation systems and for building adaptive user interfaces. Recommended preparation: INF 550 and INF 551 taken previously or concurrently; knowledge of statistics and linear algebra; programming experience.
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|Stefan Scherer||LVL13||PDF (132702 KB)|
Data mining and machine learning algorithms for analyzing very large data sets. Emphasis on Map Reduce. Case studies. Recommended preparation: INF 550, INF 551 and INF 552. Knowledge of probability, linear algebra, basic programming, and machine learning.
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Graphical depictions of data for communication, analysis, and decision support. Cognitive processing and perception of visual data and visualizations. Designing effective visualizations. Implementing interactive visualizations.
|32404D||048||Lecture||2:00-4:50pm||Monday||23 of 32||Luciano Nocera||THH108||PDF (337056 KB)|
The practice of User Experience Design and Strategy principles for the creation of unique and compelling digital products and services. Open only to Data Informatics majors. Recommended preparation: Basic familiarity with web development and/or graphic design using a digital layout tool.
- Restriction: Registration open to the following major(s): Data Informatics
|32436D||048||Lecture||3:30-6:20pm||Thursday||19 of 20||Jaime Levy||WPH101||PDF (176308 KB)|
Research leading to the master's degree; maximum units which may be applied to the degree to be determined by the department. Graded CR/NC.
- Restriction: Registration open to the following major(s): INF
|32449D||048||2.0||Lecture||TBA||TBA||8 of 10||Cyrus Shahabi||OFFICE|