I study the intersection of human-computer interaction and systems security, investigating users’ (mis)behavior with systems security. Oftentimes users are unwilling to report socially unacceptable behavior such as violating security policies. Or, they are unable to explain why they did not notice a security warning. Furthermore, it is challenging to ask users about their security behavior and still obtain ecologically-valid data since doing so primes users to think about security. This is problematic because in practice, security tasks are secondary tasks – they are not the focus of primary attention. Given these challenges, studying this field while still obtaining generalizable results requires carefully-crafted laboratory studies that do not prime users to security. Alternatively, field studies are required. Survey instruments can be of use to the extent that they capture constructs that are antecedents to real security behaviors.
keywords
Human-computer interaction, Behavioral information system security, Neuroscience applications to HCI and information security
BAIM 3200 - Business Analytics
Primary Instructor
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Fall 2018
Teaches cutting-edge tools and approaches to the analysis of data, including "big data" for effective decision-making. The class creates data connoisseurs through hands-on exposure to exploratory and predictive analytics. Application areas covered include Web Marketing, the Internet of Things, Biometric Monitoring, as well as data integration and analysis for online marketing, human resources and operations. Formerly MGMT 3200. Credit not granted for this course and MKTG 3201.
BAIM 4250 - Information Security Management
Primary Instructor
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Fall 2018 / Fall 2019 / Fall 2020 / Spring 2022
A broad introduction to the managerial issues of information security. Because security is multifaceted, the topics of the class range widely, including technical (e.g., cryptography), managerial (e.g., policy compliance), physical (e.g., door locks) and psychological (e.g., social engineering) issues. A key objective is to develop a security mindset, in which one learns to think like an attacker for ways to exploit a system. Formerly MGMT 4250.
MGMT 3200 - Business Analytics
Primary Instructor
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Spring 2018
Teaches cutting-edge tools and approaches to the analysis of data, including "big data" for effective decision-making. The class creates data connoisseurs through hands-on exposure to exploratory and predictive analytics. Application areas covered include Web Marketing, the Internet of Things, Biometric Monitoring, as well as data integration and analysis for online marketing, human resources and operations. Formerly MGMT 3200. Credit not granted for this course and MKTG 3201.
MKTG 3201 - Business Analytics
Primary Instructor
-
Spring 2018 / Fall 2018
Teaches cutting-edge tools and approaches to the analysis of data, including "big data" for effective decision-making. Creates data connoisseurs through hands-on exposure to exploratory and predictive analytics. Application areas covered include Web Marketing, the Internet of Things, Biometric Monitoring, as well as data integration and analysis for online marketing, human resources and operations. Same as MGMT 3201. Degree credit not granted for this course and BAIM 4120.
MSBX 5480 - Information Security Management
Primary Instructor
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Fall 2018 / Fall 2019 / Fall 2020 / Spring 2022
A broad introductions to the managerial issues of information security. Because security is multifaceted, the topics of the class range widely, including technical (e.g., cryptography), managerial (e.g., policy compliance), physical (e.g., door locks), and psychological (e.g. social engineering) issues. A key objective of the class is to develop a security mindset, in which one learns to think like an attacker for ways to exploit a system.
MSBX 5500 - Security Analytics with Python and Machine Learning
Primary Instructor
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Spring 2020 / Spring 2021 / Spring 2022
Explores the application of data analytics to the domain of information security. Project-based class using python machine learning libraries to both build and deploy models for both supervised and unsupervised modeling algorithms. Business problem contexts include classifying the likelihood that a file or website is malicious based on either extracted static indicators or dynamic behavioral analysis (predictive analytics), as well as network anomaly detection on organizational network traffic data or on user account usage (unsupervised machine learning). Master of Business Admin (MBAD), MBA w/ Dual Degree (DMBA), Joint Juris Doctor/MBA (JMBA), Profl MBA Program (PMBA) can seek departmental approval to enroll upon demonstration of data networking and modeling capabilities.
