View The Document

Accession Number:

AD1064608

Title:

Privacy Support for the Total Learning Architecture Volume 2: Modeling Factors

Author(s):

• Knijnenburg, Bart P.
• Cherry, David
• He, Yang
• Anaraky, Reza G.
• Namara, Moses
• Ash, Erin
• Johnson, A.

Author Organization(s):

• CLEMSON UNIV SC

Report Date:

2018-07-31

Abstract:

The purpose of this document is to make recommendations for implementing User-Tailored Privacy (UTP) into Total Learning Architecture (TLA)-based systems and to inform ADL and other TLA performers about the Modeling Factors that need to be considered in the context of this implementation. The set of recommendations put forth in this document will allow ADL and other TLA performers to build a user-tailored privacy decision-support system that supports users in making better privacy decisions.

Document Type:

Conference:

Journal:

Pages:

115

File Size:

1.61MB

Contracts:

Grants:

Descriptors:

• internet
• information science
• information systems
• social networking services
• network science
• information processing
• multiagent systems
• data mining
• electronic commerce
• psychology
• machine learning
• social networks
• computational science
• cognitive systems engineering
• distance learning
• information exchange
• social media
• artificial intelligence
• computers
• cybersecurity

Identifiers:

• utp(User-Tailored Privacy)
• tla(Total Learning Architecture)
• lms(learning management system)

SubjectCategory:

• Mathematical and Computer Sciences

Communities of Interest:

• Cyber

Distribution Statement:

Approved For Public Release

View The Document