Privacy Concerns with Big Data Analytics: US DoD/Army Landscape
(Room 320C)
04 Dec 19
11:00 AM
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11:30 AM
Tracks:
Full Schedule, Wednesday Schedule
Big data analytics is a relatively new field but matured enough to provide innovatory solutions to automate mining and extracting data from the next generation Mission Command (MC) and Live, Virtual and Constructive (LVC) simulation systems. It provides powerful technologies and methods to quickly analyze huge amounts of data but also introduces potential harms to individuals whose personal data is collected, stored, analyzed, used for decision-making, and disclosed. Desire to keep big datasets indefinitely, reuse it for different projects, combine it with additional data, and automate decisions based on data presents privacy and security challenges. Moreover, big data may increase system opacity because of many streams of data created by multiple stakeholders, complicated algorithms processing the data, multiple storage locations, and multiple data consumers with different data aggregation needs. This increased complexity can lead to data leaking, breaches, spillages, and re-identification of individuals. On the other hand, it is critical to take full advantage of big data by processing special data categories on individuals and a variety of data types. Without using combined personal attributes, quasi-identifiers, and sensitive attributes combined with insensitive attributes data utility decreases or may even render analysis useless. This paper discusses the importance and benefits of using big data especially focusing on the US Department of the Army (DA). It presents privacy laws, policies, and regulations relevant to the DoD/DA and investigates their incompatibilities with big data principles. Moreover, it identifies privacy-preserving components relevant to big data, allowing for a balanced approach that benefits the DoD/DA while preserving the privacy of individuals.