Brown U Reseachers Recommend Data Shuffling Technique To Secure Cloud Activity
Researchers at Brown University have
developed a data shuffling technique that aims to improve security of data
stored in the cloud by hiding usage patterns, which can be analyzed to reveal
secret information.
Without data shuffling, snoopers and cloud providers can monitor which files
an organization accesses from a cloud service and when, even though the content
of those files themselves is encrypted. By tracking that information, along with
major events related to the organization, the third parties can figure out what
an organization may be doing before that information is made public.
For example, if an organization typically accesses a particular set of files
stored at a particular location on the cloud server before announcing a negative
earnings report, eavesdroppers can figure out when the organization is preparing
to release such a report again. Some programs, such as those for processing
bankruptcy proceedings, may also have a recognizable pattern of accessing data.
When snoopers detect that pattern, they can deduce that the organization may be
preparing to file for bankruptcy.
The data shuffling technique, dubbed the Melbourne Shuffle after a dance move
originating in Australia where one of the researchers did her graduate studies,
aims to add an extra layer of security to data stored in the cloud. The
technique downloads data from the cloud in small chunks, rearranges it, and then
uploads it back to the cloud. By repeating the process with different blocks of
data, all of an organization's cloud data can be shuffled, so data snoopers can
no longer detect patterns.
According to information from the university, "the researchers envision
deploying their shuffle algorithm through a software application or a hardware
device that users keep at their location. It could also be deployed in the form
of a tamper-proof chip controlled by the user and installed at the data center
of the cloud provider."
The research paper, "The Melbourne Shuffle: Improving Oblivious Storage in
the Cloud," can be found on arXiv.
About the Author
Leila Meyer is a technology writer based in British Columbia. She can be reached at [email protected].