Canadian Security Magazine

Federal security officials eye big data analytics

By Jim Bronskill for The Canadian Press   

News Public Sector analytics big data privacy

OTTAWA — Federal security agencies risk being overwhelmed by threats — or failing to even foresee them — unless they embrace the digital-age phenomenon of big-data crunching, warns an internal Public Safety Canada presentation.

With billions of people using mobile phones and surfing the Internet, security officials are preoccupied with getting timely access to valuable information. But the recent past is littered with challenges related to information sharing and privacy — including controversy over the Conservative omnibus bill known as C-51, the presentation notes.

Officials acknowledge the public might not trust government to respect privacy in the process, pointing to revelations by former U.S. spy contractor Edward Snowden about widespread surveillance of communications.

“Canadians are increasingly concerned about issues of crime and terrorism, but in the post-Snowden era, public concerns about government data use may stand as a barrier to the effective use of innovative data analytics by law enforcement and security organizations,” the presentation says.

Big data analytics generally refers to the process of gathering and systematically sifting through millions or even billions of pieces of data — numbers, text, graphics, videos and sensor information — to glean insights that can’t be detected through standard methods.


Given the pace of technological advancement and the exponential increase in the amount of data produced worldwide, there may be opportunities to do things more efficiently and identify patterns through innovative techniques, the presentation says.

“In other words, once we have the information, how can we ensure that we are in a position to use it effectively?”

The May 2015 presentation, Big Data Analytics in the World of Safety and Security, was prepared for Public Safety Canada’s internal policy committee. The Canadian Press obtained a declassified version of the secret draft presentation under the Access to Information Act. Small portions were withheld due to their sensitivity.

The presenters cite examples of using big data analysis to create efficiencies, find a needle in a haystack and fill data gaps. For instance:

— Philadelphia police mined data to predict a parolee’s risk of reoffending to determine the necessary level of supervision;

— U.S. researchers found that a genetic variant related to schizophrenia was not detectable when reviewing 3,500 cases but were able to pinpoint a trend by looking at 35,000 cases;

— In Guatemala, a pilot project revealed how mobile phone movement patterns could be used to predict socioeconomic status.

More than two years ago, Jennifer Stoddart, the federal privacy commissioner at the time, cautioned that big data had not simply increased the risk to privacy — it had changed the very nature of that risk.

The Public Safety presentation allows that privacy considerations and building public confidence must be taken into account.

“Privacy does not need to be a barrier to innovative data analytics,” it says. “We need to think strategically about what we want to accomplish with data and then design in appropriate privacy protections.”

The officials also stress the importance of finding the right partners to pursue “promising practices” as well as ensuring agencies have the technology, policies and people to make the most of the techniques.

Other federal departments and provincial security partners are exploring the potential of big data analytics, they note, but “innovation is limited and often done in silos.”

The risk of not harnessing big data is a “reduced capacity to respond to — or even understand — the changing threat environment,” the presentation warns.

Ultimately, the presenters ask whether officials should explore big data opportunities in more depth and, if so, which ones would be most useful to the portfolio?

Public Safety had no immediate comment on the department’s plans.

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