{"id":39317,"date":"2021-01-27T23:17:02","date_gmt":"2021-01-27T23:17:02","guid":{"rendered":"http:\/\/b8e88369-833d-4559-853c-97be465631c6"},"modified":"2021-01-27T23:17:02","modified_gmt":"2021-01-27T23:17:02","slug":"nsw-running-data61-de-identification-tool-across-covid-data-prior-to-public-release","status":"publish","type":"post","link":"https:\/\/www.threatshub.org\/blog\/nsw-running-data61-de-identification-tool-across-covid-data-prior-to-public-release\/","title":{"rendered":"NSW running Data61 de-identification tool across COVID data prior to public release"},"content":{"rendered":"
<\/div>\n

The New South Wales government has been using a tool to help de-identify data related to COVID-19 prior to the release of that data to the public, the CSIRO said on Thursday.<\/p>\n

The tool, dubbed Personal Information Factor (PIF), has been created by Data61, the NSW government, the Australian Computer Society, Cyber Security Cooperative Research Centre (CSCRC), and “several other groups”.<\/p>\n

“The privacy tool assesses the risks to an individual’s data within any dataset; allowing targeted and effective protection mechanisms to be put in place,” the CSIRO claimed.<\/p>\n

“The software uses a sophisticated data analytics algorithm to identify the risks that sensitive, de-identified and personal information within a dataset can be re-identified and matched to its owner.”<\/p>\n

NSW chief data scientist Dr Ian Oppermann said the tool was being used on datasets containing data on people who had been infected with COVID-19 before it was made publicly available.<\/p>\n

“Given the very strong community interest in growing COVID-19 cases, we needed to release critical and timely information at a fine-grained level detailing when and where COVID-19 cases were identified,” Oppermann said.<\/p>\n

“This also included information such as the likely cause of infection and, earlier in the pandemic, the age range of people confirmed to be infected.<\/p>\n

<\/section>\n

“We wanted the data to be as detailed and granular as possible, but we also needed to protect the privacy and identity of the individuals associated with those datasets.”<\/p>\n

Data61 said PIF assigns a risk score to a dataset and makes recommendations to make de-identification “more secure and safe”.<\/p>\n

The tool is also being used on other datasets such as domestic violence data and public transport usage, Data61 said.<\/p>\n

PIF will be made available by June 22.<\/p>\n

In a recent submission to a review of the Privacy Act<\/a>, security researcher Vanessa Teague said de-identification does not work.<\/p>\n

“A person’s detailed individual record cannot be adequately de-identified or anonymised, and should not be sold, shared, or published without the person’s explicit, genuine, informed consent,” Teague said.<\/p>\n

“Identifiable personal information should be protected exactly like all other personal information, even if an attempt to de-identify it was made.” <\/p>\n

At the end of 2017, a team of academics, including Teague, were able to re-identify some of the data<\/a> from a set containing historic longitudinal medical billing records on one-tenth of all Australians.<\/p>\n

“We found that patients can be re-identified, without decryption, through a process of linking the unencrypted parts of the record with known information about the individual such as medical procedures and year of birth,” Dr Chris Culnane said at the time.<\/p>\n

“This shows the surprising ease with which de-identification can fail, highlighting the risky balance between data sharing and privacy.”<\/p>\n

In September 2016, the same dataset was found by the University of Melbourne team to not be encrypting supplier codes properly<\/a>. The dataset was subsequently pulled down by the Department of Health.<\/p>\n

“Leaving out some of the algorithmic details didn’t keep the data secure \u00ad– if we can reverse-engineer the details in a few days, then there is a risk that others could do so too,” the team said at the time.<\/p>\n

“Security through obscurity doesn’t work — keeping the algorithm secret wouldn’t have made the encryption secure, it just would have taken longer for security researchers to identify the problem.<\/p>\n

“It is much better for such problems to be found and addressed than to remain unnoticed.”<\/p>\n

In response, the Australian government sought to criminalise the intentional re-identification<\/a> and disclosure of de-identified Commonwealth datasets and reverse the onus of proof, with the aim of applying the changes retrospectively from 29 September 2016.<\/p>\n

The changes lapsed at the 2019 election.<\/p>\n

\n

Coronavirus<\/span> <\/h3>\n<\/p><\/div>\n

READ MORE HERE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

The Personal Information Factor tool is claimed by the CSIRO to lower the risk of de-identified data being re-identified.
\nREAD MORE HERE…<\/p>\n","protected":false},"author":2,"featured_media":39318,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"colormag_page_layout":"default_layout","footnotes":""},"categories":[62],"tags":[],"class_list":["post-39317","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-zdnet-security"],"yoast_head":"\nNSW running Data61 de-identification tool across COVID data prior to public release 2026 | ThreatsHub Cybersecurity News<\/title>\n<meta name=\"description\" content=\"ThreatsHub Cybersecurity News | ThreatsHub.org | Cloud Security & Cyber Threats Analysis Hub. 100% Free OSINT Threat Intelligent and Cybersecurity News.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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