Difference between revisions of "GDPArrrrr: Using Privacy Laws to Steal Identities (Q3215)"
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(Created claim: comment (P126): We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to performwell and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests.) |
(Changed claim: comment (P126): We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to perform well and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests.) |
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| Property / comment | Property / comment | ||
| - | + | We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to perform well and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests. | |
Revision as of 17:07, 7 January 2020
scholarly article published in 2019
| Language | Label | Description | Also known as |
|---|---|---|---|
| English |
GDPArrrrr: Using Privacy Laws to Steal Identities
|
scholarly article published in 2019
|
Statements
In a survey of more than 150 companies, the authors demonstrate that organizations willingly provide highly sensitive information in response to GDPR right of access requests with little or no verification of the individual making the request.
0 references
We found that the largest organizations in our data set (e.g. Fortune 100 companies) tended to perform well and that the smallest organizations tended to simplyi gnore GDPR requests. Non-profits and mid-size orga-nizations (100 - 1,000 employees) accounted for around70% of mishandled requests.
0 references