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[…] are especially egregious when the victim is a child. Financial fraud and identity theft increasingly target young Americans, who are often unable to discover or combat the crimes until years later. 27 Worse, 2014) https://www.dhs.gov/publication/fair-information-practice-principles-fipps; Executive Orders 13636 and 13691: Privacy and Civil Liberties Assessment Report , U.S. Dᴇᴘᴛ ᴏғ Hᴏᴍᴇʟᴀɴᴅ Sᴇᴄ. Pʀɪᴠᴀᴄʏ Oғғɪᴄᴇ […]

1 Processing Personal D ata on the Basis of Legitimate Interests under the GDPR PRACTICAL CASES The Future of Privacy Forum and Nymity would like to thank Gabriela Zanfir -Fortuna (Policy Counsel, FPF) and Teresa Troester -Falk (Chief Global Privacy Strategist, Nymity) for authoring this paper and Me aghan McCluskey (Director, Compliance Research, Nymity) principal […]

1 Processing Personal D ata on the Basis of Legitimate Interests under the GDPR PRACTICAL CASES The Future of Privacy Forum and Nymity would like to thank Gabriela Zanfir -Fortuna (Policy Counsel, FPF) and Teresa Troester -Falk (Chief Global Privacy Strategist, Nymity) for authoring this paper and Me aghan McCluskey (Director, Compliance Research, Nymity) principal […]

1 Appendix C: Model Benefit -Risk Analysis Step 1: Evaluate the I nformation the Dataset Contains Dataset: ___ ___________________________ Consider the following categories of information: o Direct Identifiers: These are data points that identify a person without additional information or by linking to other readily availabl e information. “Personally Identifiable Information,” or PII, often falls […]

[…] There may be some concern that the city’s dataset is consolidating and highlighting propertie s and individuals that would make particularly good targets for financial or property crimes, which could make it a target for lawsuits . o Data quality and equity impacts : This dataset’s connection to the Construction and =nspections department’s trackers […]

1 October 2, 2017 Dear Kelsey Finch, We are pleased to have the opportunity to provide comments on the Future of Privacy Forum proposed draft report for the City of Seattle Open Data Risk Assessment. Municipalities face significant challenges regarding the design and implementation of privacy -aware open data systems. A model risk assessment framework […]

[…] ** 3.412 ** Table 1: Logistic Regression Model Predicting Odds of School Using Security Practices Metal Detectors Locked Gates Random Sweeps SROs/Guards Surveillance Cameras School Crime Weapons/Sex Crimes 1.259 1.162 1.098 1.292 .838 Non – weapon/non – sex crimes 1.157 .962 1.079 1.035 1.185 School Disorder .930 .916 1.206 1.460* 1.717* Geographic Region Northeast […]

[…] of Service (DOS/Ddos) o Mobile/remote o Third -party attacks Understanding the Threat  Cyber criminals o Motivated by money o ID theft o W2 scams o Financial Crimes  Employees o Just looking o Occasionally malicious  EXAMPLE: Disgruntled employee who fired deleted 1450 out of 1500 students from the student information system. They […]

The Future of Privacy Forum tracks student privacy news very closely, and shares relevant news stories with our newsletter subscribers. Approximately every month, we post “The Top 10,” a blog with our top student privacy stories.

Checkifself-employed OMB No. 1545-0047 Department of the TreasuryInternal Revenue Service Check ifapplicable: AddresschangeNamechangeInitialreturnFinalreturn/termin-ated Gross receipts $ AmendedreturnApplica-tionpending Are all subordinates included? 632001 11-11-16 Beginning of Current Year Paid Preparer Use Only Under section 501(c), 527, or 4947(a)(1) of the Internal Revenue Code (except private foundations) | Do not enter social security numbers on this form […]