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[…] Remedies Provided by Law Are Not Foreclosed Violations of MODPA are tied to the Maryland Consumer Protection Act, and the Act specifically denies private enforcement under Md. Code Com. Law § 13-408, leaving enforcement solely with the Division of Consumer Protection of the Office of the Attorney General. However, the Act specifies that “his […]

[…] that require a privacy manifest and an application signature. Developers have had to be extremely cautious in adopting new SDKs because they are responsible for all the code in their app as well as the code in third-party SDKs included in their app. The goal of combining privacy manifests with an application signature is […]

[…] Brussels Privacy Symposium . 2012 FPF launches a first-of-its-kind privacy seal program for companies that use consumer energy information. EXPLICITLY PERSONAL POTENTIALLY IDENTIFIABLE NOT READILY IDENTIFIABLE KEY CODED PSEUDONYMOUS PROTECTED PSEUDONYMOUS DE-IDENTIFIEDPROTECTED DE-IDENTIFIED ANONYMOUSAGGREGATED ANONYMOUS SELECTED EXAMPLESINTACT ELIMINATED or TRANSFORMED ELIMINATED or TRANSFORMED INTACT INTACTINTACTINTACT INTACT PARTIALLY MASKED INTACT PARTIALLY MASKED ELIMINATED or TRANSFORMED […]

[…] Information: FTC Committed to Fully Enforcing the Law Against Illegal Use and Sharing of Highly Sensitive Data, Federal Trade Commission (July 11, 2022), https://www.ftc.gov/business- guidance/blog/2022/07/location-health-and-other-sensitive-information-ftc-committed-fully-enforcing-law-against-illegal. 29 Revised Code of Washington § 19.373.005 – 19.373.900 (2023). 30 Examples of Data Points Used in Profiling, Privacy International (April 2018), https://privacyinternational.org/sites/default/ files/2018- 04/data%20points%20used%20in%20tracking_0.pdf. 31 Yassine Zahraoui et […]

[…] Zurich, under the advisorship of Prof. Dr. Martin Vechev. His research focuses on the security and privacy of modern machine learning systems, investigating federated learning, synthetic data, code generation, and large language models. He was part of the SRI team, winning the 2023 U.S. PETs Prize Federated Learning Red Teaming Challenge organized by NIST. […]

[…] Information: FTC Committed to Fully Enforcing the Law Against Illegal Use and Sharing of Highly Sensitive Data, Federal Trade Commission (July 11, 2022), https://www.ftc.gov/business- guidance/blog/2022/07/location-health-and-other-sensitive-information-ftc-committed-fully-enforcing-law-against-illegal. 29 Revised Code of Washington § 19.373.005 – 19.373.900 (2023). 30 Examples of Data Points Used in Profiling, Privacy International (April 2018), https://privacyinternational.org/sites/default/ files/2018- 04/data%20points%20used%20in%20tracking_0.pdf. 31 Yassine Zahraoui et […]

[…] networking among peers, fostering new connections and addressing common challenges. We anticipate lively group discussions and encourage active participation from each attendee. (Chatham House Rules & FPF’s Code of Conduct are to be followed please). 2024 Advisory Board Meeting Directory The directory link (COMING SOON!) will be shared here the week of the event. […]

[…] bill was approved by the Health Commission Rapporteur in October 2023 and awaits further consideration.  The neurorights discussion has also made its way into Brazil’s Federal Civil Code. In December 2023, the Sub-Committee on Digital Law of the Commission of Jurists, who are responsible for reviewing the Civil Code, submitted a report that seeks […]

[…] Information: FTC Committed to Fully Enforcing the Law Against Illegal Use and Sharing of Highly Sensitive Data, Federal Trade Commission (July 11, 2022), https://www.ftc.gov/business- guidance/blog/2022/07/location-health-and-other-sensitive-information-ftc-committed-fully-enforcing-law-against-illegal. 29 Revised Code of Washington § 19.373.005 – 19.373.900 (2023). 30 Examples of Data Points Used in Profiling, Privacy International (April 2018), https://privacyinternational.org/sites/default/ files/2018- 04/data%20points%20used%20in%20tracking_0.pdf. 31 Yassine Zahraoui et […]

[…] Zurich, under the advisorship of Prof. Dr. Martin Vechev. His research focuses on the security and privacy of modern machine learning systems, investigating federated learning, synthetic data, code generation, and large language models. He was part of the SRI team, winning the 2023 U.S. PETs Prize Federated Learning Red Teaming Challenge organized by NIST. […]