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[…] detect security incidents , protect against malicious, deceptive, fraudulent, or illegal activity, or prosecute those responsible for that activity; 2727 Differences (cont’d) • debug to identify and repair errors that impair existing intended functionality ; • to enable solely internal uses that are reasonably aligned with the expectations of the consumer based on the […]

[…] https://www.commerce.gov/news/blog/2019/10/internet -things . 38 WhatIsMyIPAddress.com, What is a MAC address? , https://whatismyipaddress.com/mac -address (last visited Nov. 25, 2019). 39 See Jules Polonetsky, Omer Tene, and Kelsey Finch, Shades of Gray: Seeing the Full Spectrum of Practical Data De -identification , 56 SantaClaraL. Rev. 593 (2016). 10 toy store’s age inference might be stronger if […]

[…] Defensibility and reduce Ligations and Enforcements with Strong Proof of Records The Business Case for Privacy “Trust takes years to build, seconds to destroy, and forever to repair.” … And trust among the public is at an all – time low today Guard Your Reputation Pew Research Internet Project • Public Perceptions of Privacy […]

[…] Exempts vehicle information shared between a new auto dealer and a vehicle manufacturer when information is shared or retained pursuant to, or in anticipation of, a vehicle repair relating to warranty work or recall. AB 1202 Data broker requirements – Defines a “data broker” and requires data brokers to register with and provide certain […]

[…] when they talk about de-identification? How does anonymous data differ from pseudonymous or de-identified information? Data identifiability is not binary. Data lies on a spectrum with multiple shades of identifiability. This is a primer on how to distinguish different categories of data. FPF.ORGProduced by In collaboration with LIMITED or NONE IN PLACE CONTROLS IN […]

[…] LAW AND LEGAL THEORY W ORKING PAPERS , Paper 530 (2015)  De -Identification of Personal Information (NISTIR 8053) , Simon Garfinkel, NIST (October 2015 )  Shades of Gray: Seeing the Full Spectrum of Practical Data De -identification , Jules Polonetsky et al., 56 SANTA CLARA L. REV . 593 (June 2016)  […]

[…] consumer ; • detect security incidents , protect against malicious, deceptive, fraudulent, or illegal activity, or prosecute those responsible for that activity; • debug to identify and repair errors that impair existing 28 Fairly consistent D a t a G u i d a n c e Dierences (cont’d) intended functionality ; • to […]

[…] X, line 21, for escrow or custodial account liability, serve as a custodian for amounts not listed in Part X; or provide credit counseling, debt management, credit repair, or debt negotiation services? Did the organization, directly or through a related organization, hold assets in temporarily restricted endowments, permanent endowments, or quasi-endowments? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~ If […]

[…] X, line 21, for escrow or custodial account liability, serve as a custodian for amounts not listed in Part X; or provide credit counseling, debt management, credit repair, or debt negotiation services? Did the organization, directly or through a related organization, hold assets in temporarily restricted endowments, permanent endowments, or quasi-endowments? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~ If […]