Browser Fingerprinting Sample Clauses

The Browser Fingerprinting clause defines the rules and limitations regarding the collection and use of information that uniquely identifies a user's web browser. Typically, this clause outlines what types of browser data may be collected, such as installed fonts, plugins, or device settings, and under what circumstances this data can be used to track or identify users. Its core practical function is to inform users and set boundaries for privacy, helping to prevent unauthorized tracking and ensuring compliance with data protection regulations.
Browser Fingerprinting. Collection and analysis of information from your Device, such as, without limitation, your operating system, plug-ins, system fonts and other data, for purposes of identification; and
View SourceView Similar (7)

Related to Browser Fingerprinting

  • Fingerprinting For purposes of this Agreement and because the District will provide a qualified employee for the supervision of District's students at all times that Consultant is present and performing services at an active school site, Consultant shall be relieved of the requirements to provide a criminal background check pursuant to California Education Code 45125.1.

  • Fingerprinting Requirements Contractor hereby acknowledges that, if applicable, it is required to comply with the requirements of Education Code Section 45125.1 with respect to fingerprinting of employees who may have contact with the District's students. The Contractor shall also ensure that its Contractors on the Project also comply with the requirements of Section 45125.1. If required by Education Code Section 45125.1, the Contractor must provide for the completion of a Fingerprint Certification form, in the District’s required format, prior to any of the Contractor's employees, or those of any other Contractors, coming into contact with the District's students. Contractor further acknowledges that other fingerprinting requirements may apply, as set forth in Education Code Section 45125 et seq., and will comply with any such requirements.

  • Workstation/Laptop encryption All workstations and laptops that process and/or store County PHI or PI must be encrypted using a FIPS 140-2 certified algorithm which is 128bit or higher, such as Advanced Encryption Standard (AES). The encryption solution must be full disk unless approved by the County Information Security Office.

  • Images If applicable, the CONSULTANT is prohibited from capturing on any visual medium images of any property, logo, student, or employee of the DISTRICT, or any image that represents the DISTRICT without express written consent from the DISTRICT.

  • Bibliography [ABD16] ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇, ▇▇▇ ▇▇▇, and ▇▇▇ ▇▇▇▇▇. A subfield lattice attack on overstretched NTRU assumptions. In: Springer, 2016, pages 153–178. [AD21] ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇ and ▇▇▇ ▇▇▇▇▇. Lattice Attacks on NTRU and LWE: A History of Refinements. In: Compu- tational Cryptography: Algorithmic Aspects of Cryptol- ogy. London Mathematical Society Lecture Note Series. Cambridge University Press, 2021, pages 15–40. [ADPS16] ▇▇▇▇▇ ▇▇▇▇▇, ▇▇▇ ▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇, and Pe- ter ▇▇▇▇▇▇▇. Post-quantum Key Exchange–A New Hope. In: 2016, pages 327–343. [AEN19] ▇▇▇▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇, and ▇▇▇▇▇ ▇. ▇▇▇▇▇▇. Random Lattices: Theory And Practice. Available at ▇▇▇▇▇://▇▇▇▇▇▇▇.▇▇▇▇▇▇.▇▇/bin/random_lattice. pdf. 2019. [AFG13] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇. On the efficacy of solving LWE by reduction to unique-SVP. In: Springer, 2013, pages 293–310. [AGPS20] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇, ▇▇▇▇ ▇▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇ ▇. ▇▇▇▇▇▇▇. Estimating quan- tum speedups for lattice sieves. In: Springer, 2020, pages 583–613. [AGVW17] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇, ▇▇▇▇▇▇▇▇ ▇▇▇▇▇▇, and ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇. Revisiting the expected cost of solving uSVP and applications to LWE. In: International Conference on the Theory and Application of Cryptology and Information Security. Springer. 2017, pages 297–322. [Ajt99] ▇▇▇▇▇▇ ▇▇▇▇▇. Generating Hard Instances of the Short Basis Problem. In: ICALP. 1999, pages 1–9. [AKS01] ▇▇▇▇▇▇ ▇▇▇▇▇, ▇▇▇▇ ▇▇▇▇▇, and ▇. ▇▇▇▇▇▇▇▇▇. A sieve algorithm for the shortest lattice vector problem. In: STOC. 2001, pages 601–610. [AL22] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇ and ▇▇▇▇▇▇▇ ▇▇. Predicting BKZ Z- Shapes on q-ary Lattices. Cryptology ePrint Archive, Re- port 2022/843. 2022. [Alb+15] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇, ▇▇▇▇-▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇▇▇▇ ▇▇▇▇▇▇. On the complex- ity of the BKW algorithm on LWE. In: Designs, Codes and Cryptography 74.2 (2015), pages 325–354. [Alb+19] ▇▇▇▇▇▇ ▇. ▇▇▇▇▇▇▇▇, ▇▇▇ ▇▇▇▇▇, ▇▇▇▇▇▇▇▇▇ ▇▇▇▇▇▇, ▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇ ▇▇▇▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇ ▇▇▇▇▇▇▇. The general sieve kernel and new records in lattice reduction. In: Annual International Conference on the Theory and Applications of Cryptographic Tech- niques. Springer. 2019, pages 717–746. [ALL19] ▇▇▇▇▇▇▇ ▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇▇▇, and ▇▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇. Decoding Challenge. Available at http : / / ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇.▇▇▇. 2019. [AN17] ▇▇▇▇▇▇▇▇▇ ▇▇▇▇ and ▇▇▇▇▇ ▇. ▇▇▇▇▇▇. Random ▇▇▇- ▇▇▇▇▇ revisited: lattice enumeration with discrete prun- ing. In: Eurocrypt. 2017, pages 65–102. [ANS18] ▇▇▇▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇ ▇. ▇▇▇▇▇▇, and ▇▇▇▇▇ ▇▇▇▇. Quantum lattice enumeration and tweaking discrete pruning. In: Asiacrypt. 2018, pages 405–434. [AP11] ▇▇▇▇ ▇▇▇▇▇ and ▇▇▇▇▇ ▇▇▇▇▇▇▇. Generating Shorter Bases for Hard Random Lattices. In: Theory of Computing Sys- tems 48.3 (Apr. 2011). Preliminary version in STACS 2009, pages 535–553. [AR05] ▇▇▇▇▇ ▇▇▇▇▇▇▇▇ and ▇▇▇▇ ▇▇▇▇▇. Lattice problems in NP coNP. In: J. ACM 52.5 (2005). Preliminary version in FOCS 2004, pages 749–765. [AUV19] ▇▇▇▇▇▇ ▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇, and ▇▇▇▇▇ ▇▇▇▇▇▇▇▇. Faster sieving algorithm for approximate SVP with con- stant approximation factors. Cryptology ePrint Archive, Report 2019/1028. 2019. [AWHT16] ▇▇▇▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇▇ ▇▇▇▇▇▇▇, and ▇▇▇▇▇▇▇▇ ▇▇▇▇▇▇. Improved progressive BKZ algorithms and their precise cost estimation by sharp simulator. In: Springer, 2016, pages 789–819. [Bab16] ▇▇▇▇▇▇ ▇▇▇▇▇. Graph isomorphism in quasipolynomial time. In: Proceedings of the forty-eighth annual ACM symposium on Theory of Computing. 2016, pages 684– 697. [Bab19] ▇▇▇▇▇▇ ▇▇▇▇▇. Canonical form for graphs in quasipolyno- mial time: preliminary report. In: Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Com- puting. 2019, pages 1237–1246. [Bab86] ▇▇▇▇▇▇ ▇▇▇▇▇. On ▇▇▇▇▇▇’ lattice reduction and the near- est lattice point problem. In: Combinatorica 6.1 (1986). Preliminary version in STACS 1985, pages 1–13.