# US 10,313,127 B1 · Method and system for detecting and alerting users of device fingerprinting attempts > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,313,127 B1 - Document ID: US10313127B1 - Status: Granted - Kind: B1 - Application number: 16/155,254 - Filed: 2018-10-09 - Granted: 2019-06-04 - Earliest claimed: 2018-09-28 - Assignees: Trackoff, Inc. - Applicants: TRACKOFF, Inc. - Inventors: Ryan A Flach; Chandler R Givens - Web page: https://patentgrep.com/patent/US10313127B1 ## CPC - H04L 9/3231: {Biological data, e.g. fingerprint, voice or retina (network architectures or network communication protocols for supporting authentication of entities using biometrical features in a packet data network H04L63/0861)} - G06F 17/18: for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} - G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints - G06F 21/554: {involving event detection and direct action} - G06F 21/566: {Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities} - G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes} - G06F 21/73: by creating or determining hardware identification, e.g. serial numbers - H04L 9/0866: {involving user or device identifiers, e.g. serial number, physical or biometrical information, DNA, hand-signature or measurable physical characteristics} - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method for detecting attempts to collect parameters used for device fingerprinting includes receiving information traversing a communications network and creating a dataset of examinable information. The dataset is then analyzed using a weighted scoring system to determine the probability that parameters present are intended for purposes of device fingerprinting and a score reflecting the same is returned. ## Claims ### Claim 1 A detection system for detecting attempts to collect parameters to create a device fingerprint, comprising: a computer program provided on a computing device having a processor and a non-transitory computer-readable medium and comprising one or more computer program instructions that when executed by said processor operate said detection system and cause the processor to perform a detection process, wherein said computer program of said detection system comprises: a fingerprint detection module defined by said computer program instructions, said fingerprint detection module receiving information traversing a communications network and performing the steps of: identifying a subset of said information based on a classification of the information transmitted and generating a dataset from the subset of information for analysis to identify parameters used for device fingerprinting; determining a probability that parameters contained in said dataset are present for collecting information used for device fingerprinting based on analysis using a weighted scoring system; and returning a score that reflects the probability the parameters present in the dataset are present for device fingerprinting, wherein the classification of information transmitted to generate a dataset is based on one of: the identification of an executable script based upon predetermined identifiers stored in a local storage medium; and the identification of an executable script based upon predetermined identifiers stored in a storage medium on a remote computing device. ### Claim 2 (depends on 1) The method of claim 1, wherein the classification of information transmitted to generate a dataset is based on the identification of an executable script using markers signifying the type of executable script. ### Claim 3 (depends on 1) The method of claim 1, wherein the weighted scoring system used to determine the probability that parameters contained in the dataset are present for device fingerprinting purposes relies on the entropy possessed by each parameter. ### Claim 4 (depends on 1) The method of claim 1, wherein the weighted scoring system used to determine the probability that parameters contained in the dataset are present for device fingerprinting purposes relies on the programmatic treatment of parameters requested. ### Claim 5 (depends on 1) The method of claim 1, wherein the weighted scoring system used to determine the probability that parameters contained in the dataset are present for device fingerprinting purposes relies on the relevance of the parameters in relation to the nature of the communications in which the parameters are identified. ### Claim 6 (depends on 1) The method of claim 1, wherein the weighted scoring system used to determine the probability that parameters contained in the dataset are present for device fingerprinting purposes relies on a determination that the source of the parameters is a known source of device fingerprinting attempts. ### Claim 7 (depends on 1) The method of claim 1, wherein the weighted scoring system is included in a database stored in a local storage medium. ### Claim 8 (depends on 1) The method of claim 1, wherein the weighted scoring system is included in a database stored in a stored medium on a remote computing device. ### Claim 9 A detection system for detecting attempts to collect parameters to create a device fingerprint, comprising: a computer program provided on a computing device having a processor and a non-transitory computer-readable medium and comprising one or more computer program instructions that when executed by said processor operate said detection system and cause the processor to perform a detection process, said computer program of said detection system comprising: a fingerprint detection module defined by said computer program instructions, said fingerprint detection module receiving information traversing a communications network and performing the steps of: identifying a subset of said information based on a classification of the information transmitted and generating a dataset from the subset of information for analysis to identify parameters used for device fingerprinting; determining a probability that parameters contained in said dataset are present for collecting information used for device fingerprinting based on analysis using a weighted scoring system; and returning a score that reflects the probability the parameters present in the dataset are present for device fingerprinting, wherein the score returned reflecting the probability that the parameters present in the dataset are present for device fingerprinting is stored in one of a local storage medium and a storage medium located on a remote computing device. ### Claim 10 A detection system provided on a computing device having a processor and a non-transitory computer-readable medium and comprising one or more instructions that when executed by said processor operate said detection system and cause the processor to perform a detection process, said detection system comprising: a fingerprint detection module operated by said processor which communicates with a communications network from which detection attempts are made, said fingerprint module receiving information traversing said communications network and performing the steps of: identifying a subset of said information based on a classification of transmitted information; generating a dataset from the subset of information for analysis to identify parameters used for device fingerprinting; determining the probability that parameters contained in said dataset are present for collecting information used for device fingerprinting based on analysis using a weighted scoring system; and returning a score that reflects the probability the parameters present in the dataset are present for device fingerprinting; wherein the weighted scoring system used to determine the probability that parameters contained in the dataset are present for device fingerprinting purposes relies on at least one of the entropy possessed by each parameter, the programmatic treatment of parameters requested, the relevance of the parameters in relation to the nature of the communications in which the parameters are identified, and a determination that the source of the parameters is a known source of device fingerprinting attempts. ### Claim 11 (depends on 10) The detection system of claim 10, wherein the instructions, when executed by the processor, classify the information transmitted to said fingerprint detection module generate said dataset based on the identification of an executable script using markers signifying the type of executable script. ### Claim 12 A detection system provided on a computing device having a processor and a non-transitory computer-readable medium and comprising one or more instructions that when executed by said processor operate said detection system and cause the processor to perform a detection process, said detection system comprising: a fingerprint detection module operated by said processor which communicates with a communications network from which detection attempts are made, said fingerprint module receiving information traversing said communications network and performing the steps of: identifying a subset of said information based on a classification of transmitted information, wherein said fingerprint detection module includes a parsing module which receives said transmitted information and identifies said subset of said transmitted information; generating a dataset from the subset of information for analysis to identify parameters used for device fingerprinting; determining the probability that parameters contained in said dataset are present for collecting information used for device fingerprinting based on analysis using a weighted scoring system; and returning a score that reflects the probability the parameters present in the dataset are present for device fingerprinting. ### Claim 13 (depends on 12) The detection system of claim 12, wherein said fingerprint detection module further including a heuristic detection module, and said parsing module generates said dataset which communicates said dataset to said heuristic detection module. ### Claim 14 (depends on 13) The detection system of claim 13, wherein said heuristic detection module determines the probability that parameters contained in said dataset are present for collecting information used for device fingerprinting based on analysis using a weighted scoring system. ### Claim 15 (depends on 14) The detection system of claim 14, wherein said heuristic detection module returns said score that reflects the probability the parameters present in the dataset are present for device fingerprinting. ### Claim 16 (depends on 12) The detection system of claim 12, wherein the classification of information transmitted to generate a dataset is based on the identification of an executable script using markers signifying the type of executable script. ### Claim 17 (depends on 10) The detection system of claim 10, wherein the weighted scoring system is included in at least one of a database stored in a local storage medium or a remote computing device.