# US 11,310,033 B2 · System and method for operating pseudorandom generators > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,310,033 B2 - Document ID: US11310033B2 - Status: Granted - Kind: B2 - Application number: 16/431,845 - Filed: 2019-06-05 - Published: 2020-12-10 - Granted: 2022-04-19 - Earliest claimed: 2019-06-05 - Assignees: BlackBerry Limited - Applicants: Certicom Corp. - Inventors: Robert John Lambert; Nevine Maurice Nassif Ebeid; Daniel Richard L. Brown; Atsushi Yamada - Web page: https://patentgrep.com/patent/US11310033B2 ## CPC - H04L 9/0662: {with particular pseudorandom sequence generator} - H04L 9/0668: {producing a non-linear pseudorandom sequence} - G06F 7/58: Random or pseudo-random number generators - G06F 7/582: {Pseudo-random number generators} - H03M 7/3059: {Digital compression and data reduction techniques where the original information is represented by a subset or similar information, e.g. lossy compression} - H04L 9/0643: {Hash functions, e.g. MD5, SHA, HMAC or f9 MAC} - H04L 9/0869: {involving random numbers or seeds} - H04W 12/60: Context-dependent security - 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) - H03M: CODING; DECODING; CODE CONVERSION IN GENERAL (using fluidic means F15C4/00; optical analogue/digital converters G02F7/00; coding, decoding or code conversion, specially adapted for particular applications, see the relevant subclasses, e.g. G01D, G01R, G06F, G06T, G09G, G10L, G11B, G11C, H04B, H04L, H04M, H04N; ciphering or deciphering for cryptography or other purposes involving the need for secrecy G09C) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract A method for operating a pseudorandom generator is disclosed. The method may be implemented by a processor of a mobile computing device. The method includes: collecting raw sensor data from at least one sensor associated with the mobile computing device; selecting a subset of the raw sensor data; retrieving first representation representing accumulated entropy associated with one or more previously acquired raw sensor data sets for the at least one sensor; and generating a seed for a pseudorandom generator based on combining the first representation and the selected subset of raw sensor data. ## Claims ### Claim 1 A method for processing raw sensor data of sensors associated with a mobile computing device, the method comprising: collecting raw sensor data from at least one sensor associated with the mobile computing device; selecting a subset of the raw sensor data based on: compressing the raw sensor data using a lossy compression technique to obtain a lossy compressed sensor data output; and selecting, for inclusion in the subset, one or more bits from a data bit stream associated with the at least one sensor that are not included in the lossy compressed sensor data output; applying a one-way cryptographic compression on the selected subset to obtain a compressed value; retrieving a first representation of accumulated entropy associated with one or more previously acquired raw sensor data sets for the at least one sensor; and generating an updated current representation of accumulated entropy based on combining the first representation and the compressed value. ### Claim 2 (depends on 1) The method of claim 1, wherein the first representation comprises a first bit string and wherein generating the updated current representation comprises obtaining a second bit string based on the first bit string. ### Claim 3 (depends on 1) The method of claim 1, wherein applying the one-way cryptographic compression on the selected subset comprises applying a cryptographic hash function on the selected subset. ### Claim 4 (depends on 3) The method of claim 3, wherein combining the first representation and the compressed value comprises applying at least one of “exclusive or”, addition, subtraction, or scaling operations to the first representation and the compressed value. ### Claim 5 (depends on 1) The method of claim 1, further comprising initializing the first representation to a static value. ### Claim 6 (depends on 1) The method of claim 1, further comprising updating the first representation to incorporate the generated updated current representation. ### Claim 7 (depends on 1) The method of claim 1, wherein selecting the subset of the raw sensor data comprises selecting a fixed fraction of a predefined number of low order bits of a data bit stream associated with the at least one sensor. ### Claim 8 A mobile computing device, comprising: at least one sensor; memory; and a processor coupled with the at least one sensor and the memory, the processor being configured to: collect raw sensor data from at least one sensor associated with the mobile computing device; select a subset of the raw sensor data based on: compression of the raw sensor data using a lossy compression technique to obtain a lossy compressed sensor data output; and selection, for inclusion in the subset, of one or more bits from a data bit stream associated with the at least one sensor that are not included in the lossy compressed sensor data output; apply a one-way cryptographic compression on the selected subset to obtain a compressed value; retrieve a first representation of accumulated entropy associated with one or more previously acquired raw sensor data sets for the at least one sensor; and generate an updated current representation of accumulated entropy based on combining the first representation and the compressed value. ### Claim 9 (depends on 8) The mobile computing device of claim 8, wherein the first representation is represented by a first bit string and wherein generating the updated current representation comprises obtaining a second bit string based on the first bit string. ### Claim 10 (depends on 8) The mobile computing device of claim 8, wherein applying the one-way cryptographic compression on the selected subset comprises applying a cryptographic hash function on the selected subset. ### Claim 11 (depends on 10) The mobile computing device of claim 10, wherein combining the first representation and the compressed value comprises applying at least one of “exclusive or”, addition, subtraction, or scaling operations to the first representation and the compressed value. ### Claim 12 (depends on 8) The mobile computing device of claim 8, wherein the processor is further configured to initialize the first representation to a static value. ### Claim 13 (depends on 8) The mobile computing device of claim 8, wherein the processor is further configured to update the first representation to incorporate the generated updated current representation. ### Claim 14 (depends on 8) The mobile computing device of claim 8, wherein selecting the subset of the raw sensor data comprises selecting a fixed fraction of a predefined number of low order bits of a data bit stream associated with the at least one sensor. ### Claim 15 A non-transitory, computer readable medium storing instructions that, when executed by a processor, cause the processor to: collect raw sensor data from at least one sensor associated with the mobile computing device; select a subset of the raw sensor data based on: compression of the raw sensor data using a lossy compression technique to obtain a lossy compressed sensor data output; and selection, for inclusion in the subset, of one or more bits from a data bit stream associated with the at least one sensor that are not included in the lossy compressed sensor data output; apply a one-way cryptographic compression on the selected subset to obtain a compressed value; retrieve a first representation of accumulated entropy associated with one or more previously acquired raw sensor data sets for the at least one sensor; and generate an updated current representation of accumulated entropy based on combining the first representation and the compressed value. ### Claim 16 (depends on 15) The computer readable medium of claim 15, wherein the first representation comprises a first bit string and wherein generating the updated current representation comprises obtaining a second bit string based on the first bit string. ### Claim 17 (depends on 15) The computer readable medium of claim 15, wherein applying the one-way cryptographic compression on the selected subset comprises applying a cryptographic hash function on the selected subset. ### Claim 18 (depends on 17) The computer readable medium of claim 17, wherein combining the first representation and the compressed value comprises applying at least one of “exclusive or”, addition, subtraction, or scaling operations to the first representation and the compressed value. ### Claim 19 (depends on 15) The computer readable medium of claim 15, wherein the instructions, when executed, further cause the processor to update the first representation to incorporate the generated updated current representation. ### Claim 20 (depends on 15) The computer readable medium of claim 15, wherein selecting the subset of the raw sensor data comprises selecting a fixed fraction of a predefined number of low order bits of a data bit stream associated with the at least one sensor.