# US 10,372,731 B1 · Method of generating a data object identifier and system thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,372,731 B1 - Document ID: US10372731B1 - Status: Granted - Kind: B1 - Application number: 15/360,612 - Filed: 2016-11-23 - Granted: 2019-08-06 - Earliest claimed: 2015-11-25 - Assignees: Minereye Ltd. - Applicants: Minereye Ltd. - Inventors: Yaniv Avidan; Avner Atias - Web page: https://patentgrep.com/patent/US10372731B1 ## CPC - G06F 16/285: {Clustering or classification} - G06F 16/2219: {Large Object storage; Management thereof} - G06F 16/2237: {Vectors, bitmaps or matrices} - G06F 16/2264: {Multidimensional index structures} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Generating a data object identifier by dividing the data in the data object into a plurality of chunks; processing each chunk using a clustering algorithm to generate, for each chunk, a pair of values characterizing the data in the chunk, thereby giving rise to a plurality of pairs of values (PoV); generating a plurality of nodes in a two dimensional space each corresponding to a respective PoV, wherein, for any given PoV, the values in the given PoV are indicative of location coordinates of the corresponding node in the two dimensional space; generating a plurality of features related to the plurality of nodes, each feature characterizing a spatial relationship between three or more nodes; and generating the data object identifier by arranging the features in a feature vector in accordance with predetermined rules. ## Claims ### Claim 1 A method of generating a data object identifier, the method executed by a computer and comprising: upon receiving a data object, dividing the data in the data object into a plurality of chunks; processing each chunk using a clustering algorithm to generate, for each chunk, a pair of values characterizing the data in the chunk, thereby giving rise to a plurality of pairs of values (PoV); generating a plurality of nodes in a two dimensional space each corresponding to a respective PoV, wherein, for any given PoV, the values in the given PoV are indicative of location coordinates of the corresponding node in the two dimensional space; generating a plurality of features related to the plurality of nodes, each feature characterizing a spatial relationship between three or more nodes; and generating the data object identifier by arranging the features in a feature vector in accordance with predetermined rules, wherein the generated data object identifier is usable for detecting similarity with other data objects whereby a level of accuracy of the detecting is increased. ### Claim 2 (depends on 1) The method of claim 1 wherein the data object is a file. ### Claim 3 (depends on 1) The method of claim 1 wherein the data is divided into chunks using a predetermined value n indicative of a maximum chunk size. ### Claim 4 (depends on 1) The method of claim 1 wherein the PoV for a chunk is generated by processing the data in the chunk using a clustering algorithm. ### Claim 5 (depends on 4) The method of claim 4 wherein the clustering algorithm is a self-organizing map algorithm. ### Claim 6 (depends on 1) The method of claim 1 wherein for each node, the first value in the PoV corresponding to the node defines the x-axis coordinate in the two dimensional space and the second value in the PoV corresponding to the node defines the y-axis coordinate in the two dimensional space. ### Claim 7 (depends on 1) The method of claim 1 wherein the spatial relationship comprises at least one of i) an angle formed between a node and two other nodes, and ii) a distance ratio between a given node and two other nodes. ### Claim 8 (depends on 1) The method of claim 1, wherein detecting similarity with other data objects is usable for at least one of: detecting sensitive data in the data object; identifying data objects with similar data; discovering data objects with duplicate data; identifying instances of the data object sharing. ### Claim 9 A system capable of generating a data object identifier comprising a processor and memory block operatively coupled to one or more data repositories, the processor and memory block configured to: upon receiving a data object stored on the one or more data repositories, divide the data in the data object into a plurality of chunks; process each chunk using a clustering algorithm to generate, for each chunk, a pair of values characterizing the data in the chunk, thereby giving rise to a plurality of pairs of values (PoV); generate a plurality of nodes in a two dimensional space each corresponding to a respective PoV, wherein, for any given PoV, the values in the given PoV are indicative of location coordinates of the corresponding node in the two dimensional space; generate a plurality of features related to the plurality of nodes, each feature characterizing a spatial relationship between three or more nodes; and generate the data object identifier by arranging the features in a feature vector in accordance with predetermined rules, wherein the generated data object identifier is usable for detecting similarity with other data objects whereby a level of accuracy of the detecting is increased. ### Claim 10 (depends on 9) The system of claim 9 wherein the data object is a file. ### Claim 11 (depends on 9) The system of claim 9 wherein the data is divided into chunks using a predetermined value n indicative of a maximum chunk size. ### Claim 12 (depends on 9) The system of claim 9 wherein the PoV for a chunk is generated by processing the data in the chunk using a clustering algorithm. ### Claim 13 (depends on 12) The system of claim 12 wherein the clustering algorithm is a self-organizing map algorithm. ### Claim 14 (depends on 9) The system of claim 9 wherein for each node, the first value in the PoV corresponding to the node defines the x-axis coordinate in the two dimensional space and the second value in the PoV corresponding to the node defines the y-axis coordinate in the two dimensional space. ### Claim 15 (depends on 9) The system of claim 9 wherein the spatial relationship comprises at least one of i) an angle formed between a node and two other nodes, and ii) a distance ratio between a given node and two other nodes. ### Claim 16 (depends on 9) The system of claim 9, wherein detecting similarity with other data objects is usable for at least one of: detecting sensitive data in the data object; identifying data objects with similar data; discovering data objects with duplicate data; identifying instances of the data object sharing. ### Claim 17 A non-transitory computer-readable memory tangibly embodying a program of instructions executable by a computer for executing a method of generating a data object identifier, the method comprising: upon receiving a data object, dividing the data in the data object into a plurality of chunks; processing each chunk using a clustering algorithm to generate, for each chunk, a pair of values characterizing the data in the chunk, thereby giving rise to a plurality of pairs of values (PoV); generating a plurality of nodes in a two dimensional space each corresponding to a respective PoV, wherein, for any given PoV, the values in the given PoV are indicative of location coordinates of the corresponding node in the two dimensional space; generating a plurality of features related to the plurality of nodes, each feature characterizing a spatial relationship between three or more nodes; and generating the data object identifier by arranging the features in a feature vector in accordance with predetermined rules, wherein the generated data object identifier is usable for automated detecting similarity with other data objects whereby a level of accuracy of the detecting is increased.