# US 2016/0366164 A1 · Network intrusion data item clustering and analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2016/0366164 A1 - Document ID: US20160366164A1 - Status: Published application - Kind: A1 - Application number: 14/487,021 - Filed: 2014-09-15 - Published: 2016-12-15 - Earliest claimed: 2014-07-03 - Assignees: Palantir Technologies Inc. - Applicants: Palantir Technologies Inc. - Inventors: David Cohen; Jason Ma; Bing Jie Fu; Ilya Nepomnyashchiy; Steven Berler; Alex Smaliy; Jack Grossman; James Thompson; Julia Boortz; Matthew Sprague; Parvathy Menon; Michael Kross; Michael Harris; Adam Borochoff - Web page: https://patentgrep.com/patent/US20160366164A1 ## CPC - H04L 63/1425: {Traffic logging, e.g. anomaly detection} - G06F 16/285: {Clustering or classification} - G06Q 40/12: Accounting - H04L 63/1408: {by monitoring network traffic (monitoring network traffic per se H04L43/00)} - H04L 63/145: {the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms} - 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) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyses (also referred to herein as “summaries” or “conclusions”) of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures. ## Claims ### Claim 1 A computer system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; a data clustering strategy; and a plurality of data items including at least: intrusion detection system reports, each intrusion detection system report associated with at least a source Internet Protocol address and a destination Internet Protocol address; and network-related data items associated with captured communications between an internal network and an external network, the network-related data items including at least one of: external Internet Protocol addresses, external domains, external computerized devices, internal Internet Protocol addresses, internal computerized devices, users of particular computerized devices, intrusion detection system information, network firewall data, or WHOIS information; and one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an intrusion detection system report including a communication between a source Internet Protocol address and a destination Internet Protocol address; initiate an automated lookup to determine which of the source Internet Protocol address and the destination Internet Protocol address is an external Internet Protocol address, the external Internet Protocol address being external to the internal network; designate the external Internet Protocol address as a seed; and generate a data item cluster based on the data clustering strategy by at least: adding the seed to the data item cluster; identifying one or more of the network-related data items associated with the seed; and adding, to the data item cluster, the one or more identified network-related data items. ### Claim 2 (depends on 1) The computer system of claim 1, wherein generating the data item cluster based on the data clustering strategy further comprises: identifying additional one or more data items associated with any data items of the data item cluster; and adding, to the data item cluster, the additional one or more data items. ### Claim 3 (depends on 1) The computer system of claim 1, wherein the data item cluster includes at least the source Internet Protocol address, the destination Internet Protocol address, an internal computerized device associated with an Internet Protocol address in the cluster, a user of the internal computerized device, and WHOIS information associated with the external Internet Protocol address. ### Claim 4 (depends on 1) The computer system of claim 1, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to: receive a second intrusion detection system report including a communication between a second source Internet Protocol address and a second destination Internet Protocol address; initiate an automated lookup to determine which of the second source Internet Protocol address and the second destination Internet Protocol address is a second external Internet Protocol address, the second external Internet Protocol address being external to the internal network; compare the external Internet Protocol address to the second external Internet Protocol address; in response to determining, based on the comparison, that the external Internet Protocol address and the second external Internet Protocol address are the same, add the second external Internet Protocol address to the data item cluster; and in response to determining, based on the comparison, that the external Internet Protocol address and the second external Internet Protocol address are not the same: designate the second external Internet Protocol address as a second seed; and generate a second data item cluster based on the data clustering strategy and the second seed. ### Claim 5 (depends on 4) The computer system of claim 4, wherein the second external Internet Protocol address is added to the data item cluster only if the intrusion detection system report and the second intrusion detection system report are received on a same day. ### Claim 6 (depends on 1) The computer system of claim 1, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to: scan communications between the internal network and the external network so as to generate additional network-related data items; and store the additional network-related data items in the one or more computer readable storage devices. ### Claim 7 (depends on 1) The computer system of claim 1, wherein received intrusion detection system reports are automatically stored in the one or more computer readable storage devices, and the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to: identify newly received intrusion detection system reports; initiate automated lookups to determine external Internet Protocol addresses associated with each of the newly received intrusion detection system reports; designate the determined external Internet Protocol addresses as seeds; and generate data item clusters based on the data clustering strategy and the seeds. ### Claim 8 (depends on 7) The computer system of claim 7, wherein data item clusters generated based on common external Internet Protocol addresses are merged. ### Claim 9 (depends on 8) The computer system of claim 8, wherein data item clusters generated based on common external Internet Protocol addresses are merged only if the associated intrusion detection system reports are received on a same day. ### Claim 10 (depends on 1) The computer system of claim 1, wherein: the one or more computer readable storage devices are further configured to store: a plurality of data cluster analysis rules associated with the data clustering strategy, and the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the one or more hardware computer processors to: for the generated data item cluster: access the plurality of data cluster analysis rules associated with the data clustering strategy; analyze the data item cluster based on the accessed data cluster analysis rules; and based on the analysis of the data item cluster: determine an alert score for the data item cluster; and generate one or more human-readable conclusions regarding the data item cluster. ### Claim 11 (depends on 10) The computer system of claim 10, wherein the alert score indicates a degree of correlation between characteristics of the data item cluster and the accessed data cluster analysis rules. ### Claim 12 (depends on 11) The computer system of claim 11, wherein the degree of correlation is based on both an assessment of risk associated with the particular data cluster and a confidence level in accuracy of the assessment of risk. ### Claim 13 (depends on 11) The computer system of claim 11, wherein a relatively higher alert score indicates a data cluster that is relatively more important for a human analyst to evaluate, and a relatively lower alter score indicated a data cluster that is relatively less important for the human analyst to evaluate. ### Claim 14 (depends on 11) The computer system of claim 11, wherein each alert score for respective data clusters is assigned to a category indicating a high degree of correlation, a medium degree of correlation, or a low degree of correlation. ### Claim 15 (depends on 14) The computer system of claim 14, wherein the high degree of correlation is associated with a first color, the medium degree of correlation is associated with a second color, and the low degree of correlation is associated with a third color. ### Claim 16 (depends on 10) The computer system of claim 10, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the computer system to: for the generated data item cluster: generate an alert, the alert comprising a the alert score, the one or more human-readable conclusions, the data items associated with the data item cluster, and metadata associated with the data items of the data item cluster. ### Claim 17 (depends on 16) The computer system of claim 16, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the computer system to: generate a user interface including a list of user-selectable alert indicators, an alert indicator being provided for each of the generated alerts, each of the alert indicators providing a summary of information associated with respective generated alerts. ### Claim 18 (depends on 17) The computer system of claim 17, wherein the one or more hardware computer processors are further configured to execute the plurality of computer executable instructions in order to cause the computer system to: in response to a selection of an alert indicator by a human analyst: generate an alert display, the alert display including at least an indication of the alert score and a list of the one or more human-readable conclusions. ### Claim 19 (depends on 10) The computer system of claim 10, wherein the one or more human-readable conclusions each comprise a phrase or sentence including one or more indications of summary or aggregated data associated with a plurality of the data items of the data item cluster. ### Claim 20 (depends on 19) The computer system of claim 19, wherein generating the one or more human-readable conclusions comprises: selecting, based on the data cluster type associated with the particular data cluster, one or more conclusion templates; and populating the one or more conclusion templates with data associated with the particular data cluster.