# US 10,122,695 B2 · Remote crowd attestation in a network > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,122,695 B2 - Document ID: US10122695B2 - Status: Granted - Kind: B2 - Application number: 14/924,799 - Filed: 2015-10-28 - Published: 2017-05-04 - Granted: 2018-11-06 - Earliest claimed: 2015-10-28 - Assignees: Cisco Technology, Inc. - Applicants: Cisco Technology, Inc. - Inventors: Tao Zhang; Yi Zheng; Helder F. Antunes; Marcelo Yannuzzi; Gonzalo Salgueiro; Joseph Michael Clarke - Web page: https://patentgrep.com/patent/US10122695B2 ## CPC - H04L 63/08: {for authentication of entities (cryptographic mechanisms or cryptographic arrangements for entity authentication H04L9/32)} - H04L 63/123: {received data contents, e.g. message integrity} - H04L 63/126: {the source of the received data} - H04W 12/102: Route integrity, e.g. using trusted paths - H04L 63/0823: {using certificates (cryptographic mechanisms or cryptographic arrangements for entity authentication involving certificates H04L9/3263)} - H04W 4/70: Services for machine-to-machine communication [M2M] or machine type communication [MTC] - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract In one embodiment, a first device in a network receives information regarding one or more nodes in the network. The first device determines a property of the one or more nodes based on the received information. The first device determines a degree of trustworthiness of the one or more nodes based on the received information. The first device attests to the determined property and degree of trustworthiness of the one or more nodes to a verification device. The verification device is configured to verify the attested property and degree of trustworthiness. ## Claims ### Claim 1 A method, comprising: receiving, at a first device in a network, information regarding plurality of nodes in the network, wherein the network is an implementation of Low-Power and Lossy Networks (LLNs); determining, by the first device, a property of the one or plurality of nodes based on the received information, wherein the property of the plurality of nodes comprises at least one of: a hardware configuration, a software configuration, a physical location, or a traffic pattern of the one or more nodes; observing, by the first device, a behavior of the plurality of nodes; constructing, by the first device, a behavioral model based on the observed behavior; determining, by the first device, a degree of trustworthiness of the plurality of nodes based on the received information by comparing the determined property to the behavioral model; ensuring, by the first device, a degree of trustworthiness of the observed behavior; and attesting, by the first device, to the determined property and degree of trustworthiness of the plurality of nodes to a verification device, wherein the verification device is configured to verify the attested property and degree of trustworthiness as part of a hierarchy of attester devices in the network. ### Claim 2 (depends on 1) The method as in claim 1, wherein the verification device is further configured to attest to the property and degree of trustworthiness of the plurality of nodes to a higher level attester device in the hierarchy. ### Claim 3 (depends on 1) The method as in claim 1, wherein the behavioral model was constructed by the first device while in a learning mode. ### Claim 4 (depends on 1) The method as in claim 1, wherein the behavioral model comprises an inferred finite state machine (FSM) that models the observed behavior of the plurality of nodes. ### Claim 5 (depends on 1) The method as in claim 1, further comprising: selecting, by the first device, the plurality of nodes based on a security policy, wherein the security policy identifies a set of trusted device types. ### Claim 6 (depends on 1) The method of claim 1, further comprising: comparing the received information regarding the plurality of nodes to a history of information regarding the plurality of nodes. ### Claim 7 An apparatus, comprising: one or more network interfaces to communicate with a network; a processor coupled to the network interfaces and configured to execute one or more processes; and a memory configured to store a process executable by the processor, the process when executed configured to: receive information regarding a plurality of one or more nodes in the network, wherein the network is an implementation of Low-Power and Lossy Networks (LLNs); determine a property of the plurality of nodes based on the received information, wherein the property of the plurality of nodes comprises at least one of: a hardware configuration, a software configuration, a physical location, or a traffic pattern of the one or more nodes; observe a behavior of the plurality of nodes; construct a behavioral model based on the observed behavior; determine a degree of trustworthiness of the plurality of nodes based on the received information by comparing the determined property to the behavioral model; ensure a degree of trustworthiness of the observed behavior; and attest to the determined property and degree of trustworthiness of the plurality of nodes to a verification device, wherein the verification device is configured to verify the attested property and degree of trustworthiness as part of a hierarchy of attester devices in the network. ### Claim 8 (depends on 7) The apparatus as in claim 7, wherein the verification device is further configured to attest to the property and degree of trustworthiness of the plurality of one or more nodes to a higher level attester device in the hierarchy. ### Claim 9 (depends on 8) The apparatus as in claim 8, wherein the behavioral model was constructed by the first device while in a learning mode. ### Claim 10 (depends on 7) The apparatus as in claim 7, wherein the behavioral model comprises an inferred finite state machine (FSM) that models the observed behavior of the plurality of nodes. ### Claim 11 (depends on 7) The apparatus as in claim 7, wherein the process when executed is further configured to: select the plurality of nodes based on a security policy, wherein the security policy identifies a set of trusted device types. ### Claim 12 (depends on 7) The apparatus as in claim 7, wherein the process when executed is further configured to: compare the received information regarding the plurality of nodes to a history of information regarding the plurality of nodes. ### Claim 13 A tangible, non-transitory, computer-readable media having software encoded thereon, the software when executed by a processor configured to: receive information regarding plurality of nodes in the network, wherein the network is an implementation of Low-Power and Lossy Networks (LLNs); determine a property of the plurality of nodes based on the received information, wherein the property of the plurality of nodes comprises at least one of: a hardware configuration, a software configuration, a physical location, or a traffic pattern of the plurality of nodes; observe a behavior of the plurality of nodes; construct a behavioral model based on the observed behavior; determine a degree of trustworthiness of the plurality of nodes based on the received information by comparing the determined property to the behavioral model; ensure a degree of trustworthiness of the observed behavior; and attest to the determined property and degree of trustworthiness of the plurality of nodes to a verification device, wherein the verification device is configured to verify the attested property and degree of trustworthiness as part of a hierarchy of attester devices in the network. ### Claim 14 (depends on 13) The computer-readable media as in claim 13, wherein the verification device is further configured to attest to the property and degree of trustworthiness of the plurality of nodes to a higher level attester device in the hierarchy. ### Claim 15 (depends on 13) The computer-readable media as in claim 13, wherein the behavioral model was constructed by the first device while in a learning mode. ### Claim 16 (depends on 13) The computer-readable media as in claim 13, wherein the behavioral model comprises an inferred finite state machine (FSM) that models the observed behavior of the plurality of nodes. ### Claim 17 (depends on 13) The computer-readable media as in claim 13, wherein the software when executed by the processor is further configured to: select the plurality of nodes based on a security policy, wherein the security policy identifies a set of trusted device types. ### Claim 18 (depends on 13) The computer-readable media of claim 13, wherein the software when executed by the processor is further configured to: compare the received information regarding the plurality of nodes to a history of information regarding the plurality of nodes.