Patents by Inventor Einaras von Gravrock
Einaras von Gravrock has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11902435Abstract: An access control server may store a private cryptographic key. The private cryptographic key corresponds to a public cryptographic key. The public cryptographic key is stored on a blockchain as part of an autonomous program protocol. The access control server may receive access control setting related to the autonomous program protocol. The access control server may receive a request for accessing the autonomous program protocol stored on the blockchain. The access control server may review the request. The access control server may determine the request is in compliance with the policies specified in the setting. The access control server may create, using the private cryptographic key, a digital signature for the request and generate a response including the digital signature. A successful verification of the digital signature using the public cryptographic key stored in the autonomous program protocol is required by the autonomous program protocol to process the request.Type: GrantFiled: November 9, 2022Date of Patent: February 13, 2024Assignee: CUBE Security Inc.Inventors: Attila Marosi-Bauer, Einaras von Gravrock, Sean Tiernan, Jonas Lekevicius
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Publication number: 20240031146Abstract: An access control server may store a private cryptographic key. The private cryptographic key corresponds to a public cryptographic key. The public cryptographic key is stored on a blockchain as part of an autonomous program protocol. The access control server may receive access control setting related to the autonomous program protocol. The access control server may receive a request for accessing the autonomous program protocol stored on the blockchain. The access control server may review the request. The access control server may determine the request is in compliance with the policies specified in the setting. The access control server may create, using the private cryptographic key, a digital signature for the request and generate a response including the digital signature. A successful verification of the digital signature using the public cryptographic key stored in the autonomous program protocol is required by the autonomous program protocol to process the request.Type: ApplicationFiled: November 9, 2022Publication date: January 25, 2024Inventors: Attila Marosi-Bauer, Einaras von Gravrock, Sean Tiernan, Jonas Lekevicius
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Patent number: 11303656Abstract: The behavior analysis engine can identify malicious entities based on connections between the entity and other entities. The behavior analysis engine receives an entity from the network traffic hub and identifies entities that are connected to the entity within a threshold degree of separation. The behavior analysis engine applies a recursive process to the entity whereby the behavior analysis engine determines whether an entity is malicious based on whether its connections within a threshold degree of separation are malicious. The behavior analysis engine uses the maliciousness of the entities' connections to determine whether the entity is malicious and, if the entity is malicious, the behavior analysis engine may instruct the network traffic hub to block network communications associated with the malicious entity.Type: GrantFiled: March 1, 2018Date of Patent: April 12, 2022Assignee: Cujo LLCInventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Patent number: 11303657Abstract: The behavior analysis engine can condense stored machine-learned models and transmit the condensed versions of the machine-learned models to the network traffic hub to be applied in the local networks. When the behavior analysis engine receives new data that can be used to further train a machine-learned model, the behavior analysis engine updates the machine-learned model and generates a condensed-version of the machine-learned model. The condensed-version of the machine-learned model may be more resource efficient than the machine-learned model while capable of making similar or the same decisions as the machine-learned model. The behavior analysis engine transmits the condensed version of the machine-learned model to the network traffic hub and the network traffic hub uses the condensed-version of the machine-learned model to identify malicious behavior in the local network.Type: GrantFiled: March 1, 2018Date of Patent: April 12, 2022Assignee: Cujo LLCInventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Patent number: 11277422Abstract: The behavior analysis engine can also detect malicious network addresses that are sent to networked devices in the local network. The network traffic hub identifies network communications that are transmitted through the local network that contain network addresses. The network traffic hub transmits (or sends) the network address to the behavior analysis engine and the behavior analysis engine extracts network address features from the network address. The behavior analysis engine then applies an execution model to the execution features to determine a confidence score for the network address that represents the execution model's certainty that the network address is malicious. The behavior analysis engine uses the confidence score to provide instructions to the network traffic hub as to whether to allow the networked device to receive the network address.Type: GrantFiled: March 1, 2018Date of Patent: March 15, 2022Assignee: Cujo LLCInventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Patent number: 11165798Abstract: The behavior analysis engine can also detect malicious network addresses that are sent to networked devices in the local network. The network traffic hub identifies network communications that are transmitted through the local network that contain network addresses. The network traffic hub transmits (or sends) the network address to the behavior analysis engine and the behavior analysis engine extracts network address features from the network address. The behavior analysis engine then applies an execution model to the execution features to determine a confidence score for the network address that represents the execution model's certainty that the network address is malicious. The behavior analysis engine uses the confidence score to provide instructions to the network traffic hub as to whether to allow the networked device to receive the network address.Type: GrantFiled: March 1, 2018Date of Patent: November 2, 2021Assignee: Cujo LLCInventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Patent number: 11153336Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: February 20, 2020Date of Patent: October 19, 2021Assignee: Cujo LLCInventors: Robert Beatty, Yuri Frayman, Einaras von Gravrock
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Patent number: 10819723Abstract: A network traffic hub is configured to receive a request for a port service (i.e., port forwarding or port triggering) from a smart appliance in a local network. The request may be a part of the UPnP protocol, which includes SSDP and IGDP. The request may be transmitted to the network traffic hub directly or the network traffic hub may intercept the request transmitted to a router of the local network. By receiving the request, the network traffic hub prevents automatic establishment of the port service between the smart appliance and the router until an approval or denial of the port service is received from a user. As such, the user is informed of the request and has the ability to approve or deny the port service. Furthermore, the network traffic hub can configure a network to perform a port service if the network does not allow for it natively.Type: GrantFiled: March 26, 2018Date of Patent: October 27, 2020Assignee: Cujo LLCInventors: Leonid Kuperman, Einaras von Gravrock
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Publication number: 20200195666Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: ApplicationFiled: February 20, 2020Publication date: June 18, 2020Inventors: Robert Beatty, Yuri Frayman, Einaras von Gravrock
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Patent number: 10609051Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: January 13, 2019Date of Patent: March 31, 2020Assignee: CUJO LLCInventors: Robert Beatty, Yuri Frayman, Einaras von Gravrock
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Patent number: 10567410Abstract: The behavior analysis engine detects malicious executable files that are being downloaded by networked devices in the local network by executing the executable files in a sandboxing environment operating on the behavior analysis engine. The network traffic hub identifies network communications that are transmitted through the local network that contain executable files. The network traffic hub sends the executable file to the behavior analysis engine and the behavior analysis engine executes the executable file in a sandboxing environment that replicates the networked device that was downloading the executable. The behavior analysis engine extracts execution features from the execution of the executable file and applies an execution model to the execution features to determine a confidence score for the executable file. The behavior analysis engine uses the confidence score to provide instructions to the network traffic hub as to whether to allow the networked device to download the executable.Type: GrantFiled: March 1, 2018Date of Patent: February 18, 2020Assignee: CUJO LLCInventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Patent number: 10560280Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and appliance identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: September 11, 2018Date of Patent: February 11, 2020Assignee: CUJO LLCInventors: Einaras von Gravrock, Yuri Frayman, Robert Beatty
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Publication number: 20190149563Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: ApplicationFiled: January 13, 2019Publication date: May 16, 2019Inventors: Robert Beatty, Yuri Frayman, Einaras von Gravrock
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Patent number: 10230740Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: November 20, 2015Date of Patent: March 12, 2019Assignee: Cujo LLCInventors: Robert Beatty, Yuri Frayman, Einaras von Gravrock
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Publication number: 20190013958Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and appliance identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: ApplicationFiled: September 11, 2018Publication date: January 10, 2019Inventors: Einaras von Gravrock, Yuri Frayman, Robert Beatty
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Patent number: 10135633Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and appliance identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: April 14, 2016Date of Patent: November 20, 2018Assignee: Cujo LLCInventors: Einaras von Gravrock, Yuri Frayman, Robert Beatty
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Patent number: 10103900Abstract: A method and system for detecting malicious behavior from smart appliances within a network. Smart appliances have a certain level of intelligence that allows them to perform a specific role more effectively and conveniently. Network traffic data and appliance identification data is collected about smart appliances within a network. The data is sent to a behavior analysis engine, which computes confidence levels for anomalies within the network traffic that may be caused by malicious behavior. If the behavior analysis engine determines that malicious behavior is present in the network, it sends an instruction to a network traffic hub to block network traffic relating to the anomaly. In some embodiments, network traffic is blocked based on source-destination pairs. In some embodiments, network traffic is blocked from a device outside the network that is determined to be malicious.Type: GrantFiled: April 14, 2016Date of Patent: October 16, 2018Assignee: Cujo LLCInventors: Einaras von Gravrock, Yuri Frayman, Robert Beatty
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Publication number: 20180278637Abstract: A network traffic hub is configured to receive a request for a port service (i.e., port forwarding or port triggering) from a smart appliance in a local network. The request may be a part of the UPnP protocol, which includes SSDP and IGDP. The request may be transmitted to the network traffic hub directly or the network traffic hub may intercept the request transmitted to a router of the local network. By receiving the request, the network traffic hub prevents automatic establishment of the port service between the smart appliance and the router until an approval or denial of the port service is received from a user. As such, the user is informed of the request and has the ability to approve or deny the port service. Furthermore, the network traffic hub can configure a network to perform a port service if the network does not allow for it natively.Type: ApplicationFiled: March 26, 2018Publication date: September 27, 2018Inventors: Leonid Kuperman, Einaras von Gravrock
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Publication number: 20180255086Abstract: The behavior analysis engine can condense stored machine-learned models and transmit the condensed versions of the machine-learned models to the network traffic hub to be applied in the local networks. When the behavior analysis engine receives new data that can be used to further train a machine-learned model, the behavior analysis engine updates the machine-learned model and generates a condensed-version of the machine-learned model. The condensed-version of the machine-learned model may be more resource efficient than the machine-learned model while capable of making similar or the same decisions as the machine-learned model. The behavior analysis engine transmits the condensed version of the machine-learned model to the network traffic hub and the network traffic hub uses the condensed-version of the machine-learned model to identify malicious behavior in the local network.Type: ApplicationFiled: March 1, 2018Publication date: September 6, 2018Inventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs
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Publication number: 20180253550Abstract: The behavior analysis engine detects malicious executable files that are being downloaded by networked devices in the local network by executing the executable files in a sandboxing environment operating on the behavior analysis engine. The network traffic hub identifies network communications that are transmitted through the local network that contain executable files. The network traffic hub sends the executable file to the behavior analysis engine and the behavior analysis engine executes the executable file in a sandboxing environment that replicates the networked device that was downloading the executable. The behavior analysis engine extracts execution features from the execution of the executable file and applies an execution model to the execution features to determine a confidence score for the executable file. The behavior analysis engine uses the confidence score to provide instructions to the network traffic hub as to whether to allow the networked device to download the executable.Type: ApplicationFiled: March 1, 2018Publication date: September 6, 2018Inventors: Leonid Kuperman, Yuri Frayman, Einaras von Gravrock, Gabor Takacs