Peraton Labs Inc.

United States of America

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IPC Class
H04L 9/40 - Network security protocols 3
G06N 3/08 - Learning methods 2
H04B 7/08 - Diversity systemsMulti-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station 2
H04L 27/26 - Systems using multi-frequency codes 2
H04L 41/08 - Configuration management of networks or network elements 2
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Found results for  patents

1.

Verification and synthesis of cyber physical systems with machine learning and constraint-solver-driven learning

      
Application Number 16713779
Grant Number 12147900
Status In Force
Filing Date 2019-12-13
First Publication Date 2024-06-20
Grant Date 2024-11-19
Owner Peraton Labs Inc. (USA)
Inventor
  • Narain, Sanjai
  • Mak, Emily Chun

Abstract

In a computer-implemented method, computer program product, and computer system, program code executing on a processor(s) generates input-output pairs, to form a training set for machine learning and generates a machine learning model of a cyber physical system by utilizing a machine learning algorithm and the training set to train the machine learning model. The program code converts the trained machine learning model into an equivalent constraint and optimizes objective functions subject to the constraint by utilizing one or more constraint solvers to compute an input-output pair. The program code determines if the computed input-output pair, is within an error tolerance and based on determining that it is, either utilizes it as a solution or adds it to the training set (and continues training). If the pair is not within the tolerance, the program code utilizes it as a solution or adds it to the training set (and continues training).

IPC Classes  ?

  • G06N 3/08 - Learning methods
  • G06N 3/082 - Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections

2.

Adaptive radio frequency communication

      
Application Number 18502860
Grant Number 12289191
Status In Force
Filing Date 2023-11-06
First Publication Date 2024-02-29
Grant Date 2025-04-29
Owner PERATON LABS INC. (USA)
Inventor
  • Johnson, William
  • Rege, Kiran
  • Kogiantis, Achilles

Abstract

There is set forth herein, in one embodiment, receiving, by a transceiver of a UE device an aggregate signal stream, the aggregate signal stream including an aggregate of base station downlink signal streams from a plurality of base stations; and processing the aggregate signal stream.

IPC Classes  ?

  • H04L 27/26 - Systems using multi-frequency codes
  • H04B 7/08 - Diversity systemsMulti-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
  • H04W 48/16 - DiscoveringProcessing access restriction or access information

3.

Common-mode signaling and coupler bypass in legacy busses

      
Application Number 17351890
Grant Number 11880320
Status In Force
Filing Date 2021-06-18
First Publication Date 2024-01-23
Grant Date 2024-01-23
Owner PERATON LABS INC. (USA)
Inventor
  • Dixon, James
  • Banwell, Thomas
  • Robertson, Seth
  • Porter, Frederick

Abstract

A system and method of adding a high-rate channel to a legacy baseband bus includes a bus communicatively coupled to a transmitter and a receiver via one or more transformer couplers, where the transmitter and receiver transmit and receive a first signal over the bus utilizing a differential mode. The system also includes at least two modems coupled to the bus, where a first modem transmits a second signal over the bus for receipt by a second modem, where the at least two modems are each coupled to the bus via the one or more transformer couplers, where the second signal is transmitted over the bus utilizing a common mode, and where the first signal and the second signal are spatially separated on the bus based on an isolation between the common mode and the differential mode.

IPC Classes  ?

  • G06F 13/36 - Handling requests for interconnection or transfer for access to common bus or bus system

4.

Highspeed shared-memory optical network interfaces and topology

      
Application Number 17228491
Grant Number 11698878
Status In Force
Filing Date 2021-04-12
First Publication Date 2023-07-11
Grant Date 2023-07-11
Owner Peraton Labs Inc. (USA)
Inventor
  • Douglis, Frederick
  • Robertson, Seth
  • Van Den Berg, Eric

Abstract

Examples herein include a computer system and methods. Some computer systems comprise two or more devices (each device comprises at least one processing circuit), where each computing device comprises or is communicatively coupled to one or more optical network interface controller (O-NIC) cards. Each O-NIC card comprises at least two bidirectional optical channels to transmit data and to receive additional data from each O-NIC card communicatively coupled to a device, over a channel. The system also includes one or more interfaces and a memory. Program instructions execute a method on one or more processors in communication with a memory, and the method includes modifying, during runtime of at least one application, a pairing over a given bidirectional optical channel of an interface of the interfaces to a given device.

IPC Classes  ?

  • G06F 13/40 - Bus structure
  • G06F 13/38 - Information transfer, e.g. on bus
  • G06F 13/42 - Bus transfer protocol, e.g. handshakeSynchronisation
  • G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
  • G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation

5.

Migration of traffic flows

      
Application Number 18055209
Grant Number 12081573
Status In Force
Filing Date 2022-11-14
First Publication Date 2023-03-09
Grant Date 2024-09-03
Owner Peraton Labs Inc. (USA)
Inventor
  • Kaplan, Michael
  • Shur, David
  • Kaul, Vikram
  • Bowen, Thomas

Abstract

There is set forth herein obtaining data traffic monitoring data, the data traffic monitoring data being in dependence on monitoring of traffic received by a container of a protected computing environment; obtaining data traffic monitoring data, the data traffic monitoring data being in dependence on monitoring of traffic received by a processing resource of a computing environment; obtaining a state of the processing resource and provisioning a utility processing resource to include the state of the processing resource; and configuring the computing environment to route data traffic to the utility processing resource.

IPC Classes  ?

  • H04L 9/40 - Network security protocols
  • H04L 41/08 - Configuration management of networks or network elements
  • H04L 41/0806 - Configuration setting for initial configuration or provisioning, e.g. plug-and-play
  • H04L 43/062 - Generation of reports related to network traffic
  • H04L 43/08 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
  • H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
  • H04L 45/00 - Routing or path finding of packets in data switching networks
  • H04L 47/00 - Traffic control in data switching networks
  • H04L 41/082 - Configuration setting characterised by the conditions triggering a change of settings the condition being updates or upgrades of network functionality
  • H04L 43/16 - Threshold monitoring

6.

Anomaly detection based on side-channel emanations

      
Application Number 17101592
Grant Number 11487875
Status In Force
Filing Date 2020-11-23
First Publication Date 2022-11-01
Grant Date 2022-11-01
Owner Peraton Labs Inc. (USA)
Inventor
  • Alexander, Scott
  • Micallef, Josephine
  • Morman, Joshua
  • Panagos, Euthimios
  • Pucci, Marc
  • Tsang, Simon

Abstract

A computer program product, a computer-implemented method, and a computer system include a processor(s) that obtains side channel emanations from a device. The processor(s) analyzes the side channel emanations to identify distinct emanation patterns and timing characteristics, wherein the timing characteristics are associated with transitions between the distinct emanation patterns. The processor(s) generates a non-deterministic finite automaton (NFA) by correlating the distinct emanation patterns with states of the device, where the NFA captures states and state transitions of the device. The processor(s) identifies an anomaly in the device, based on deviation in emanations from the device.

IPC Classes  ?

  • G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
  • G06F 21/55 - Detecting local intrusion or implementing counter-measures

7.

Adaptive radio frequency communication

      
Application Number 17249590
Grant Number 12034582
Status In Force
Filing Date 2021-03-05
First Publication Date 2022-09-08
Grant Date 2024-07-09
Owner Peraton Labs Inc. (USA)
Inventor
  • Johnson, William
  • Rege, Kiran
  • Kogiantis, Achilles

Abstract

There is set forth herein, in one embodiment, receiving, by a transceiver of a UE device an aggregate signal stream, the aggregate signal stream including an aggregate of base station downlink signal streams from a plurality of base stations; processing the aggregate signal stream and detecting, from the processing of the aggregate signal stream, a set of base stations in communication range of the UE device, wherein the set of base stations include a current serving base station and a scanning base station; determining, from the processing of the aggregate signal stream, a Doppler shifted center frequency of a downlink scanning signal stream received from the scanning base station; and enhancing, in dependence on the Doppler shifted center frequency, the downlink scanning signal stream associated to the scanning base station.

IPC Classes  ?

  • H04L 27/26 - Systems using multi-frequency codes
  • H04B 7/08 - Diversity systemsMulti-antenna systems, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
  • H04W 48/16 - DiscoveringProcessing access restriction or access information

8.

Balanced resource allocator for heterogeneous multi-objective systems

      
Application Number 16883616
Grant Number 11403142
Status In Force
Filing Date 2020-05-26
First Publication Date 2022-08-02
Grant Date 2022-08-02
Owner Peraton Labs Inc. (USA)
Inventor
  • Chang, Nicholas
  • Fecko, Mariusz
  • Smith, Clay

Abstract

A computer-implemented method, a system, and a computer program product include program code that obtains, from a controller, temporal objectives and configuration specifications. The program code adjusts weighting for multiple concurrent modes. The program code optimizes each mode of the multiple concurrent modes. The program code discovers conflicts exist between the optimized multiple concurrent modes and resolves the conflicts. The program code allocates resources to the optimized multiple concurrent modes.

IPC Classes  ?

  • G06N 3/08 - Learning methods
  • G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
  • G06F 9/46 - Multiprogramming arrangements
  • H04K 3/00 - Jamming of communicationCounter-measures

9.

Independent situational awareness for a network

      
Application Number 17002361
Grant Number 11388044
Status In Force
Filing Date 2020-08-25
First Publication Date 2022-07-12
Grant Date 2022-07-12
Owner Peraton Labs Inc. (USA)
Inventor
  • Lau, Chi Leung
  • Shur, David
  • Shen, Qiong
  • Rege, Kiran
  • Krishnan, Rajesh
  • Chen, Ta
  • Cichocki, Andrzej
  • Banwell, Tom

Abstract

A computer-program product, a system, and a computer-implemented method include a processor(s) obtaining a configuration of a network including configurations of multiple network nodes and configurations of the network communication devices. The program code automatically models the network to generate a system model. The program code derives, from the system model, a loop-free Bayesian inference model, by generating a loop-free Bayesian network from the network.

IPC Classes  ?

  • H04L 41/0677 - Localisation of faults
  • H04L 41/12 - Discovery or management of network topologies
  • G06N 7/00 - Computing arrangements based on specific mathematical models
  • H04L 9/40 - Network security protocols

10.

Directed handovers in a cellular network for airborne mobile telemetry

      
Application Number 17072538
Grant Number 11716665
Status In Force
Filing Date 2020-10-16
First Publication Date 2021-04-15
Grant Date 2023-08-01
Owner Peraton Labs Inc. (USA)
Inventor
  • Triolo, Anthony A.
  • Kogiantis, Achilles
  • Rege, Kiran M.

Abstract

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining one or more parameter characterizing a prospective connection of the mobile airborne article to first through Nth base stations, the one or more parameter including a Doppler shift; determining based on the examining that a criterion is satisfied, the criterion having one or more factor; and initiating handoff of the mobile airborne article to one of the first through Nth base stations based on the determining.

IPC Classes  ?

  • H04W 36/32 - Reselection being triggered by specific parameters by location or mobility data, e.g. speed data
  • H04W 36/08 - Reselecting an access point
  • H04W 84/06 - Airborne or Satellite Networks
  • H04B 17/336 - Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
  • H04B 17/318 - Received signal strength
  • H04B 7/01 - Reducing phase shift
  • H04B 17/391 - Modelling the propagation channel

11.

Migration of traffic flows

      
Application Number 16246388
Grant Number 11503051
Status In Force
Filing Date 2019-01-11
First Publication Date 2019-07-11
Grant Date 2022-11-15
Owner PERATON LABS INC. (USA)
Inventor
  • Kaplan, Michael
  • Shur, David
  • Kaul, Vikram
  • Bowen, Thomas

Abstract

There is set forth herein obtaining data traffic monitoring data, the data traffic monitoring data being in dependence on monitoring of traffic received by a container of a protected computing environment; obtaining data traffic monitoring data, the data traffic monitoring data being in dependence on monitoring of traffic received by a processing resource of a computing environment; obtaining a state of the processing resource and provisioning a utility processing resource to include the state of the processing resource; and configuring the computing environment to route data traffic to the utility processing resource.

IPC Classes  ?

  • H04L 9/40 - Network security protocols
  • H04L 41/08 - Configuration management of networks or network elements
  • H04L 43/08 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
  • H04L 47/00 - Traffic control in data switching networks
  • H04L 43/062 - Generation of reports related to network traffic
  • H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
  • H04L 45/00 - Routing or path finding of packets in data switching networks
  • H04L 41/0806 - Configuration setting for initial configuration or provisioning, e.g. plug-and-play
  • H04L 43/16 - Threshold monitoring
  • H04L 41/082 - Configuration setting characterised by the conditions triggering a change of settings the condition being updates or upgrades of network functionality