SIGNAL-EMISSION CONTROL DEVICE FOR WIRELESS COMMUNICATION NETWORK

    公开(公告)号:US20240267726A1

    公开(公告)日:2024-08-08

    申请号:US18565726

    申请日:2022-05-30

    IPC分类号: H04W12/02 H04W12/65 H04W12/79

    CPC分类号: H04W12/02 H04W12/65 H04W12/79

    摘要: The invention is directed to a signal-emission control device (100) for controlling emission of RF communication signals (Si) in a wireless communication network (140) that includes a transmitter device (152) and a receiver device (154). The emission is controllable with respect to a variable signal parameter (P). An emission-value ascertainment unit (102) is configured to ascertain variation-data indicative of an emission-value variation of signal-parameter values of the signal parameter. A scheduling unit (110) is configured to ascertain operation-trigger data indicative of operation conditions for triggering control of emission of the wireless RF communication signals in accordance with the ascertained emission-value. A transmitter-control unit (104) is configured to control operation of transmitter device for transmitting the communication signals (Si) according to the emission-value variation of the respective signal-parameter value upon fulfilment of the operation conditions. This enables an increase of the verisimilitude of the provided communication signals against illegitimate RF-based eavesdropping.

    SECRET KEY EXTRACTION FOR LINE-OF-SIGHT COMMUNICATIONS

    公开(公告)号:US20230171595A1

    公开(公告)日:2023-06-01

    申请号:US17540136

    申请日:2021-12-01

    摘要: Methods, systems, and devices for wireless communications are described. Communication devices may perform secret key generation using a set of line-of-sight (LOS) communication modes to secure a physical channel. For example, a first device and a second device may communicate a set of reference signals over the physical channel using a set of LOS communication modes. The first device and the second device may generate a secret key based on the set of LOS communication modes, for example, by using information associated with the set of LOS communication modes to compute the secret key using a key derivation function that outputs the secret key. The first device and the second device may secure the physical channel by encrypting signaling between the first device and the second device with the secret key and communicating the signaling over the physical channel using LOS communications.

    RADIO FREQUENCY FINGERPRINTING USING ATTENTIONAL MACHINE LEARNING

    公开(公告)号:US20230164572A1

    公开(公告)日:2023-05-25

    申请号:US18057830

    申请日:2022-11-22

    IPC分类号: H04W12/79 H04B1/04

    CPC分类号: H04W12/79 H04B1/0483

    摘要: Embodiments of the disclosure provide a sensitivity enhancing radio frequency identification technique using machine learning. A method according to the disclosure includes obtaining an input signal associated with a radio frequency (RF) transmission; separately extracting spatial domain features, time-frequency domain features, and temporal domain features from the input signal; processing the spatial domain features, time-frequency domain features, and temporal domain features to generate an attentional vector; and predicting at least one descriptor for an emitter of the RF transmission based on the attentional vector.

    MONITORING SYSTEM FOR SECURING NETWORKS FROM HACKER DRONES

    公开(公告)号:US20220109702A1

    公开(公告)日:2022-04-07

    申请号:US17553987

    申请日:2021-12-17

    摘要: Methods, systems, and apparatus, including computer programs encoded on a storage device, for securing a network associated with a property in response to the detection of a hacking drone within a vicinity of the property. In one aspect, a method includes obtaining sensor data from one or more sensors located at a property, detecting, based on the obtained sensor data, the presence of a drone, determining, based on the obtained sensor data, that the detected drone is an unauthorized drone, determining, by the monitoring system, that the unauthorized drone (i) is communicating or (ii) attempting to communicate with a network associated with the property, selecting one or more network adjustment policies, and transmitting one or more instructions to (i) one or more monitoring system components or (ii) one or more network components that are configured to adjust network parameters based on the one or more selected network adjustment policies.

    Surveillance-based relay attack prevention

    公开(公告)号:US11228601B2

    公开(公告)日:2022-01-18

    申请号:US15926982

    申请日:2018-03-20

    申请人: Intel Corporation

    摘要: In one embodiment, an apparatus comprises an antenna to receive one or more radio signals, wherein the antenna is associated with a proximity-based access portal. The apparatus further comprises a processor to: detect, based on the one or more radio signals, an access request from a first device, wherein the access request comprises a request to access the proximity-based access portal using an access token associated with an authorized device; determine, based on the one or more radio signals, that the first device is within a particular proximity of the proximity-based access portal; obtain a first motion history associated with movement detected near the proximity-based access portal; obtain a second motion history associated with movement detected by the authorized device; and determine, based on the first motion history and the second motion history, whether the movement detected near the proximity-based access portal matches the movement detected by the authorized device.

    Systems and methods for recognizing a device and/or an instance of an app invoked on a device

    公开(公告)号:US11093852B2

    公开(公告)日:2021-08-17

    申请号:US15297889

    申请日:2016-10-19

    申请人: ACCERTIFY, INC.

    摘要: A system of classifying devices and/or app instances a new or returning divides attributes generated from observations received from an uncharacterized device/software app into base-fingerprint attributes and predictor attributes, where the two kinds of attributes have different longevities. Predictor attribute tuples from attribute tuples having the same base fingerprint as the base fingerprint corresponding to the uncharacterized device/app, and the predictor attribute tuple corresponding to the uncharacterized device/app are analyzed using a machine learned predictor function to obtain a final fingerprint. Machine learning techniques such as logistic regression, support vector machine, and artificial neural network can provide a predictor function that can decrease the conflict rate of the final fingerprint and, hence, the utility thereof, without significantly affecting the accuracy of classification.

    CAMOUFLAGING EMI FINGERPRINTS IN ENTERPRISE COMPUTER SYSTEMS TO ENHANCE SYSTEM SECURITY

    公开(公告)号:US20210235275A1

    公开(公告)日:2021-07-29

    申请号:US17230156

    申请日:2021-04-14

    摘要: The disclosed embodiments relate to a system that camouflages EMI fingerprints in EMI emissions from a computing system to enhance system security. During operation, the system monitors the EMI emissions from the computer system during operation of the computer system to produce corresponding EMI signals. Next, the system determines a dynamic amplitude of the EMI emissions based on the EMI signals. If the dynamic amplitude of the EMI emissions drops below a threshold value, the system executes synthetic transactions, which have interarrival times that, when superimposed on a workload of the computer system, cause the computer system to produce randomized EMI emissions.

    Camouflaging EMI fingerprints in enterprise computer systems to enhance system security

    公开(公告)号:US11012862B2

    公开(公告)日:2021-05-18

    申请号:US16258544

    申请日:2019-01-26

    摘要: The disclosed embodiments relate to a system that camouflages electromagnetic interference (EMI) fingerprints in EMI emissions from a computing system to enhance system security. During operation, the system monitors the EMI emissions from the computer system while the computer system is operating to produce corresponding EMI signals. Next, the system performs a Fast Fourier Transform (FFT) operation on the EMI signals. The system then converts an output of the FFT operation into a frequency-domain representation of the EMI signals. Next, the system generates a camouflaging signal based on the frequency-domain representation of the EMI signals. Finally, the system outputs the camouflaging signal through a transmitter to camouflage EMI fingerprints in the EMI emissions from the computer system.