Abstract: A radio transmitter adjusts its radio frequency (RF) fingerprint to defeat RF fingerprinting identification without destroying the content of its transmissions. The radio transmitter comprises a frequency-upconverter configured to upconvert a baseband or intermediate-frequency signal to an RF signal, and an amplifier to amplify the RF signal to produce a transmission signal. An RF fingerprint control circuit changes the non-linear behavior of the frequency-upconverter or the amplifier in order to change the RF fingerprint. The transmitter may create RF fingerprint “personalities” to be paired with different radio protocol behaviors and subscriber terminal identification codes (e.g., MAC addresses or SMSIs) for generating different radio identities.

Abstract: In a wireless communication system, a secure communication link is provided by producing a set of reference symbols selected from a modulation symbol constellation; generating a data-bearing pre-coding transform from information to be transmitted to a receiver; applying the data-bearing pre-coding transform to the set of reference symbols, thereby distorting the reference symbols with respect to the information, to produce a linear transformation signal; and transmitting the linear transformation signal to the receiver. The reference symbols are known at the receiver. The receiver removes the reference symbols from the linear transformation signal and decodes the data-bearing pre-coding transform.

Abstract: A system detects and identifies unmanned vehicles (UVs) from radio communications between UVs and their controllers. One or more radio frequency (RF) signal detectors can detect RF signals, including downlink signals transmitted by a UV or uplink signals transmitted by a UV controller. A feature extractor can extract signal features from detected RF signals, and a classifier performs machine learning to identify at least one of the UV and the UV controller based on the signal features. Machine learning can employ an artificial neural network, which may perform deep learning.

Abstract: A system deploys electronic countermeasures against unmanned aerial vehicles (UAVs) that are determined to be a threat. A radio transceiver coupled to at least one antenna detects if radio signals are being communicated between a remote control unit and a UAV. A mitigation engine communicatively coupled to the radio transceiver synthesizes an exploit signal to be transmitted to the UAV, wherein the exploit signal is configured to inject commands into the UAV's navigation system. If the system determines that the UAV is operating in an autopilot mode, it transmits an induce-mode signal that causes the UAVs to switch to a communication mode so the UAV is responsive to the exploit signal.

Abstract: A network node in a distributed network employs a surface immunoglobulin program to monitor other nodes in the distributed network and generate an alert upon detecting a suspicious activity; and pushes a free-antibody program to a requesting node petitioning to access the distributed network. The free-antibody program can include a software agent that monitors the requesting node. The free-antibody program reports detected malware and/or suspicious activity to the surface immunoglobulin program, which can enact countermeasures against the requesting node. The network node's role is based on a hierarchy of trustworthiness levels, wherein it performs at least one of monitoring other nodes, sending alerts when anomalous behavior is detected, transmitting the free-antibody software program to the requesting node, updating defensive programs, participating in consensus-based threat analysis with other nodes, identifying threats, tagging suspicious nodes, and performing countermeasures against identified threats.

Abstract: A system deploys electronic countermeasures against unmanned aerial vehicles (UAVs) that are determined to be a threat. A radio transceiver coupled to at least one antenna detects if radio signals are being communicated between a remote control unit and a UAV. A mitigation engine communicatively coupled to the radio transceiver synthesizes an exploit signal to be transmitted to the UAV, wherein the exploit signal is configured to inject commands into the UAV's navigation system. If the system determines that the UAV is operating in an autopilot mode, it transmits an induce-mode signal that causes the UAVs to switch to a communication mode so the UAV is responsive to the exploit signal.

Abstract: In a wireless communication system, a secure communication link is provided by producing a set of reference symbol values selected from a modulation symbol constellation; generating a linear transformation operator from information to be transmitted to a receiver; applying the linear transformation operator to the set of reference symbol values, thereby distorting the reference symbol values with respect to the information, to produce a linear transformation signal; and transmitting the linear transformation signal to the receiver. The receiver decodes the linear transformation signal to receive the information.

Abstract: A system deploys electronic countermeasures against unmanned aerial vehicles (UAVs) that are determined to be a threat. A radio transceiver coupled to at least one antenna detects if radio signals are being communicated between a remote control unit and a UAV. A mitigation engine communicatively coupled to the radio transceiver synthesizes an exploit signal to be transmitted to the UAV, wherein the exploit signal is configured to inject commands into the UAV's navigation system. If the system determines that the UAV is operating in an autopilot mode, it transmits an induce-mode signal that causes the UAVs to switch to a communication mode so the UAV is responsive to the exploit signal.

Abstract: In a wireless communication system, a secure communication link is provided by selecting a decoy data signal vector for transmission, generating a MIMO precoding matrix from a message to be sent; and multiplying the decoy data signal vector by the MIMO precoding matrix to construct a precoded signal vector. The MIMO precoding matrix produces information-bearing synthesized channel distortions in the transmitted signal. An undistorted version of the decoy data may be transmitted to an intended receiver. The receiver distinguishes between the synthesized information-bearing channel distortions and natural channel distortions to decrypt the information, while an eavesdropper would find it difficult to distinguish between natural and synthesized channel distortions in the signals it receives.

Abstract: A first node in a wireless network retransmits a data signal. The node employs a precoder that generates transmit power values from a message to be transmitted and precodes the data signal with the transmit power values before the data signal is retransmitted. A second node receives the retransmitted signal. The second node uses a reference signal processor configured to determine the data signal and a decoder configured to remove the data signal from the received signal. The power values are estimated and processed to decode the information therefrom.

Abstract: In a wireless communication system, a secure communication link is provided by selecting a decoy data signal vector for transmission, generating a MIMO precoding matrix from a message to be sent; and multiplying the decoy data signal vector by the MIMO precoding matrix to construct a precoded signal vector. The MIMO precoding matrix produces information-bearing synthesized channel distortions in the transmitted signal. An undistorted version of the decoy data may be transmitted to an intended receiver. The receiver distinguishes between the synthesized information-bearing channel distortions and natural channel distortions to decrypt the information, while an eavesdropper would find it difficult to distinguish between natural and synthesized channel distortions in the signals it receives.

Abstract: A system detects unmanned aerial vehicles (UAVs) and deploys electronic countermeasures against one or more UAVs that are determined to be a threat. A signal detector detects radio signals communicated between a remote control unit and UAV. A feature extractor extracts signal features from the detected radio signals, and a classifier processes the detected radio signals based on its signal features and determines whether the detected radio signals correspond to a known or unknown radio protocol. A threat analyzer determines if a detected UAV is a threat based on at least one of remote-sensing data and classification(s) of the detected radio signals. When a UAV system employs an unknown radio protocol, a mitigation engine synthesizes an exploit based on corresponding extracted signal features. A response analyzer detects a response from the UAV system when an exploit is activated and may adapt the exploit based on the response. In some cases, the exploits can be configured against a UAV in autopilot mode.