An aerial vehicle system is comprised of a detector, a signal generator, and a transmitter. The detector is configured to detect a presence of a target unmanned aerial vehicle within a range of the aerial vehicle system. The signal generator is configured to generate a communication disruption signal. The transmitter is configured to trigger a transmission of the communication disruption signal based in part on the detected presence of the target unmanned aerial vehicle.

RF tags using source addresses to locate stations on a Wi-Fi network are secured. An RF location server receives a pseudo source address of an RF (radio frequency) tag from a station. The station obtains the pseudo source address while being within radio range of the RF tag and the station receiving a beacon frame from the RF tag. A source address for the RF tag is looked-up utilizing the pseudo source address, and a specific location for the RF tag is looked-up utilizing the source address. Some embodiments store the locations in association with the pseudo address. Either way, the specific location of the station is identified based on the source address of the RF tag. An action is determined in response to at least the specific location of the station. Information related to the action is sent to the station for output to a user of the station. For example, a location-based offer or service can be provided in real-time with a consumer's presence to relevant products or services.

Disclosed is a low-altitude unmanned aerial vehicle surveillance system. According to an embodiment, monitoring is performed using a balloon main body filled with gas and staying in the air; radar; camera units being provided outside the balloon main body, and including a camera taking an image of a subject; radio frequency detectors; and sound detectors and correspondingly, interceptor means is included. As interceptor means, a jammer, a jamming gun, and a spoofing device corresponding to jamming are disclosed.

Disclosed herein are system, method, and computer program product embodiments for adapting to malware activity on a compromised computer system by detecting timing anomalies between timing signals. An embodiment operates by analyzing first timing data accessed from a validated source and second timing data accessed from an unvalidated receiver source in order to compute a threat detection value, which is utilized to determine if there is a discrepancy or anomaly in the timing or frequency of either the validated and unvalidated sources.

A privacy protection method and system (10) is provided for a building, home, apartment, or other area (12) protected by a connected security system (14). The system (10) includes a detector drone (16) and the security system (14). The drone (16) includes at least one drone detecting sensor (24) and automatically initiates a wireless signal (30) in response to the sensor (24) indicating the presence of a foreign drone (17). The security system (14) includes a central processor (40) and at least one electronic device (46) having a privacy condition wherein the device (46) protects against privacy intrusions by a foreign drone (17) and a non-privacy condition wherein the device (46) does not protect from the privacy intrusion. The processor (40) is configured to command the device (46) to change from the non-privacy condition to the privacy condition in response to the wireless signal (30) from the detector drone (16).

Methods and apparatus for detecting, geo-locating and/or classifying a GPS or GNSS jamming signal are disclosed. One such method comprises the steps of analysing a spectrogram of the jamming signal using a tree-based decision process and as a result, then selecting one of a number of types of jamming signal, wherein one of the decisions (1103) in the tree is whether the spectrogram has spectral periodicity.

Disclosed herein are system, method, and computer program product embodiments for a GNSS interference and spoofing fast detection and mitigation system. A RF signal associated with a PNT device, such as a GNSS receiver, is received. The received RF signal is split into a plurality of sub-data signals. The received RF signal is re-routed by sending each of the plurality of sub-data signals to at least one of a processing module and a switching module. An anomaly associated with a second sub-data signal is detected. The anomaly is detected during a capture period of an adversarial attack on the PNT device, prior to corruption of any associated system depending on outputs from the PNT device. An output of a first sub-data signal of the plurality of sub-data signals is terminated based on the anomaly detected with the second sub-data signal.

A navigation method based on satellite and inertial positioning data includes the following steps of computing: a first reference navigation, that is hybridised on the basis of inertial positioning data with positional corrections determined on the basis of satellite positioning data; a second reference navigation, that is hybridised on the basis of inertial positioning data; an emergency navigation on the basis of the second reference navigation, reset on the operational navigation then corrected by means of the positional corrections provided by the first reference navigation. A navigation system for implementing this method is also disclosed.

The present disclosure relates to an automatic interference/jamming detection system for use with a GNSS receiver or a GNSS receiver and off-the-shelf jamming detector. The automatic jamming detection system utilizes one of the following two techniques: using a jamming detector in conjunction with a GNSS receiver in order to analyze received data for key data indicators for suspicious interference/jamming activities such as signal-to-noise ratio, phase or maximum power, or using a trained jamming detection algorithm to convert received/stored GNSS data into spectrograms to visually highlight anomalies or potential interference/jamming events and then further using the Box-Cox transform to train the algorithm in order to transform data into a normal distribution for comparison against user tunable thresholds to further highlight potential interference/jamming events.

Disclosed herein are system, method, and computer program product embodiments for adapting to malware activity on a compromised computer system by detecting timing anomalies between timing signals. An embodiment operates by analyzing first timing data accessed from a validated source and second timing data accessed from an unvalidated receiver source in order to compute a threat detection value, which is utilized to determine if there is a discrepancy or anomaly in the timing or frequency of either the validated and unvalidated sources.