Disclosed herein is a method and system for detecting, monitoring and/or controlling one or more of mobile services for a mobile communication device (also referred to herein as a Controllable Mobile Device or CMD), and in particular, when the device is being used and the vehicle, operated by the user of the device, is moving. In addition, one aspect of the invention generally relates to a method and system for modifying a user's driving behaviors, in particular to a system and method for modifying a user's unsafe driving behaviors, e.g., using one or more services of a controllable mobile device while driving, by providing a score to the user rating indicating that they are using a mobile device in a distracting way, or driving in a manner that indicates that they are distracted.

A system, method and computer program product for controlled drone descent, and deactivation, including a drone deactivation system; and a location system. The drone deactivation system calculates positioning, signal reception, signal strength, and signal identification parameters of a target drone from the location system, and determines an attack method based on the calculated parameters. The drone deactivation system employs the determined attack method against the target drone for forcing at least one of controlled drone descent, and deactivation of the target drone.

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. Sensor data can be received from one or more portable countermeasure devices or sensors. The sensor data can relate to an object detected proximate to a particular airspace. The system can analyze the sensor data relating to the object to determine a location of the object and determine that the object is flying within the particular airspace based at least in part on location data. A portable countermeasure device can be identified that corresponds to the location of the object. The system can transmit information about the object to the identified portable countermeasure device. The portable countermeasure device can transmit additional data relating to the object to the system.

Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Certain aspects of the present disclosure generally relate to jamming detection for radio frequency (RF) front-end circuitry. For example, certain aspects provide an apparatus having a first counter configured to count a number of times that a power of a reception signal exceeds a first threshold. The apparatus also includes a second counter configured to count a number of measurements of the power of the reception signal. The apparatus further includes control logic having a first input coupled to an output of the first counter and having a second input coupled to an output of the second counter. The control logic is configured to determine an amount of jamming over a measurement window based on the number of times that the power of the reception signal exceeds the first threshold and on the number of measurements.

Provided is a method and a computer device for performing the method for defending a perimeter against a small unmanned aerial system (sUAS). The method includes detecting a presence of a wireless access point (WAP) associated with a sUAS; analyzing data packets intercepted from the WAP; determining the type of sUAS based on the data packets that were intercepted using a machine learning classifier; determining one or more exploits from a library of exploits to initiate against the sUAS based on the type of sUAS determined by the machine learning classifier; and transmitting the one or more exploits to the sUAS.

The system and methods described herein aids in the defense of unmanned vehicles, such as aerial vehicles, from wifi cyber attacks. Such attacks usually do not last long and in the case of many point-to-point command and control systems, the attacks originate from close proximity to the unmanned vehicle. The system and methods described herein allow a team to rapidly identify and physically respond to an adversary trying to take control of the unmanned vehicle. Another aspect of the embodiment taught herein is to allow for the location of a wifi signal in a hands-free manner by able to visualize the source of the signal using an augmented reality display coupled to an antenna array.

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. A tracking system can include one or more first computing devices that receive sensor data associated with an object in a particular airspace from one or more sensors. The first computing device can analyze the sensor data relating to the object to determine information about the object. A portable countermeasure device can include one or more second computing devices. The second computing device can receive the information relating to the object. The second computing device can display a visual indicator indicating the information on a display.

A method for processing information related to one or more monitored areas, the method may include receiving by a central control unit, UAV indicators about at least one unmanned airborne vehicle (UAV) located within the one or more monitored areas; wherein the UAV indicators are generated by a preprocessing step that comprises extracting information that is embedded within sensed UAV communication, the sensed UAV communication is sensed by at least one sensor of a group of sensors; aggregating, by a central control unit, the UAV indicators, to provide aggregated information; and responding to the aggregated information, wherein the responding comprises at least one out of (i) outputting the aggregated information, and (ii) storing the aggregated information.

Disclosed herein are various clusters. A cluster comprises processing nodes that have supervisory roles and subordinate roles. A node in the cluster can have a supervisory or a subordinate role. The cluster can self-orchestrate its roles. The roles of the nodes can be assigned and/or reassigned (e.g., autonomously and/or automatically) by the cluster. Such system may achieve automatic commissioning of the cluster(s), e.g., in a facility.