Abstract: The invention described herein addresses the security shortcomings in existing Supervisory Control Systems (SCS), inclusive of but not limited to CAN Bus, SCADA, DCS, HEMS and IoT. The invention references U.S. Pat. No. 10,367,794 B2 Sayers et al., which is improved by the addition of a Validated Transmission data system, a Receiver Validation data system, and redundant links, which may be comprised of but not limited to technologies such as fiberoptics, time division multiplexing, frequency division multiplexing, various radio frequency links inclusive of TDM, OFDM, and CDMA modulation schemes, and a novel scheme for validating transmissions through self-generated tables by network elements.

Abstract: One embodiment of this invention describes a method and apparatus for the use of Machine Learning to efficiently detect, identify, prevent, and predict cyber-attacks on Low Power and Low Complexity Sensor 100 (FIG. 1) networks that have low data transmission requirements, something that all current Machine Learning techniques are unable to accomplish due to numerous restrictions when applied to Low Power and Low Complexity Sensors. Low Power and Low Complexity Sensors are frequently found in various Internet of Things (IOT) network architectures. The IOT is a network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables them to connect and exchange data, providing more direct integration of the physical world into computer-based systems. However, this should not restrict the applicability of any potential embodiment of this invention as described in this patent application.

Abstract: A method for the trading of cryptocurrencies using a modified blockchain approach. It facilitates the creation of a blockchain based indexed record consisting of customized grouping of various Cryptocurrencies or Digital Ledger Tokens (collectively abbreviated as CCDLTs). In addition the consumers can purchase or sell multiple Cryptocurrencies or Digital ledger Tokens (CCDLTs) of an indexed fund, using a single purchase order instead of the current method of manually placing multiple individual purchase orders.

Abstract: One embodiment of this invention describes a method and apparatus for the use of Machine Learning to efficiently detect, identify, prevent, and predict cyber-attacks on Low Power and Low Complexity Sensor 100 (FIG. 1) networks that have low data transmission requirements, something that all current Machine Learning techniques are unable to accomplish due to numerous restrictions when applied to Low Power and Low Complexity Sensors. Low Power and Low Complexity Sensors are frequently found in various Internet of Things (IOT) network architectures. The IOT is a network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables them to connect and exchange data, providing more direct integration of the physical world into computer-based systems. However, this should not restrict the applicability of any potential embodiment of this invention as described in this patent application.

Abstract: One embodiment of this invention describes a method and apparatus for the secure identification and validation of low complexity sensors or devices on a network. In addition any data transmitted between the sensors/devices to/from the network is secured by means of encryption techniques. The method as described herein is intended to protect and secure sensors/devices that might transmit limited amounts of data and have reduced levels of onboard processing power. However it could easily be adapted to other types of networks to provide comparable levels of security and protection. A further understanding of the nature and the advantages of the particular embodiments disclosed herein may be realized by referencing the remaining portions to the specification and the attached drawings.

Abstract: One embodiment of this invention describes a method and apparatus for the secure identification and validation of devices on a network using a low complexity method. In addition, any data transmitted between the devices to/from the network is secured by means of encryption techniques. The method as described herein is intended to protect and secure devices that might need to access a secured sensor or device type of network, for example an Internet of Things (IOT) network. However it could easily be adapted to other types of networks to provide comparable levels of security and protection. A further understanding of the nature and the advantages of particular embodiments disclosed herein may be realized by referencing the remaining portions of the specification and the attached drawings.

Abstract: One embodiment of this invention describes a method and apparatus for the secure identification and validation of low complexity sensors or devices on a network. In addition any data transmitted between the sensors/devices to/from the network is secured by means of encryption techniques. The method as described herein is intended to protect and secure sensors/devices that might transmit limited amounts of data and have reduced levels of onboard processing power. However it could easily be adapted to other types of networks to provide comparable levels of security and protection. A further understanding of the nature and the advantages of the particular embodiments disclosed herein may be realized by referencing the remaining portions to the specification and the attached drawings.

Abstract: One embodiment of this invention describes a method and apparatus for identifying, predicting, and preventing malicious attacks against low complexity sensors or devices (sensors/devices) on a network through the use of an Artificial Neural Network (ANN) which is defined as a connectionist system (i.e. interconnected networks) functioning as a computing system inspired by living neural networks (e.g. the human brain). An ANN employs Machine Learning computational models that, without being programmed with any task-specific rules, can “learn” capabilities such as image recognition by simply considering relevant examples. This approach is similar to how a person might learn a new task. There are many forms and types of malicious attacks that are sometimes more commonly referred to as cyber attacks. In one instance of this invention the malicious attacks are identified by organizing and classifying encryption keys and/or messages sent to or received from a sensor/device.

Abstract: The present invention relates to a method and apparatus for the communicating between remote devices using a low message rate wireless connection via monitoring, control and information systems. The network described in this invention is capable of supporting billions of such devices in an efficient and cost effective manner. The network uses a very low signaling rate and centrally controlled architecture in order to achieve this efficiency. The network can easily support numerous applications each controlling large numbers of devices. As the complexity of protocol used in the network is very much reduced in comparison to existing hierarchical mobile wireless networks, it is possible to produce devices that use very little energy allowing their use in many new and novel applications.

Abstract: The present invention relates to a method and apparatus for the communicating between remote devices using a low message rate wireless connection via monitoring, control and information systems. The network described in this invention is capable of supporting billions of such devices in an efficient and cost effective manner. The network uses a very low signaling rate and centrally controlled architecture in order to achieve this efficiency. The network can easily support numerous applications each controlling large numbers of devices. As the complexity of protocol used in the network is very much reduced in comparison to existing hierarchical mobile wireless networks, it is possible to produce devices that use very little energy allowing their use in many new and novel applications.

Abstract: A technique for implementing Special Call Services (SCS) to extend wireless system functionality to include private emergency or other types of service-specific special calls in a private network. In a preferred embodiment, the capability is implemented by taking advantage of certain service type elements that may be coded in the Radio Resource Management (RR) functional layer channel request message and/or the Mobility Management (MM) functional layer call request messages in a Global System for Mobile (GSM) communication system. Specifically, an establishment cause field in a RR channel request message and/or a service type field in a MM request message is used to request such services from the network. These establishment causes and service types can be defined, but not limited to, using those codes currently defined as reserved by GSM Version 4.08, Section 9.1.8 and Section 10.5.3.3.

Abstract: A multiple antenna cellular network communicates with a mobile station over a plurality of antennas. The antennas are arranged in a plurality of positions to customize a cell or cells. A transceiver is coupled to the antennas and configured to receive inbound information from the mobile station and transmit outbound information to the mobile station. A processor is coupled to the transceiver and configured to decode the inbound information and to encode the outbound information to communicate with the mobile station. In another embodiment, the transmit signal power is continuously modified to move interference nulls to improve quality so that a fixed location user can receive a high quality signal. Exemplary embodiments are provided for use with the Global Systems for Mobile Communication (GSM) protocol and can be applied to other digital technologies.

Abstract: A multiple antenna cellular network communicates with a mobile station over a plurality of antennas. The antennas are arranged in a plurality of positions to customize a cell or cells. A transceiver is coupled to the antennas and configured to receive inbound information from the mobile station and transmit outbound information to the mobile station. A processor is coupled to the transceiver and configured to decode the inbound information and to encode the outbound information to communicate with the mobile station. In another embodiment, the antennas are similarly deployed to create a cell or cells. The transmit signal power is continuously modified to improve quality and to move the nulls so that a fixed location user can receive a high quality signal. Exemplary embodiments are provided for use with the Global Systems for Mobile Communication (GSM) protocol and can be applied to other digital technologies.

Abstract: A multiple antenna cellular network communicates with a mobile station over a plurality of antennas. The antennas are arranged in a plurality of positions to customize a cell or cells. A transceiver is coupled to the antennas and configured to receive inbound information from the mobile station and transmit outbound information to the mobile station. A processor is coupled to the transceiver and configured to decode the inbound information and to encode the outbound information to communicate with the mobile station. In another embodiment, the transmit signal power is continuously modified to move interference nulls to improve quality so that a fixed location user can receive a high quality signal. Exemplary embodiments are provided for use with the Global Systems for Mobile Communication (GSM) protocol and can be applied to other digital technologies.