Abstract: This application is directed to a method for detecting if a cellular attack from a rogue base station router (RBRS) on a cellular network is active. The method includes a step of surveying the network to obtain broadcast data. The method also includes a step of determining that a base station router (BSR) in the network is the RBSR based on execution of a machine learning algorithm using the broadcast data. The method also includes a step of determining that an event associated with a cellular attack is present in the network. The method further includes a step of determining that the cellular attack from the RBSR on the network is active based on the determined RBSR and the determined event associated with a cellular attack.

Abstract: One aspect of the patent application is directed to a method for detecting a rogue device in a network. The method includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including system information blocks (SIBs) associated with plural devices. The method also includes a step of decoding the SIBS of the devices. The method further includes a step of comparing the decoded SIBs with the predetermined criteria. The method even further includes a step of determining a threshold of the predetermined criteria has been met by the decoded SIBs associated with one of the plural devices. Yet even further, the method includes a step of calculating a confidence level based upon the met threshold of the one device. Lastly, the method includes a step of determining, based on the confidence level, the one device exhibits characteristics of the rogue device.

Abstract: The patent application is directed to a method for determining if a cellular attach on a communication system is active, include the step of identifying a base station router (BSR) in the communication system via a cellular scan. The method also includes a step of determining a distribution curve for a predetermined criteria, including a calculated mean and calculated standard deviation, based on survey data for the predetermined criteria from the cellular scan that is associated with a public land mobile network (PLMN) of a single carrier in a single radio access technology (RAT). The method also includes a step of determining that an event directed to cellular connectivity is present in the communication system. The method further includes a step of determining that the cellular attack associated with the BSR is active based on the determined distribution curve and the determined event.

Abstract: The patent application is directed to a method for detecting a rogue device in a network including the step of providing an algorithm including predetermined criteria, executed by a processor, for identifying the rogue device. The method also includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including information of plural devices associated with the predetermined criteria. The method further includes a step of displaying, via a graphical user, a distribution curve including a calculated mean and a standard deviation based on the survey data for the predetermined criteria. The method also includes a step of comparing the information of one of the plural devices with statistically-calculated distribution curves.

Abstract: This application is directed to a method for detecting if a cellular attack from a rogue base station router (RBRS) on a cellular network is active. The method includes a step of surveying the network to obtain broadcast data. The method also includes a step of determining that a base station router (BSR) in the network is the RBSR based on execution of a machine learning algorithm using the broadcast data. The method also includes a step of determining that an event associated with a cellular attack is present in the network. The method further includes a step of determining that the cellular attack from the RBSR on the network is active based on the determined RBSR and the determined event associated with a cellular attack.

Abstract: One aspect of the patent application is directed to a method for detecting a rogue device in a network. The method includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including system information blocks (SIBs) associated with plural devices. The method also includes a step of decoding the SIBS of the devices. The method further includes a step of comparing the decoded SIBs with the predetermined criteria. The method even further includes a step of determining a threshold of the predetermined criteria has been met by the decoded SIBs associated with one of the plural devices. Yet even further, the method includes a step of calculating a confidence level based upon the met threshold of the one device. Lastly, the method includes a step of determining, based on the confidence level, the one device exhibits characteristics of the rogue device.

Abstract: This application is directed to a method for detecting a rogue device in a network. The method includes a step of surveying the network. The method also includes a step of collecting broadcast data from cellular towers in the network based on the survey. The method also includes a step of distilling the collected broadcast data into abstract syntax notation one (ASN.1)-encoded system information blocks (SIBs) associated with plural devices. The method further includes a step of featurizing the ASN.1-encoded SIBs. The method even further includes a step of running the featurized, ASN.1-encoded SIBs through an unsupervised machine learning algorithm. The algorithm is executed by a processor to analyze all cells in the survey for the rogue device. Yet even further, the method includes a step of determining, based on the run, anomalous cells exhibiting characteristics of the rogue device from all cells in the survey.

Abstract: One aspect of the patent application is directed to a method for detecting a rogue device in a network. The method includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including system information blocks (SIBs) associated with plural devices. The method also includes a step of decoding the SIBS of the devices. The method further includes a step of comparing the decoded SIBs with the predetermined criteria. The method even further includes a step of determining a threshold of the predetermined criteria has been met by the decoded SIBs associated with one of the plural devices. Yet even further, the method includes a step of calculating a confidence level based upon the met threshold of the one device. Lastly, the method includes a step of determining, based on the confidence level, the one device exhibits characteristics of the rogue device.

Abstract: One aspect of the patent application is directed to a method for detecting a rogue device in a network. The method includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including system information blocks (SIBs) associated with plural devices. The method also includes a step of decoding the SIBS of the devices. The method further includes a step of comparing the decoded SIBs with the predetermined criteria. The method even further includes a step of determining a threshold of the predetermined criteria has been met by the decoded SIBs associated with one of the plural devices. Yet even further, the method includes a step of calculating a confidence level based upon the met threshold of the one device. Lastly, the method includes a step of determining, based on the confidence level, the one device exhibits characteristics of the rogue device.

Abstract: The patent application is directed to a method for detecting a rogue device in a network including the step of providing an algorithm including predetermined criteria, executed by a processor, for identifying the rogue device. The method also includes a step of performing a cellular scan across the network. The method also includes a step of receiving, from the cellular scan, survey data including information of plural devices associated with the predetermined criteria. The method further includes a step of displaying, via a graphical user, a distribution curve including a calculated mean and a standard deviation based on the survey data for the predetermined criteria. The method also includes a step of comparing the information of one of the plural devices with statistically-calculated distribution curves.

Abstract: This application is directed to a method for detecting a rogue device in a network. The method includes a step of surveying the network. The method also includes a step of collecting broadcast data from cellular towers in the network based on the survey. The method also includes a step of distilling the collected broadcast data into abstract syntax notation one (ASN.1)-encoded system information blocks (SIBs) associated with plural devices. The method further includes a step of featurizing the ASN.1-encoded SIBs. The method even further includes a step of running the featurized, ASN.1-encoded SIBs through an unsupervised machine learning algorithm. The algorithm is executed by a processor to analyze all cells in the survey for the rogue device. Yet even further, the method includes a step of determining, based on the run, anomalous cells exhibiting characteristics of the rogue device from all cells in the survey.

Abstract: Secure electronic access may be provided by receiving at least one electronic certificate from an electronic device seeking to access a secure resource at a device under protection including at least one security processor, the at least one certificate providing device information related to the security of the electronic device, and comparing with at least one autonomous processor of an autonomous system the device information to the security requirement information. The at least one autonomous processor may instruct the at least one security processor to provide the secure resource to the device when the device information meets the security requirement information. The device under protection may provide the secure resource to the electronic device in response to the instruction.

Abstract: Systems and methods described herein may detect hardware modifications. A test loop may terminate at a transmit pin and a receiver pin of a processor footprint pad. A processor may be coupled to the test loop via the transmit pin and the receiver pin. The processor may cause a signal to be transmitted to the test loop from the transmit pin and receive a modified signal from the test loop at the receiver pin. The processor may analyze the modified signal to detect a hardware modification in communication with the test loop based on the modified signal.

Abstract: A system for autonomous enforcement of rules may comprise a protected system, including infrastructure, operative in response to input signals and an autonomous control system. The autonomous control system may include a monitor circuit which is coupled to the input signals to monitor the input signals for violations of the rules and an action circuit coupled to the protected system which prevents the violating input signals from affecting the protected system.

Abstract: Secure electronic access may be provided by receiving at least one electronic certificate from an electronic device seeking to access a secure resource at a device under protection including at least one security processor, the at least one certificate providing device information related to the security of the electronic device, and comparing with at least one autonomous processor of an autonomous system the device information to the security requirement information. The at least one autonomous processor may instruct the at least one security processor to provide the secure resource to the device when the device information meets the security requirement information. The device under protection may provide the secure resource to the electronic device in response to the instruction.

Abstract: A system for autonomous enforcement of rules may comprise a protected system operative in response to input signals and an autonomous control system. The autonomous control system may include a monitor circuit which is coupled to the input signals to monitor the input signals for violations of the rules and an action circuit coupled to the protected system which prevents the violating input signals from affecting the protected system.

Abstract: A system may be broken down into one or more components. Each of the components may be evaluated to ascribe a security score to each of the components. A composite security score may be generated for the system based on the security scores and a rate of decay measure characterizing a probabilistic security degradation of the system. The rate of decay measure may be applied to the composite security score to obtain a current composite security score. The composite security score may be used to control access to a document, either alone or in addition to other criteria.

Abstract: A method of an application to identify wireless peripherals in an iOS environment or other environment when peripheral identification information such as address is limited or not available. The application assigns a unique identifier to each peripheral as it connects to a wireless network such as Bluetooth. The unique identifier is a settable/readable parameter that the operating system assigns as a property to the wireless peripheral, for example audio volume. The application assigns a unique value to the identifier for each peripheral, and if the parameters are equal for two or more peripherals, the values are slightly adjusted to be different. The application is particularly useful for keeping track of multiple Bluetooth headsets.