Abstract: Techniques are described to improve the security of frame synchronization detection between wireless devices in high accuracy positioning (HAP) applications using personal area networks (PANs). A receiver may detect whether a frame synchronization pattern has been manipulated by comparing the sampled data of the received frame synchronization pattern with a reference waveform predicted as the frame synchronization pattern. The receiver may reuse the data in the correlation buffer at the moment a correlator finds a peak and declares that the synchronization pattern is found. The correlator may also provide fractional timing information associated with the correlation peak for the receiver to create a delayed reference phase differential pattern. The receiver may subtract the data in the correlation buffer by the delayed reference differential data and look for absolute deviations in the output of such subtraction that exceed a predetermined threshold.

Abstract: A system is disclosed that includes a computer. The computer includes a processor and a memory. The memory includes instructions such that the processor is programmed to: group a plurality of endpoints based on evaluation result data for each endpoint of the plurality of endpoints; determine a target system configuration for the group; and transmit the target system configuration to a software agent corresponding to each endpoint of the plurality of endpoints.

Abstract: A method (300) for linking a common vulnerability and exposure, CVE, (106) with at least one synthetic common platform enumeration, CPE, (112) wherein the CVE (106) comprises a summary of a vulnerability, is disclosed. The method (300) comprising: receiving (S302) the summary of the CVE (106) from a vulnerability database, VD, (104); extracting (S304) information from the summary of the CVE (106) using a Natural Language Processing, NLP, model; building (S306) at least one synthetic CPE (112) based on the extracted information; and linking (S308) the CVE (106) with the at least one synthetic CPE (112).

Abstract: In some implementations, a system may receive a shell script associated with a computing device. The system may generate a character frequency feature vector based on the shell script. The system may input text of the shell script to a convolutional neural network (CNN) branch of a trained deep learning model. The system may input the character frequency feature vector to a feedforward neural network (FNN) branch of the trained deep learning model. The system may determine using the trained deep learning model, respective probability scores for each of a plurality of obfuscation types for the shell script based on a combined output of the CNN branch and the FNN branch. The system may detect whether the shell script is obfuscated based on respective probability scores for each of the plurality of obfuscation types determined for the shell script.

Abstract: This invention presents a computer processing system and method designed to execute cryptographic operations while providing selective protection against side-channel attacks. It comprises a configuration of unprotected and protected hardware modules, the latter of which is equipped with data isolators, and a protected arithmetic logic unit (ALU) for secure data processing. The system enhances cryptographic security by selectively transmitting and computing input shares to generate side-channel protected output shares, ensuring robust protection during cryptographic operations.

Abstract: Disclosed are an electronic cigarette, e-cigarette, for preventing minors from using and a control method thereof. The e-cigarette includes a vaporization assembly and a battery assembly, where the vaporization assembly is provided therein with a vaporization device; the battery assembly includes a casing, a holder, a battery, and a control circuit; the control circuit includes an output power control unit, a storage control unit, a personal biometric information acquisition unit, a prompt unit, and a communication unit; the personal biometric information acquisition unit is configured to acquire and input a user's personal biometric information into the storage control unit; and when the storage control unit stores or changes the user's authorized personal biometric information, the storage control unit utilizes an external device and special software that are authorized to complete the storage or change.

Abstract: A system for detection of binary files containing a known malware code fragment includes a processor coupled to a memory storing instructions, the processor being configured to implement the instructions to process an unknown binary file (UBF) and a known malicious source code file (KMSCF) to decompile the UBF into a text-based unknown source code (USC) and identify whether the KMSCF is contained within the USC.

Abstract: Events from one or more primary systems associated with one or more tenants are received. The received events are stored in a message queue. At least a portion of the events in the message queue are ingested for organization and storage in a data store. One or more progress identifiers associated with ingesting of the events in the message queue are tracked. An event query is received from an external system. The event query is rewritten into a first component query for the data store and a second component query for the message queue based at least in part on a progress identifier. A result of the first component query and a result of the second component query are combined to determine a result of the event query.

Abstract: Security drift can be automatically handled in cloud environments. A security audit engine can be configured to extract security configuration datasets from cloud resources and create text sentences from the datasets as well as from a golden configuration. These text sentences can be encoded as vectors in an n-dimensional space. Probability distributions can then be generated using the vectors such as by using an unsupervised clustering algorithm. Distance matrixes can then be generated from the probability distributions. A probability distribution pertaining to a dataset and a probability distribution pertaining to the golden configuration can then be compared and normalized using a transport to thereby yield a security drift score representing a divergence of the corresponding security settings from the golden configuration. When a security drift score exceeds a threshold, the security audit engine can take appropriate action.

Abstract: In some implementations, a system may receive a shell script associated with a computing device. The system may generate a character frequency feature vector based on the shell script. The system may input text of the shell script to a convolutional neural network (CNN) branch of a trained deep learning model. The system may input the character frequency feature vector to a feedforward neural network (FNN) branch of the trained deep learning model. The system may determine using the trained deep learning model, a respective probability score for each of a plurality of obfuscation types for the shell script based on a combined output of the CNN branch and the FNN branch. The system may detect whether the shell script is obfuscated based on the respective probability score for each of the plurality of obfuscation types determined for the shell script.