Abstract: Techniques for IoT policy recommendation LLM embeddings based on global behavior learning are disclosed. In some embodiments, a system, process, and/or computer program product for IoT policy recommendation LLM embeddings based on global behavior learning includes receiving information associated with network communications of a plurality of Internet of Things (IoT) devices; automatically learning a global common behavior for the plurality of IoT devices using a Large Language Model (LLM) classifier to generate a plurality of recommended rules; and applying a policy to at least one of the plurality of IoT devices based on one or more of the plurality of recommended rules.

Abstract: Techniques for detecting anomalous behavior of an Internet-of-Things (IoT) device in an IoT network. IoT events of an IoT device are captured and analyzed to identify periodic activities of the IoT device. The periodic activities of the IoT device are tracked over time, and variations in the periodic activities are analyzed to assess potential threats to the IoT network.

Abstract: Data packets transmitted to and from an IoT device are obtained and at least one of the data packets are analyzed using deep packet inspection to identify transaction data from payload of the at least one of the data packets. An event log is generated for the IoT device from the transaction data, the event log, at least in part, used to generate a historical record for the IoT device. The IoT device into a device profile based on the historical record for the IoT device. The event log is updated in real-time to indicate current operation of the IoT device. Abnormal device behavior of the IoT device is determined using the event log and the device profile. The device profile is updated to indicate the abnormal device behavior of the IoT device.

Abstract: Embodiments described herein include methods and apparatus for dynamically selecting antenna settings for reception of wireless signals in multiple radio frequency band by wireless devices. A wireless device includes at least two SIM/eSIM profiles that each use different radio frequency bands and dynamically selects an antenna tuner setting based on requirements of one or more applications in use and key radio frequency performance indicators. In some embodiments, the antenna hardware tuner setting is selected to improve paging reception for a secondary SIM/eSIM from a second cellular wireless network when applications communicating using a first SIM/eSIM via a first cellular wireless network can accommodate performance degradation for a period of time.

Abstract: Techniques for IoT policy recommendation LLM embeddings based on global behavior learning are disclosed. In some embodiments, a system, process, and/or computer program product for IoT policy recommendation LLM embeddings based on global behavior learning includes receiving information associated with network communications of a plurality of Internet of Things (IoT) devices; automatically learning a global common behavior for the plurality of IoT devices using a Large Language Model (LLM) classifier to generate a plurality of recommended rules; and applying a policy to at least one of the plurality of IoT devices based on one or more of the plurality of recommended rules.

Abstract: A modular adversarial training data generator (“generator”) generates adversarial training data for a machine learning (ML) model to detect malicious protocol data units (PDUs). The adversarial training data mimics high volume cyberattacks by perturbing PDUs to bypass malicious detection systems. For HyperText Transfer Protocol (HTTP) PDUs, the generator rearranged, replaces, and grid searches values of HTTP header fields to generate the adversarial training data. The generator further biases grid search based on metrics for values of HTTP header fields that quantify impact of replacing the values on malicious verdicts by ML models trained on the adversarial training data.

Abstract: Disclosed is an intelligent interactive decision-making method for a discrete manufacturing system. The method includes the following steps: step 1, establishing a production scheduling optimization model and strategy for discrete manufacturing for an actual application scene; step 2, training the scheduling strategy with existing production data on the basis of a deep reinforcement learning algorithm, and storing a state having a high reward in a training process in a memory; step 3, updating the state according to prior knowledge in the memory; step 4, inputting the updated state into a deep reinforcement learning network, obtaining a corresponding reward, and updating the memory according to the reward; and step 5, repeating step 4 until model parameters converge, and saving and putting the model into an actual production scene.

Abstract: The present disclosure is directed to a heat pipe assembly having a first heat pipe and at least one second heat pipe. The first heat pipe includes an inner wall surface, an outer wall surface, and at least one opening. The inner wall surface surrounds a first cavity, and the outer wall surface faces away from the inner wall surface. The at least one opening penetrates the inner wall surface and the outer wall surface. The at least one second heat pipe includes a second cavity and a connecting port. The connecting port connects the second cavity to the first cavity through the at least one opening.

Abstract: A stateful chatbot system leverages generative AI to provide an interface by which users can retrieve information from backend IoT databases of a security provider via natural language queries. Upon receiving a natural language query that corresponds to a request for information from the database, the chatbot generates a corresponding database query having a format compatible with the database. The chatbot comprises a generative model adapted to generate database queries based on natural language queries via prompt engineering using natural language and database query pairs. The chatbot queries the database with the generated database query, retrieves results comprising data/metadata that satisfy the query, and generates a summary of the results, both of which it presents as a response to the user's query. The chatbot also has access to a vulnerability database from which it can obtain information about known vulnerabilities documented therein to respond to user queries.

Abstract: Management of IoT devices through a private cloud. An IoT device is coupled to a gateway. A request from the IoT device to connect to a private cloud, wherein the private cloud is used to manage IoT devices, is received at a private cloud control center agent. An identification of the IoT device is determined. The IoT device is onboarded, using the identification, for management through the private cloud. A device profile of the IoT device is generated. The flow of data to and from the IoT device is regulated through application of IoT rules according to the device profile of the IoT device.

Abstract: A heat pipe including a pipe body, a first capillary structure and a second capillary structure. The pipe body has an evaporation portion and a condensation portion. The condensation portion is connected to the evaporation portion. The first capillary structure is disposed in the evaporation portion. The second capillary structure is disposed in the condensation portion and is connected to an end of the condensation portion that is located away from the evaporation portion. The second capillary structure is not in direct contact with the first capillary structure.

Abstract: A heat pipe including a pipe body, a first capillary structure and a second capillary structure. The pipe body has an evaporation portion and a condensation portion. The condensation portion is connected to the evaporation portion. The first capillary structure is disposed in the evaporation portion. The second capillary structure is disposed in the condensation portion and is connected to an end of the condensation portion that is located away from the evaporation portion. The second capillary structure is not in direct contact with the first capillary structure.

Abstract: Techniques for detecting anomalous network behavior in operational technology (OT) protocols are disclosed. A system, process, and/or computer program product for detecting anomalous network behavior in OT protocols include monitoring network traffic to perform automated OT malware detection analysis of OT related network traffic, extracting one or more features from the OT related network traffic, inputting the one or more extracted features into a model for malware detection analysis, and performing an action based on a result of the model.

Abstract: A software bill of materials (SBOM) and vulnerability management system (“system”) disclosed herein extracts software component-related identifiers for Internet of Things (IoT) devices using deep packet inspection. The system filters the identifiers by removing identifiers that match a blacklist of identifiers known to not correspond to software components. The system then populates SBOM fields using a database storing the filtered identifiers with a schema that is uniform across SBOM file formats and queries a vulnerability database with software components indicated in the filtered identifiers to identify vulnerabilities for each IoT device for security risk assessment.

Abstract: The present invention is a reconfigurable antenna, which includes a total reflection part, a partial reflection part, a partial transmission part, and a radiation part stacked in sequence. A resonant cavity is formed between the partial reflection part and the total reflection part. The radiation part is arranged in the resonant cavity. So that the electromagnetic wave radiated by the radiation part is reflected in the resonant cavity. The electromagnetic wave forms constructive interference during the reflection of the resonant cavity. The resonant cavity makes the electromagnetic wave form the same phase electromagnetic wave and radiation penetrating the reflection part. The partial transmission part is regulated to form beam reconstruction conditions, and the same-phase electromagnetic waves are formed into beams and radiated into space by the beam control conditions.

Abstract: A system, method, and device for detecting Command and Control (C2) traffic is disclosed. The method includes (i) converting a monitored traffic sample to an image representation, (ii) querying a classifier based at least in part on the image representation to obtain a traffic classification, (iii) automatically detecting C2 traffic based at least in part on the traffic classification, and (iv) handling the network traffic based at least in part on the traffic classification.

Abstract: Disclosed are a three-dimensional modeling system and modeling method based on multimodal fusion. The method includes: separately collecting feedback data of an electroencephalogram sensor, an electromyography sensor, an eye movement sensor, a gesture sensor, and a voice sensor, conducting multimodal fusion on the feedback data, obtaining multimodal-fused model data, matching the model data with a database instruction, obtaining and analyzing an instruction set, obtaining and identifying a relevant modeling parameter, obtaining a modeling method, automatically conducting modeling according to the modeling method, and obtaining a visual entity model.

Abstract: An optoelectronic synaptic memristor includes: a bottom electrode layer, a porous structure layer modified with quantum dots, a two-dimensional material layer, a transparent top electrode layer, and a waveguide layer, which are arranged in sequence from top to bottom, wherein the waveguide is ridge shaped for light conduction, comprising a wedge-shaped output terminal, wherein: through the wedge-shaped output terminal of the waveguide, light is vertically injected into the two-dimensional material layer and the porous structure layer modified with the quantum dots. By integrating the waveguide and the optoelectronic memristor, the present invention obtains the highly controlled characteristics with high alignment and confinement for light effect on the device and has advantages in realizing optoelectronic synergy in the optoelectronic synaptic memristors.

Abstract: A heat pipe including a pipe body, a first capillary structure and a second capillary structure. The pipe body has an evaporation portion and a condensation portion. The condensation portion is connected to the evaporation portion. The first capillary structure is disposed in the evaporation portion. The second capillary structure is disposed in the condensation portion and is connected to an end of the condensation portion that is located away from the evaporation portion. The second capillary structure is not in direct contact with the first capillary structure.