Abstract: A set of data packets transmitted by an IoT device is received at a system. At least one packet included in the set of data packets is analyzed. An Authentication, and Account (AAA) message, including contextual information associated with the IoT device, is transmitted on behalf of the IoT device.

Abstract: A first device governs operation of a second device based on a network security risk posed by the second device. The second device is disposed locally to the first device and in local network communication with the first device. The first device is in network communication with a cloud-based computational service.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. A first set of raw events associated with a first IoT device is identified, including a transmission made by the first IoT device. A communication manner of the first IoT device is determined, based at least in part on a communication manner of the first IoT device. The first set of raw events over the first time period is examined to generate one or more formatted events of the first IoT device. The formatted events are used to extract a set of features. Similar processing is performed with respect to a second IoT device. A context-based IoT device grouping model is generated based on at least one of: (1) the features extracted for the first IoT device or (2) the features extracted for the second IoT device. The model is applied to determine that a third IoT device belongs to a particular group. A deviation by the third IoT device from group behavior is detected and an alert is generated in response.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. A set of raw events associated with a first IoT device is identified. A context of the first IoT device is identified, and used to enrich at least some of the raw events. At least some of the raw events are aggregated. A context-based IoT device grouping model is generated based at least in part on the aggregated events and events associated with a second IoT device in operation. The model is applied to determine that a third IoT device belongs to a particular group. A deviation by the third IoT device from group behavior is detected and an alert is generated in response.

Abstract: The present disclosure provides a quantitative accuracy evaluation method and system for a result of remote sensing inversion. The method includes the following steps: acquiring measured data of a target element content in a preset zone; acquiring, based on acquired remote sensing image reflectivity of the preset zone, predicted data of the target element content in the preset zone by a remote sensing inversion model; and conducting comprehensive index evaluation of abnormal feature similarity between the measured data and the predicted data. The technical solution adopted in the present disclosure can solve the problem with quantitative accuracy evaluation of remote sensing inversion that inverted object content and measured object content are distributed inconsistently in space.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. A set of raw events associated with a first IoT device is identified. A context of the first IoT device is identified, and used to enrich at least some of the raw events. At least some of the raw events are aggregated. A context-based IoT device grouping model is generated based at least in part on the aggregated events and events associated with a second IoT device in operation. The model is applied to determine that a third IoT device belongs to a particular group. A deviation by the third IoT device from group behavior is detected and an alert is generated in response.

Abstract: An electrical connector assembly includes: a printed circuit board; an electrical connector seated upon the printed circuit board; an electronic package coupled to the electrical connector; a frame structure affixed to the printed circuit board; a metallic securing seat affixed to the frame structure and having plural securing posts; a heat sink positioned upon the electronic package and having plural through holes aligned with the securing posts; plural fasteners each extending through a corresponding through hole to engage a corresponding securing post and plural springs each compressed between an associated fastener and the heat sink; and a retention member mounted to a corresponding securing post for engaging the heat sink, wherein the retention member has a mounting part and a latching part pivoted to the mounting part.

Abstract: A first device governs operation of a second device based on a network security risk posed by the second device. The second device is disposed locally to the first device and in local network communication with the first device. The first device is in network communication with a cloud-based computational service.

Abstract: Techniques for passively providing Authentication, Authorization, and Accounting (AAA) support for an IoT device in a network are disclosed. A set of data packets transmitted by an IoT device is received. At least one packet included in the set of data packets is analyzed. An AAA message, including contextual information associated with the IoT device, is transmitted on behalf of the IoT device.

Abstract: Techniques for passively providing AAA support for an IoT device in a network are disclosed. A set of data packets transmitted by an IoT device is obtained. At least one packet included in the set of data packets is analyzed. A message, including information associated with the IoT device, is transmitted on behalf of the IoT device.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. A set of raw events associated with a first IoT device is identified. A context of the first IoT device is identified, and used to enrich at least some of the raw events. At least some of the raw events are aggregated. A context-based IoT device grouping model is generated based at least in part on the aggregated events and events associated with a second IoT device in operation. The model is applied to determine that a third IoT device belongs to a particular group. A deviation by the third IoT device from group behavior is detected and an alert is generated in response.

Abstract: An Internet of Things (IoT) device profile applicable to an IoT device is determined. Data packets transmitted to and from the IoT device are analyzed. A risk level of the IoT device is determined based at least in part on the data packet analysis. A determination is made that the risk level exceeds a threshold and a remedial action is taken in response.

Abstract: A fastening mechanism for retaining a heat sink upon the CPU includes a fastening seat surrounding the connector, and a pair of fastening clips. The fastening seat includes four alignment posts at four corners, and the pair of fastening clips are attached at two corresponding diagonal corners. Each fastening clip includes a mounting section secured to the corresponding post, a latching section for temporarily holding the heat sink, and a resilient arm for upwardly urging the heat sink. Each alignment post is equipped with a screw nut and a coil spring so as to reinforce the downward pressing forces against the heat sink for assuring reliable connection between the CPU and the contacts of the electrical connector for better electrical transmission and intimate contact between the CPU and the heat sink for efficient heat dissipation.

Abstract: Techniques for assessing risks of IoT devices. A system utilizing such techniques can include a packet analysis based IoT device risk assessment system and an IoT device risk assessment system. A method utilizing such techniques can include extraction of IoT device risk factors from a device profile of an IoT device and application of assessment weights to the IoT device risk factors to assess a risk level of an IoT device.

Abstract: Techniques for grouping and labeling Internet of Things (IoT) devices are disclosed. In accordance with an aspect of the invention, there is provided a computer program product configured to be operable to perform the techniques described in this paper to enable grouping and labeling of IoT devices. As devices are grouped and labeled, and behavior is matched to or deviates from known or expected behavior, the network can be more readily understood and alerts can be more timely and appropriate.

Abstract: A method for forming a sensor with increased overhang to prevent passivation stress fractures is provided. Embodiments include forming a first passivation layer over a dielectric layer patterned over a first top metal layer of a logic region of a sensor and a second top metal layer of an array region of the sensor; planarizing the first passivation layer and the dielectric layer to form a level surface above the first top metal layer and the second top metal layer; etching the dielectric layer to form a pad opening in the array region of the sensor based on a predetermined overhang value, the pad opening exposing a portion of the surface of the second top metal layer; and forming a second passivation layer over the level surface and the pad opening in the array region.

Abstract: A state space controller includes an integral part configured to integrate a control deviation, wherein the control deviation indicates a difference between a digital value of a gradient coil current and a reference current; a delay compensator configured to generate a digital control amount according to the integrated control deviation by the integral part, and generated a pulse-width modulation drive signal according to the digital control amount, and includes a subtractor of which a non-inverting input terminal is connected to an output terminal of the integral part, a delayer configured to delay the digital control amount by one calculation cycle, and a first feedback loop configured to delay the digital control amount by one calculation cycle and multiply a first compensation coefficient to obtain a first compensation amount, wherein the first compensation amount is input into a first inverting input terminal of the subtractor.

Abstract: Kirigami-based optic devices are provided that include a tunable kirigami-based component comprising a plurality of bridge structures and a plurality of openings therebetween to form a grating structure. At least one surface of the kirigami-based component is micropatterned with a plasmonic material so that the grating is configured to induce or modulate rotational polarity of a beam of electromagnetic radiation as it passes through the plurality of openings. In certain aspects, the micropattern may be a gold herringbone pattern. The kirigami-based component has tunable 3D topography, which when stretched, exhibits polarization rotation angles as high as 80° and ellipticity angles as high as 34° due to the topological equivalency of helix.

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.