Abstract: An efficient K-nearest neighbor (KNN) method for a single-frame point cloud of a LiDAR and an application of the efficient KNN method for the single-frame point cloud of the LiDAR are provided, where the efficient KNN method for the single-frame point cloud of the LiDAR is accelerated by a field-programmable gate array (FPGA). In the efficient KNN method for the single-frame point cloud of the LiDAR, a data structure is established based on point cloud projection and a distance scale. The data structure ensures that adjacent points in space are organized in adjacent memories. A new data structure is efficiently constructed. An efficient nearest point search mode is provided.

Abstract: An image transform model and an image recovery model in the present disclosure are trained to obfuscate hidden malicious payloads in original images and recover the original images from the obfuscated/transformed images, respectively. The image transform model is trained on known malicious images as an ensemble with an adversarial discriminator that predicts whether malicious payloads are recoverable from transformed images output by the image transform model. The trained image transform model is then fixed and used to generate transformed images from the known malicious images, and the transformed images are used as training data for the image recovery model to recover the corresponding (original) known malicious images.

Abstract: The present disclosure provides a display panel, including a display area and a bezel area surrounding the display area, edge lines of the display area and the bezel area are arc edge lines and matched with each other in shape, the display panel includes a peripheral circuit and peripheral signal lines, which are distributed in the bezel area, and further includes an array substrate and a color filter substrate, which are not overlapped at edges thereof on a first side, and in a portion of the bezel area where the edges on the first side are not located, a distance between the peripheral signal line, closest to an outer edge of the bezel area, and the outer edge of the bezel area is in a range of 0.35±0.2 micrometers, the outer edge of the bezel area is an edge of the bezel area away from the display area.

Abstract: A system has been designed for inline detection of various cybersecurity attacks in network traffic delineated based on patterns detected in payloads of protocol data units (PDUs) of the network traffic. Patterns of the various attacks are distributed across points of network traffic inspection for inline detection, such as firewalls, of the patterns in payloads. If a pattern is detected, then an analyzer corresponding to the suspected attack is invoked and provided the suspicious payload. The analyzers can be provided as cloud-based services. The patterns and analyzers have been created for inline detection of insecure deserialization, malicious XML, XSS attacks, and XXE attacks. Each of these is referred to herein as a detector: insecure deserialization detector, malicious XML detector, XSS attack detector, and XXE attack detector.

Abstract: A traffic filter executing as part of a cybersecurity appliance detects network traffic that includes XML files. The traffic filter forwards the XML file identified in the network traffic to a malicious XML detector for further analysis. The detector heuristically analyzes the XML header and analyzes the XML document with a combination of heuristic analysis and deep learning. The detector analyzes the XML header with heuristics-based rules. The detector also analyzes the XML document using additional heuristics-based rules and/or with a model trained to predict whether XML documents are malicious. If the results of the analyses yields a verdict that the XML document is malicious, the detector returns a verdict indicating that the XML file is malicious to the traffic filter for the malicious XML file to be blocked accordingly.

Abstract: An artificial intelligence ensemble has been developed for XSS detection with high accuracy. The artificial intelligence ensemble is created with a deep learning model and a machine learning model, each trained on different perspectives of token sequences extracted from packet payloads. Pre-processing of the raw data (i.e., the packet payload) generates a sequence of tokens that represents the payload and then generates a sequence of abstract tokens from the sequence of tokens. The deep learning model is trained on abstract token sequences to detect XSS from the perspective of patterns of token sequences. The other model is trained on pattern-based features extracted from the sequence of tokens to detect XSS from the perspective of features corresponding to characteristics of tokens sequences corresponding to heuristics gleaned for XSS. After each model is trained, the models are combined and deployed for inline detection of XSS in payload traffic from the different perspectives.

Abstract: A security feed normalizer aggregates and normalizes threat intelligence data across security feeds and extracts threat descriptors of cybersecurity threats from the aggregated/normalized data. A first large language model (LLM) determines whether each threat descriptor is informative, i.e., comprises sufficient information for reproducing/generating network traffic of the corresponding cybersecurity threat. For informative threat descriptors, a second LLM generates network traffic for the corresponding cybersecurity threats. The generated network traffic is used for subsequent remediation of corresponding threats.

Abstract: A prompt generator receives descriptive data for a plug-in of a custom or open-source security testing tool. The prompt generator chooses a prompt template corresponding to the type of descriptive data and the security testing tool. For an open-source security testing tool, the prompt generator populates the prompt template with the descriptive data and prompts an open-source large language model (LLM) with the populated prompt to generate the plug-in for the open-source security testing tool. For a custom security testing tool, the prompt generator populates the prompt template with the descriptive data or an existing open source plugin, and prompts a custom LLM with the populated prompt to generate the plug-in for the custom security testing tool.

Abstract: Vulnerable program code generated by a language model is detected inline. A detection service monitors for and intercepts network traffic of a language model. For responses from the language model that include generated program code, the detection service extracts the program code and determines a programming language to which the program code corresponds. The detection service employs machine learning-based and/or rule-based vulnerability detection techniques to determine whether the program code comprises any vulnerabilities. If the program code is determined to comprise a vulnerability, the detection service can block transmission of the response comprising the program code to its destination or communicate an alert with the response indicating that the program code is vulnerable to prevent inclusion of the vulnerable program code in a software project.

Abstract: A display substrate and a display device. The display substrate includes: a first base substrate, including a display region, a first peripheral region; a signal line group, including signal lines. The signal lines includes first and second signal lines. The signal line group includes a first region and a second region arranged in an extension direction of the signal line group. The number of signal lines in the first region is greater than the number of signal lines in the second region. In the first region, orthographic projections of the first signal lines overlaps orthographic projections of the second signal lines on the first base substrate. In the second region, the first and second signal lines are alternately arranged. The first region includes sub-regions.

Abstract: A plurality of Common Vulnerabilities and Exposures (CVEs) is obtained. The CVEs are pre-processed in part by extracting information from the plurality of CVEs to generate a training dataset. One or more pre-trained large language models (LLMS) are fine-tuned using a balanced version of the training dataset.

Abstract: Vulnerable program code generated by a language model is detected inline. A detection service monitors for and intercepts network traffic of a language model. For responses from the language model that include generated program code, the detection service extracts the program code and determines a programming language to which the program code corresponds. The detection service employs machine learning-based and/or rule-based vulnerability detection techniques to determine whether the program code comprises any vulnerabilities. If the program code is determined to comprise a vulnerability, the detection service can block transmission of the response comprising the program code to its destination or communicate an alert with the response indicating that the program code is vulnerable to prevent inclusion of the vulnerable program code in a software project.

Abstract: Vulnerable program code generated by a language model is detected inline. A detection service monitors for and intercepts network traffic of a language model. For responses from the language model that include generated program code, the detection service extracts the program code and determines a programming language to which the program code corresponds. The detection service employs machine learning-based and/or rule-based vulnerability detection techniques to determine whether the program code comprises any vulnerabilities. If the program code is determined to comprise a vulnerability, the detection service can block transmission of the response comprising the program code to its destination or communicate an alert with the response indicating that the program code is vulnerable to prevent inclusion of the vulnerable program code in a software project.

Abstract: The present disclosure provides a display method, apparatus, computer device and storage medium, wherein the method comprises: in response to a trigger operation for any of book recommendation topics, acquiring a plurality of topic posts under the book recommendation topic, and target filtering items matching the topic posts; wherein the target filtering items are determined based on book recommendation information of the topic posts and book information recommended in the topic posts; displaying the target filtering items; and in response to one of the target filtering items being selected, displaying topic posts associated with the one of the target filtering items.

Abstract: A display panel includes an active area and a border-frame area located at a periphery of the active area, the active area includes a plurality of sub-pixels and a plurality of data lines connected to the sub-pixels, and the border-frame area includes a testing area and a bonding area; the testing area includes a plurality of testing units that are arranged periodically in a first direction, each of the testing units includes one or more switching transistors, a first electrode of each of the switching transistors is connected to a testing-signal lead wire, and a second electrode is connected to one of the data lines; the bonding area includes a plurality of bonding units that are arranged periodically in the first direction, each of the bonding units includes one or more bonding pads, and each of the bonding pads is connected to one of the data lines.

Abstract: An array base plate includes a substrate; a first conducting layer located at one side of the substrate, and including a plurality of data lines arranged in an array; a second conducting layer in direct contact with a part of a region of the first conducting layer, and including a pixel electrode and a compensating electrode; wherein an orthographic projection of the compensating electrode on the substrate is located within orthographic projections of the data lines on the substrate. The array base plate further comprises transistor, the first conducting layer further comprises a first electrode of the transistor and a second electrode of the transistor, the pixel electrode is in direct contact with a part of a region of the first electrode of the transistor, and the data lines are connected to the second electrode of the transistor.

Abstract: A context-based cyberattack signature generation system (“signature generation system”) disclosed herein comprises a signature prompt schema for generating prompts to a language model that generates cyberattack signatures. The signature prompt schema comprises a description of syntax for the cyberattack signatures and descriptions of case knowledge and domain knowledge for a type of cyberattack corresponding to a cyberattack signature. The signature generation system tests cyberattack signatures generated with the signature prompt schema against minimum signature conditions and traffic with ground-truth malicious/benign labels. Once the signature prompt schema passes the tests, the signature generation system deploys the tested signature prompt schema in combination with the language model for cyberattack signature generation.

Abstract: Provided are text content presentation method and apparatus, computing device and storage medium. The method comprises: acquiring a text to be presented that comprises multiple pieces of text contents, and a target reading auxiliary text corresponding to at least one piece of target text content among the multiple pieces of text content; and in response to presenting the target text content on a reading page, presenting, in a first area of the reading page, the target reading auxiliary text corresponding to the target text content, wherein the position of the first area in the reading page is related to the position of the target text content in the reading page.

Abstract: The present application provides an array base plate and a method for manufacturing the same, a display panel, the array base plate including a substrate; a first conducting layer located at one side of the substrate, and including a plurality of data lines arranged in an array; a second conducting layer located at one side of the first conducting layer away from the substrate, and in direct contact with a part of a region of the first conducting layer, and including a pixel electrode and a compensating electrode; wherein an orthographic projection of the compensating electrode on the substrate is located within orthographic projections of the data lines on the substrate. The embodiments of the present application provide an array base plate with low cost, high preparation yield, and good reliability.