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1. 发明授权

US11546359B2 Multidimensional clustering analysis and visualizing that clustered analysis on a user interface 有权
公开(公告)号：US11546359B2
公开(公告)日：2023-01-03
申请号：US16278920
申请日：2019-02-19
申请人： Darktrace Limited
发明人： Jack Stockdale , David Palmer
IPC分类号： H04L9/40 , G06N20/10 , G06N20/00 , G06F21/36 , H04L43/045 , G06F16/2455 , G06F3/04842 , G06F3/0486 , H04L41/22 , G06K9/62 , G06F40/40 , G06V30/10 , H04L51/42 , H04L51/212 , H04L51/224 , G06F21/55 , G06N20/20
摘要： Embodiments of a cyber threat defense system protects a system from cyber threats with the following operations: Identifying unusual patterns of behavior within the plotted individual alerts and/or events in the multiple dimension space; Clustering the individual alerts and events that form the unusual pattern into a distinct item for cyber threat analysis of that cluster of distinct alerts and/or events; Applying machine learning models to infer for the cyber threat analysis what is possibly happening with the distinct item of the cluster, which came from the unusual pattern, and then assign a threat risk associated with that distinct item of the cluster; and Projecting on a user interface, based on the analysis by the one or more machine learning models, the assigned threat risk associated with that distinct item of the cluster of alerts and/or events forming the unusual pattern.

2. 发明授权

US11522887B2 Artificial intelligence controller orchestrating network components for a cyber threat defense 有权
公开(公告)号：US11522887B2
公开(公告)日：2022-12-06
申请号：US16279067
申请日：2019-02-19
申请人： Darktrace Limited
发明人： Matthew Dunn
IPC分类号： H04L29/06 , G06N20/10 , H04L9/40 , G06N20/00 , G06F21/36 , H04L43/045 , G06F16/2455 , G06F3/04842 , G06F3/0486 , H04L41/22 , G06K9/62 , G06F40/40 , G06V30/10 , H04L51/42 , H04L51/212 , H04L51/224 , G06N20/20
摘要： A cyber-threat coordinator-component identifies devices and/or users that are in a breach state of a benchmark of parameters, utilized by AI models, that correspond to the normal pattern of life for the network. The cyber-threat coordinator-component sends an external communication to selected network devices in order to initiate actions with that network device in order to change a behavior of a detected threat of at least one a user and/or a device acting abnormal to the normal pattern of life on the network. The initiated actions are also targeted to minimize an impact on other network devices and users that are i) currently active in the network and ii) that are not in breach of being outside the normal behavior benchmark.

3. 发明授权

US11580344B2 Authentication apparatus, system and methods using unclonable identifiers 有权
公开(公告)号：US11580344B2
公开(公告)日：2023-02-14
申请号：US16497098
申请日：2018-03-27
申请人： SRI International
发明人： Sterling E. McBride , Michael G. Kane , Alex Krasner , Richard Sita , Winston K. Chan , Mark F. Schutzer
IPC分类号： G06F13/42 , G06K19/07 , G06K19/073 , G06K19/077 , H04L9/08 , H04L9/32 , G06V20/80
摘要： An integrated circuit having Radio Frequency Identification components and circuitry used for authentication is discussed. The RFID components and circuitry include two or more coils and corresponding electrical circuits that are tuned to use two or more different resonant frequencies including: a first resonant RF used for power generation and a second resonant RF used for data communication. The integrated circuit contains a unique signature that is used for the authentication with two or more aspects including i) a first aspect that is a programmed password in a memory embedded on the integrated circuit, and ii) a second aspect that is a unique, randomly generated code based upon a physical characteristic of the integrated circuit.

4. 发明授权

US11477222B2 Cyber threat defense system protecting email networks with machine learning models using a range of metadata from observed email communications 有权
公开(公告)号：US11477222B2
公开(公告)日：2022-10-18
申请号：US16732644
申请日：2020-01-02
申请人： Darktrace Limited
发明人： Matthew Dunn , Matthew Ferguson , Stephen Pickman
IPC分类号： H04L9/40 , G06N20/00 , H04L101/37
摘要： A cyber-threat defense system for a network including its email domain protects this network from cyber threats. Modules utilize machine learning models as well communicate with a cyber threat module. Modules analyze the wide range of metadata from the observed email communications. The cyber threat module analyzes with the machine learning models trained on a normal behavior of email activity and user activity associated with the network and in its email domain in order to determine when a deviation from the normal behavior of email activity and user activity is occurring. A mass email association detector determines a similarity between highly similar emails being i) sent from or ii) received by a collection of two or more individual users in the email domain in a substantially simultaneous time frame. Mathematical models can be used to determine similarity weighing in order to derive a similarity score between compared emails.

5. 发明授权

US11477219B2 Endpoint agent and system 有权
公开(公告)号：US11477219B2
公开(公告)日：2022-10-18
申请号：US16279039
申请日：2019-02-19
申请人： Darktrace Limited
发明人： Thomas Jenkinson , David Sansom , Maximilian Heinemeyer , Jack Stockdale
IPC分类号： H04L9/40 , G06F21/36 , G06N20/10 , G06N20/00 , H04L43/045 , G06F16/2455 , G06F3/04842 , G06F3/0486 , H04L41/22 , G06K9/62 , G06F40/40 , G06V30/10 , H04L51/42 , H04L51/212 , H04L51/224 , G06N20/20
摘要： The endpoint agent detects a cyber threat on an end-point computing device. The endpoint agent on the computing device has a communications module that communicates with a cyber defense appliance. A collections module monitors and collects pattern of life data on processes executing on the end-point computing-device and users of the end-point computing-device. The communications module sends the pattern of life data to the cyber defense appliance installed on a network. The cyber defense appliance at least contains one or more machine-learning models to analyze the pattern of life data for each endpoint agent connected to that cyber defense appliance. The endpoint agent and the cyber defense appliance may trigger one or more actions to be autonomously taken to contain a detected cyber threat when a cyber-threat risk score is indicative of a likelihood of a cyber-threat is equal to or above an actionable threshold.

6. 发明授权

US11470103B2 Anomaly alert system for cyber threat detection 有权
公开(公告)号：US11470103B2
公开(公告)日：2022-10-11
申请号：US16878347
申请日：2020-05-19
申请人： Darktrace Limited
发明人： Tom Dean , Jack Stockdale
IPC分类号： H04L9/40 , G06F21/55
摘要： Disclosed herein is a method for use in detection of anomalous behavior of a device of a computer system. The method is arranged to be performed by a processing system. The method includes deriving values, m1, . . . , mN, of a metric, M, representative of data associated with the device; modeling a distribution of the values; and determining, in accordance with the distribution of the values, the probability of observing a more extreme value of the metric than a given value, m, of the metric, wherein the probability is used to determine whether the device is behaving anomalously. Also disclosed is an equivalent computer readable medium and anomalous behavior detection system.

7. 发明授权

US11461643B2 Deep adaptive semantic logic network 有权
公开(公告)号：US11461643B2
公开(公告)日：2022-10-04
申请号：US16611177
申请日：2018-05-08
申请人： SRI International
发明人： John Byrnes , Richard Rohwer
IPC分类号： G06N3/08 , G06F16/242 , G06F16/22 , G06N3/04 , G06Q10/10
摘要： An artificial intelligence engine that has two or more modules cooperating with each other in order to create one or more machine learning models that use an adaptive semantic learning for knowledge representations and reasoning. The modules cause encoding the representations and reasoning from one or more sources in a particular field with terminology used by one or more human sources in that field into a set of rules that act as constraints and that are graphed into a neural network understandable by a first machine learning model, and then ii) adapting an interpretation of that set of encoded rules. The understanding of that set of encoded rules is adapted by i) allowing for semantically similar terms and ii) by conclusions derived from training data, to create an understanding of that set of encoded rules utilized by the machine learning model and the AI engine.

8. 发明授权

US11457030B2 Artificial intelligence researcher assistant for cybersecurity analysis 有权
公开(公告)号：US11457030B2
公开(公告)日：2022-09-27
申请号：US16278957
申请日：2019-02-19
申请人： Darktrace Limited
发明人： Dickon Humphrey , David Palmer
IPC分类号： H04L9/40 , G06N20/10 , G06F21/55 , G06F40/40 , G06N20/00 , G06N20/20 , G06F21/36 , H04L43/045 , G06F16/2455 , G06F3/04842 , G06F3/0486 , H04L41/22 , G06K9/62 , G06V30/10 , H04L51/42 , H04L51/212 , H04L51/224
摘要： A cyber threat defense system can autonomously gather research data about external hosts visited by a network entity and present that information in a format integrated with a threat-tracking graphical user interface. A collation module can collect input data from the network entity. A cyber threat module can identify a cyber threat from the input data. A host module can determine at least one host metric for an external host in the input data based on the identified cyber threat. A researcher module can collect host research data describing the external host. A scoring module can analyze the host research data using the at least one host metric. The scoring module can generate an automatic threat score describing a threat level presented by the external host. A user interface module can present a threat-tracking graphical user interface displaying the automatic threat score.

9. 发明授权

US08229743B2 Speech recognition system 有权
标题翻译：语音识别系统
公开(公告)号：US08229743B2
公开(公告)日：2012-07-24
申请号：US12489786
申请日：2009-06-23
申请人： David Carter , Mahapathy Kadirkamanathan
发明人： David Carter , Mahapathy Kadirkamanathan
IPC分类号： G10L15/00
CPC分类号： G10L15/065 , G10L15/197
摘要： Various methods and apparatus are described for a speech recognition system. In an embodiment, the statistical language model (SLM) provides probability estimates of how linguistically likely a sequence of linguistic items are to occur in that sequence based on an amount of times the sequence of linguistic items occurs in text and phrases in general use. The speech recognition decoder module requests a correction module for one or more corrected probability estimates P′(z|xy) of how likely a linguistic item z follows a given sequence of linguistic items x followed by y, where (x, y, and z) are three variable linguistic items supplied from the decoder module. The correction module is trained to linguistics of a specific domain, and is located in between the decoder module and the SLM in order to adapt the probability estimates supplied by the SLM to the specific domain when those probability estimates from the SLM significantly disagree with the linguistic probabilities in that domain.
摘要翻译：描述了用于语音识别系统的各种方法和装置。在一个实施例中，统计语言模型（SLM）基于语言项目序列出现在通常使用的文本和短语中的次数，提供语言序列在该序列中如何语言上可能发生的概率估计。语音识别解码器模块向修正模块请求一个或多个校正概率估计P'（z | xy），语言项目z在给定的语言项目序列x之后跟随y，其中（x，y和z））是从解码器模块提供的三个可变语言项目。校正模块被训练成特定领域的语言学，并且位于解码器模块和SLM之间，以便当来自SLM的概率估计显着不同于语言学时，将SLM提供的概率估计值适应于特定领域该领域的概率。

10. 发明授权

US08190420B2 Automatic spoken language identification based on phoneme sequence patterns 有权
标题翻译：基于音素序列模式的自动口语识别
公开(公告)号：US08190420B2
公开(公告)日：2012-05-29
申请号：US12535038
申请日：2009-08-04
申请人： Mahapathy Kadirkamanathan , Christopher John Waple
发明人： Mahapathy Kadirkamanathan , Christopher John Waple
IPC分类号： G06F17/20
CPC分类号： G10L15/187 , G10L15/005
摘要： A language identification system that includes a universal phoneme decoder (UPD) is described. The UPD contains a universal phoneme set representing both 1) all phonemes occurring in the set of two or more spoken languages, and 2) captures phoneme correspondences across languages, such that a set of unique phoneme patterns and probabilities are calculated in order to identify a most likely phoneme occurring each time in the audio files in the set of two or more potential languages in which the UPD was trained on. Each statistical language models (SLM) uses the set of unique phoneme patterns created for each language in the set to distinguish between spoken human languages in the set of languages. The run-time language identifier module identifies a particular human language being spoken by utilizing the linguistic probabilities supplied by the one or more SLMs that are based on the set of unique phoneme patterns created for each language.
摘要翻译：描述了包括通用音素解码器（UPD）的语言识别系统。 UPD包含一个通用音素集合，表示1）所有发音在两组或多种语言中的音素，以及2）跨语言捕获音素对应，以便计算一组独特的音素模式和概率，以便识别最有可能在音频文件中出现的两种或多种潜在语言的UPD被训练的音频文件中。每个统计语言模型（SLM）使用为集合中的每种语言创建的一组独特的音素模式，以区分该语言集中的口语人类语言。运行时语言标识符模块通过利用由基于为每种语言创建的唯一音素模式的集合的一个或多个SLM提供的语言概率来识别正在说出的特定人类语言。

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