利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

6 条记录 (耗时 0.008 秒)

    SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES
    2.
    发明公开
    SYSTEMS AND METHODS FOR IDENTIFYING AND ANALYZING RISK EVENTS FROM DATA SOURCES 审中-公开

    公开(公告)号：EP4432182A1

    公开(公告)日：2024-09-18

    申请号：EP24151060.1

    申请日：2024-01-09

    申请人： Tata Consultancy Services Limited

    发明人： NJELITA, CHARLES ,  KHATUA, SUKADEV ,  LING, YIBEI

    IPC分类号： G06Q10/0635 ,  G06F16/35 ,  G06F40/284 ,  G06F40/30

    CPC分类号： G06Q10/0635 ,  G06F40/284 ,  G06F40/30 ,  G06F16/353

    摘要： Conventional methods of analyzing social media content involves performing sentimental analysis to understand related sentiment and effects of events on communities. However, such analysis may not be completely accurate and are prone to errors. Present disclosure provides system and method that identify and analyze risk events from data collected from various sources. Key phrases obtained from sources is received, pre-processed, and clustered accordingly. The clustering is performed based on frequency of incoming words. The clustered dataset obtained is classified into one or more categories based on a polarity score. Dataset of specific category (e.g., negative category dataset) is analysed to identify events and topics which are then grouped using an associated label to obtain grouped entities. Each entity is then ranked and assigned a risk score for identifying high-risk events which are then analyzed using simulation and optimization technique(s) and an explainability text for the analyzed risk events is generated.

    Systems and methods for identifying associations between malware samples
    4.
    发明公开
    Systems and methods for identifying associations between malware samples 有权
    用于识别恶意软件样本之间关联的系统和方法

    公开(公告)号：EP2560120A2

    公开(公告)日：2013-02-20

    申请号：EP12180484.3

    申请日：2012-08-14

    申请人： Verisign, Inc.

    发明人： Sinclair, Gregory ,  Olson, Ryan ,  Falcone, Robert

    IPC分类号： G06F21/00 ,  G06F17/30

    CPC分类号： G06F21/565 ,  G06F16/338 ,  G06F16/35 ,  G06F16/353 ,  G06F16/38 ,  G06F16/907 ,  G06F21/564 ,  G06F2221/034 ,  G06Q10/10 ,  H04L51/12 ,  H04L63/1416 ,  H04L63/1441 ,  H04L63/145

    摘要： Systems and methods are disclosed for identifying associations between binary samples, such as e-mail files and their attachments or a document and an executable program associated with the document. In one implementation, the method includes receiving a plurality of binary samples, and extracting metadata from the plurality of binary samples. The metadata for a binary sample from the plurality of binary samples includes a set of attributes of the binary sample. The method further includes identifying a set of associations between the plurality of binary samples based on the extracted metadata. Each association is characterized by at least one attribute the associated binary samples have in common, and each association has a confidence level indicative of a strength of the association. The method also includes identifying associations with a confidence level that exceeds a predefined threshold.

    摘要翻译： 公开了用于识别诸如电子邮件文件及其附件或文档以及与文档相关联的可执行程序之间的关联的系统和方法。 在一个实现中，该方法包括接收多个二进制样本，并从多个二进制样本中提取元数据。 来自多个二进制样本的二进制样本的元数据包括二进制样本的一组属性。 该方法进一步包括基于所提取的元数据来识别多个二进制样本之间的一组关联。 每个关联的特征在于至少一个相关联的二进制样本具有共同的属性，并且每个关联具有指示关联的强度的置信度。 该方法还包括识别具有超过预定义阈值的置信度的关联。

    Categorizing data sets
    6.
    发明公开
    Categorizing data sets 有权
    Klassifizierung von Datensets

    公开(公告)号：EP2595065A1

    公开(公告)日：2013-05-22

    申请号：EP11189099.2

    申请日：2011-11-15

    申请人： Kairos Future Group AB

    发明人： Larsson, Tomas ,  Lindgren, Mats

    IPC分类号： G06F17/30 ,  G06Q30/00

    CPC分类号： G06F16/24578 ,  G06F16/3346 ,  G06F16/35 ,  G06F16/353 ,  G06F16/355 ,  G06F16/358 ,  G06F16/36 ,  G06F16/367 ,  G06F16/38 ,  G06F16/93

    摘要： A device for categorizing data sets obtained from a number of sources comprises a symbol frequency determining unit (24) that determines the frequency of appearance of symbols in a first collection of data sets and the frequency of appearance of symbols in a second collection of data sets, a significance determining unit (26) that determines the most significant symbols for the second collection based on the frequency of appearance in the first collection and the frequency of appearance in the second collection, a grouping unit (28) that groups the most significant symbols into groups according to their appearance in the same data set and a ranking unit (30) that ranks the data sets in relation to the symbol groups according to a ranking scheme.

    摘要翻译： 用于对从多个源获得的数据集进行分类的装置包括符号频率确定单元（24），其确定数据集的第一集合中的符号的出现频率以及在第二数据集合集合中出现符号的频率 ，基于所述第一集合中出现的频率和所述第二集合中出现的频率来确定所述第二集合的最高有效符号的重要性确定单元（26），分组单元（28），其对所述最重要符号 根据它们在相同数据集中的出现以及根据排名方案对与符号组相关的数据集进行排序的排名单元（30）进行分组。