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公开(公告)号：US20240396905A1
公开(公告)日：2024-11-28
申请号：US18763984
申请日：2024-07-03
Applicant: SAP SE
Inventor： Laurent Y. Gomez , Cedric R.J. Hebert , Slim Trabelsi
Abstract: In an example embodiment, a combination of machine learning and rule-based techniques are used to automatically detect social engineering attacks in a computer system. More particularly, three phases of detection are utilized on communications in a thread or stream of communications: attack contextualization, intention classification, and security policy violation detection. Each phase of detection causes a score to be generated that is reflective of the degree of danger in the thread or stream of communications, and these scores may then be combined into a single global social engineering attack score, which then may be used to determined appropriate actions to deal with the attack if it transgresses a threshold.
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公开(公告)号：US12001530B2
公开(公告)日：2024-06-04
申请号：US17668208
申请日：2022-02-09
Applicant: SAP SE
Inventor： Rocio Cabrera Lozoya , Slim Trabelsi , Carlos Rafael Ocanto Davila
IPC: G06F21/00 , G06F21/31 , G06F40/253 , G06F40/263 , G06F40/40
CPC classification number: G06F21/31 , G06F40/253 , G06F40/263 , G06F40/40
Abstract: In an example embodiment, an efficient, automated method to generate password guesses is provided by leveraging online text sources along with natural language processing techniques. Specifically, semantic structures in passwords are exploited to aid system in generating better guesses. This not only helps cover instances where traditional password meters would indicate a password is safe when it is not, but also makes the solution robust against fast-evolving domains such as new slang in natural languages or new vocabulary arising from new products, product updates, and services.
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公开(公告)号：US20230046392A1
公开(公告)日：2023-02-16
申请号：US17401873
申请日：2021-08-13
Applicant: SAP SE
Inventor： Laurent Y. Gomez , Cedric R.J. Hebert , Slim Trabelsi
Abstract: In an example embodiment, a combination of machine learning and rule-based techniques are used to automatically detect social engineering attacks in a computer system. More particularly, three phases of detection are utilized on communications in a thread or stream of communications: attack contextualization, intention classification, and security policy violation detection. Each phase of detection causes a score to be generated that is reflective of the degree of danger in the thread or stream of communications, and these scores may then be combined into a single global social engineering attack score, which then may be used to determined appropriate actions to deal with the attack if it transgresses a threshold.
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公开(公告)号：US10003578B2
公开(公告)日：2018-06-19
申请号：US15340781
申请日：2016-11-01
Applicant: SAP SE
Inventor： Slim Trabelsi
CPC classification number: H04L63/0421 , G06F21/602 , G06F21/606 , G06F2221/2107 , H04L9/0894 , H04L9/321 , H04L63/0471 , H04L2209/42
Abstract: Anonymity and confidentiality of information published from a microblogging platform, are preserved using randomly chosen relays (not related to the publisher account) in order to hide content in the cloud of published messages. The information can be relayed in clear text or in encrypted format. Additional linked relays may be used to overcome character number limitations imposed by the microblogging platform, with the longer full text of the original message reconstructed at the conclusion of the process. Depending upon the desired degree of confidentiality, complexity of the relay combination can be adjusted, and the path secretly shared among sender and authorized recipient. Only authorized recipient(s) can obtain (through another platform) the path combination to reach the message. A trusted third party stores the path relays and authorizations to access the path. The confidential information that is to be shared, may remain on the microblogging platform spread randomly over anonymous accounts.
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公开(公告)号：US20240370741A1
公开(公告)日：2024-11-07
申请号：US18312287
申请日：2023-05-04
Applicant: SAP SE
Inventor： Sofiane Lounici , Slim Trabelsi
IPC: G06N5/022
Abstract: A machine learning model is watermarked through fairness bias. To do this, an original set of labeled data is obtained and clustered into a plurality of groups using a clustering algorithm. Labels for data in a subset of the groups are modified, inserting fairness bias into the subset. A machine learning model is trained based on the subset of data labeled using the modified labels and the original set of data outside of the subset labeled using the original set of labels. The machine learning model trained as such exhibits the fairness bias when classifying input data belonging to subset of the plurality of groups. A model exhibiting the fairness bias for input data belonging to the subset is a watermark of a machine learning model that was trained using the modified labels for the subset determined based on the subgroup algorithm. The watermark is usable to determine ownership.
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Patent Agency Ranking
公开(公告)号：US20240143797A1
公开(公告)日：2024-05-02
申请号：US17975290
申请日：2022-10-27
Applicant: SAP SE
Inventor： Slim Trabelsi , Marco Rosa
IPC: G06F21/60
CPC classification number: G06F21/604
Abstract: Techniques for automatically revoking leaked access credentials are disclosed. In some embodiments, a computer system may receive an indication that a credential for accessing a resource has been leaked, where the credential has been leaked by being included in content that has been published on an online service or has been stored in a shared folder of the online service. The computer system may then determine that the credential is effective in accessing the resource, and, in response to the determining that the credential is effective, trigger a revocation of the credential, the revocation of the credential causing the credential to no longer be effective in accessing the resource.
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公开(公告)号：US20180124022A1
公开(公告)日：2018-05-03
申请号：US15340781
申请日：2016-11-01
Applicant: SAP SE
Inventor： Slim Trabelsi
CPC classification number: H04L63/0421 , G06F21/602 , G06F21/606 , G06F2221/2107 , H04L63/0471 , H04L2209/42
Abstract: Anonymity and confidentiality of information published from a microblogging platform, are preserved using randomly chosen relays (not related to the publisher account) in order to hide content in the cloud of published messages. The information can be relayed in clear text or in encrypted format. Additional linked relays may be used to overcome character number limitations imposed by the microblogging platform, with the longer full text of the original message reconstructed at the conclusion of the process. Depending upon the desired degree of confidentiality, complexity of the relay combination can be adjusted, and the path secretly shared among sender and authorized recipient. Only authorized recipient(s) can obtain (through another platform) the path combination to reach the message. A trusted third party stores the path relays and authorizations to access the path. The confidential information that is to be shared, may remain on the microblogging platform spread randomly over anonymous accounts.
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公开(公告)号：US20170061133A1
公开(公告)日：2017-03-02
申请号：US14843482
申请日：2015-09-02
Applicant: SAP SE
Inventor： Slim Trabelsi
CPC classification number: G06F21/577 , G06F17/30864 , G06F2221/033 , H04L63/1433
Abstract: Embodiments automate tracking of exploit information related to initially-identified security vulnerabilities, through the data mining of social networks. Certain social network communities (e.g., those frequented by hackers) share information about computer security breaches (zero-day events). Embodiments recognize that further relevant security information may be revealed, in conjunction with and/or subsequent to such initial zero-day vulnerability disclosures. That additional information can include valuable details regarding known (or unknown) vulnerabilities, exploit codes and methodologies, patches, etc. Tracking that additional information can benefit security researchers/experts/law enforcement personnel. Embodiments monitoring social media traffic based upon initial security vulnerability information, perform analysis to detect patterns and create relevant keywords therefrom. Those keywords in turn form a basis for generating social media stream(s) responsible for harvesting additional security-relevant data. Results of further analysis of the social media stream can be fed back in an iterative manner to refine pattern detection, keyword creation, and media stream generation.
Abstract translation: 实施例通过社交网络的数据挖掘自动跟踪与初始识别的安全漏洞相关的利用信息。 某些社交网络社区（例如，黑客经常访问的社区）共享有关计算机安全漏洞（零日事件）的信息。 实施例认识到，与这种初始零日漏洞披露的结合和/或之后，可能会显示进一步的相关安全信息。 这些附加信息可以包括有关已知（或未知）漏洞，漏洞代码和方法，补丁等的有价值的细节。跟踪附加信息可以使安全研究人员/专家/执法人员受益。 基于初始安全漏洞信息监控社交媒体流量的实施例，执行分析以检测模式并从中创建相关关键字。 这些关键词又构成了生成社交媒体流的基础，负责收集额外的安全相关数据。 社会媒体流的进一步分析结果可以反复反馈，以改进模式检测，关键字创建和媒体流生成。
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公开(公告)号：US20240289427A1
公开(公告)日：2024-08-29
申请号：US18659463
申请日：2024-05-09
Applicant: SAP SE
Inventor： Rocio Cabrera Lozoya , Slim Trabelsi , Carlos Rafael Ocanto Davila
IPC: G06F21/31 , G06F40/253 , G06F40/263 , G06F40/40
CPC classification number: G06F21/31 , G06F40/253 , G06F40/263 , G06F40/40
Abstract: In an example embodiment, an efficient, automated method to generate password guesses is provided by leveraging online text sources along with natural language processing techniques. Specifically, semantic structures in passwords are exploited to aid system in generating better guesses. This not only helps cover instances where traditional password meters would indicate a password is safe when it is not, but also makes the solution robust against fast-evolving domains such as new slang in natural languages or new vocabulary arising from new products, product updates, and services.
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10.发明授权公开(公告)号：US11481501B2
公开(公告)日：2022-10-25
申请号：US16778872
申请日：2020-01-31
Applicant: SAP SE
Inventor： Slim Trabelsi , Sofiane Lounici , Marco Rosa , Carlo Maria Negri
Abstract: Source code is scanned to generate a list of vulnerable tokens. Thereafter, the list of vulnerable tokens is inputted into a machine learning model to identify false positives in the list of vulnerable tokens. Based on this identification, the list of vulnerable tokens can be modified to remove the identified false positives. Related apparatus, systems, techniques and articles are also described.
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