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公开(公告)号：US11818147B2
公开(公告)日：2023-11-14
申请号：US17102295
申请日：2020-11-23
CPC分类号： H04L63/1416 , G06N3/04 , G06N3/08
摘要： Systems, methods and computer program products for improving security of artificial intelligence systems. The system comprising processors for monitoring one or more transactions received by a machine learning decision model to determine a first score associated with a first transaction. The first transaction may be identified as likely adversarial, in response to the first score being lower than a certain score threshold and the first transaction having a low occurrence likelihood. A second score may be generated in association with the first transaction based on one or more adversarial latent features associated with the first transaction. At least one adversarial latent feature may be detected as being exploited by the first transaction, in response to determining that the second score falls above the certain score threshold. Accordingly, an abnormal volume of activations of adversarial latent features spanning across a plurality of transactions scored may be detected and blocked.
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32.发明授权公开(公告)号：US11694292B2
公开(公告)日：2023-07-04
申请号：US16395112
申请日：2019-04-25
发明人： Scott Michael Zoldi , Qing Lin
摘要： A system and method includes soft-segment based rules optimization that can mitigate the overall false positives while maintaining 100% true positive detection. The soft clustering allows real-time re-assignment of an account to a dominate archetype behavior, as well as rule optimization based on a logical order with more relaxation on thresholds for the most inefficient rules is performed within each archetype. The rule optimization provides false positive reduction compared to a baseline rule system. The method can be used to reduce false positives for any rule-based detection system in which the same true positive detection is required.
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33.发明授权公开(公告)号：US11636485B2
公开(公告)日：2023-04-25
申请号：US15947717
申请日：2018-04-06
发明人： Scott Michael Zoldi , Alexei Betin
摘要： Parallelized computation by a real-time transaction scoring system that incorporates global behavior profiling of transacting entities includes dividing a global profile computing component of a transaction scoring model of a real-time behavioral analytics transaction scoring system into a plurality of global profile component instances. The transaction scoring model uses a plurality of global profile variables, each of the plurality of global profile component instances using its own global profile partition that contains the estimate of global profile variables and being configured for update by a dedicated thread of execution of the real-time transaction scoring system, each dedicated thread being configured for receiving and scoring a portion of input transactions. The method further includes partitioning, based on one or more transaction routing shuffling algorithms, the input transactions for receipt across the plurality of global profile component instances, and updating each of the plurality of global profile partitions by the corresponding global profile component running in the dedicated thread according to the scoring algorithm.
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公开(公告)号：US11373109B2
公开(公告)日：2022-06-28
申请号：US16460934
申请日：2019-07-02
摘要： In transactional systems where past transactions can have impact on the current score of a machine learning based decision model, the transactions that are most responsible for the score and the associated reasons are determined by the transactional system. A system and method identifies such past transactions that maximally impact the current score and allow for a more effective understanding of the scores generated by a model in a transactional system and explanation of specific transactions for automated decisioning, to explain the scores in terms of past transactions. Further an existing instance-based explanation system is used to identify the reasons for the score, and how the identified transactions influence these reasons. A combination of impact on score and impact on reasons determines the most impactful past transaction with respect to the most recent score being explained.
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公开(公告)号：US11049012B2
公开(公告)日：2021-06-29
申请号：US15820141
申请日：2017-11-21
发明人： Scott Michael Zoldi , Chahm An
摘要： A system and method to explain model behavior, which can benefit not only those seeking to meet regulatory requirements when using machine learning models but also help guide users of the model to assess and increase robustness associated with model governance processes. The method described utilizes changes in behavior of a time series to identify the latent factors that drive explanation.
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公开(公告)号：US11042551B2
公开(公告)日：2021-06-22
申请号：US15368518
申请日：2016-12-02
发明人： Gerald Fahner , Scott Michael Zoldi
IPC分类号： G06F16/00 , G06F16/2457 , G06F16/248 , G06F16/28 , G06F16/2455
摘要： Systems and methods for generating concise explanations of scored observations that strike good, and computationally efficient, trade-offs between rank-ordering performance and explainability of scored observations are disclosed. The systems and methods described herein for explaining scored observations are based on a framework of partial dependence functions (PDFs), multi-layered neural networks (MNNs), and Latent Explanations Neural Network Scoring (LENNS).
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37.发明授权公开(公告)号：US10791136B2
公开(公告)日：2020-09-29
申请号：US15463420
申请日：2017-03-20
摘要： A system and method for assessing the cybersecurity breach risk associated with a given organization is disclosed. The system and method assume no internal visibility into any organizational network. A taxonomy of possible data sources is defined and motivated. The system and method are both purely empirical and robust against common difficulties in scoring organizational networks, such as the raw number of network assets owned by the organization.
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38.发明申请公开(公告)号：US20190354613A1
公开(公告)日：2019-11-21
申请号：US15981755
申请日：2018-05-16
发明人： Scott Michael Zoldi , Shafi Rahman
摘要： A system and method for analyzing coverage, bias and model explanations in large dimensional modeling data includes discretizing three or more variables of a dataset to generate a discretized phase space represented as a grid of a plurality of cells, the dataset comprising a plurality of records, each record of the plurality of records having a value and a unique identifier (ID). A grid transformation is applied to each record in the dataset to assign each record to a cell of the plurality of cells of the grid according to the grid transformation. A grid index is generated to reference each cell using a discretized feature vector. A grid storage for storing the records assigned to each cell of the grid is then created. The grid storage using the ID of each record as a reference to each record and the discretized feature vector as a key to each cell.
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39.发明申请公开(公告)号：US20190311366A1
公开(公告)日：2019-10-10
申请号：US15947717
申请日：2018-04-06
发明人： Scott Michael Zoldi , Alexei Betin
摘要： Parallelized computation by a real-time transaction scoring system that incorporates global behavior profiling of transacting entities includes dividing a global profile computing component of a transaction scoring model of a real-time behavioral analytics transaction scoring system into a plurality of global profile component instances. The transaction scoring model uses a plurality of global profile variables, each of the plurality of global profile component instances using its own global profile partition that contains the estimate of global profile variables and being configured for update by a dedicated thread of execution of the real-time transaction scoring system, each dedicated thread being configured for receiving and scoring a portion of input transactions. The method further includes partitioning, based on one or more transaction routing shuffling algorithms, the input transactions for receipt across the plurality of global profile component instances, and updating each of the plurality of global profile partitions by the corresponding global profile component running in the dedicated thread according to the scoring algorithm.
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公开(公告)号：US20190095988A1
公开(公告)日：2019-03-28
申请号：US16174106
申请日：2018-10-29
发明人： Scott Michael Zoldi , Michael Urban
摘要： A system and method for detecting compromise of financial transaction instruments associated with a merchant or automated teller machine (ATM) are disclosed. Historical data representing a historical aggregate financial transaction instrument behavior history is stored in a computer memory. The historical data is received at the computer from one or more merchants and ATMs via a communications network. Authorization data representing authorization behavior of a plurality of financial transaction cards related to corresponding financial transactions at the same or a different one or more merchants and ATMs is received by the computer. Abnormal activity data representing an abnormal aggregate financial transaction instrument activity based on the authorization data is determined, and the historical data is compared with the abnormal activity data to generate a compromise profile for the plurality of financial transaction instruments.
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