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公开(公告)号：US20160210324A1
公开(公告)日：2016-07-21
申请号：US14916530
申请日：2013-09-25
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Sathyanarayanan Manamohan
IPC: G06F17/30
CPC classification number: G06F16/2358 , G06F16/2336 , G06F16/24544
Abstract: Example embodiments relate to providing a flexible data format for database management systems. In example embodiments, a query command to access a plastic table in a database is received, where the plastic table is a combination of at least two component sub-tables. The query command is executed to join the component sub-tables in the plastic table by using an AScan operator to obtain datarows from each of the component sub-tables, where the AScan operator converts an end of file (EOF) value to a null datarow that comprises null values, and joining the datarows obtained from the AScan operator to create query results for the query command.
Abstract translation: 示例实施例涉及为数据库管理系统提供灵活的数据格式。 在示例实施例中，接收访问数据库中的塑料表的查询命令，其中塑料表是至少两个组件子表的组合。 执行查询命令以通过使用AScan运算符来连接塑料表中的组件子表，以从每个组件子表获取数据行，其中AScan运算符将文件结束（EOF）值转换为空数据行 它包括空值，并加入从AScan运算符获取的数据行，以创建查询命令的查询结果。
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12.发明公开公开(公告)号：US20240259208A1
公开(公告)日：2024-08-01
申请号：US18459891
申请日：2023-09-01
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Sathyanarayanan Manamohan , Cynara Justine
CPC classification number: H04L9/3236 , G06N20/00 , H04L2209/463
Abstract: A system and a method for detecting and defending against adversarial attacks in decentralized learning models are described. The method comprises obtaining a learning parameter for determining a reference cryptographic hash value and a similarity between the data processing nodes (102). A cryptographic hash value is determined for each data processing node (102) based on the learning parameter. The trust score of each data processing node (102) is updated based on matching of the cryptographic hash value with the reference cryptographic hash value. The learning parameter of each data processing node (102) is merged to obtain a merged learning parameter based on the trust score. The merged learning parameter is provided to the data processing nodes (102) to be used for training the machine learning models.
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13.发明授权公开(公告)号：US11886959B2
公开(公告)日：2024-01-30
申请号：US16282098
申请日：2019-02-21
Applicant: Hewlett Packard Enterprise Development LP
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Decentralized machine learning to build models is performed at nodes where local training datasets are generated. A blockchain platform may be used to coordinate decentralized machine learning (ML) over a series of iterations. For each iteration, a distributed ledger may be used to coordinate the nodes communicating via a blockchain network. A node can include self-healing features to recover from a fault condition within the blockchain network in manner that does not negatively impact the overall learning ability of the decentralized ML system. During self-healing, the node can determine that a local ML state is not consistent with the global ML state and trigger a corrective action to recover the local ML state. Thereafter, the node can generate a blockchain transaction indicating that it is in-sync with the most recent iteration of training, and informing other nodes to reintegrate the node into ML.
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公开(公告)号：US11876891B2
公开(公告)日：2024-01-16
申请号：US17533595
申请日：2021-11-23
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Sathyanarayanan Manamohan , Vishesh Garg , Krishnaprasad Lingadahalli Shastry , Saikat Mukherjee
CPC classification number: H04L9/0637 , G06F21/602 , G06N20/20 , H04L9/008 , H04L9/0819 , H04L9/30 , H04L9/50
Abstract: Systems and methods are provided for implementing swarm learning while using blockchain technology and election/voting mechanisms to ensure data privacy. Nodes may train local instances of a machine learning model using local data, from which parameters are derived or extracted. Those parameters may be encrypted and persisted until a merge leader is elected that can merge the parameters using a public key generated by an external key manager. A decryptor that is not the merge leader can be elected to decrypt the merged parameter using a corresponding private key, and the decrypted merged parameter can then be shared amongst the nodes, and applied to their local models. This process can be repeated until a desired level of learning has been achieved. The public and private keys are never revealed to the same node, and may be permanently discarded after use to further ensure privacy.
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15.发明授权公开(公告)号：US11330019B2
公开(公告)日：2022-05-10
申请号：US16163484
申请日：2018-10-17
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Sathyanarayanan Manamohan , Krishnaprasad Lingadahalli Shastry , Avinash Chandra Pandey , Ravi Sarveswara
Abstract: The disclosure relates to decentralized management of edge nodes operating outside an enterprise network using blockchain technology. A management node may operate within a firewall of the enterprise to manage the edge nodes operating outside the firewall using blockchain technology. The management node may coordinate management by writing change requests to a decentralized ledger. The edge nodes may read the change requests from its local copy of the distributed ledger and implement the change requests. Upon implementation, an edge node may broadcast its status to the blockchain network. The management node may mine the transactions from the edge nodes into the distributed ledger, thereby creating a secure and scalable way to coordinate management and record the current and historical system state. The system also provides the edge nodes with a cryptographically secured, machine-to-machine maintained, single version of truth, enabling them to take globally valid decision based on local data.
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Patent Agency Ranking
公开(公告)号：US20210158122A1
公开(公告)日：2021-05-27
申请号：US17167278
申请日：2021-02-04
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Sathyanarayanan Manamohan
IPC: G06K19/07 , G11C11/21 , G06F9/38 , G06K19/077
Abstract: An example device comprising contactless circuitry to receive data about a plurality of events corresponding to an asset, and a memristor coupled to the contactless circuitry to store the data about the plurality of events. The contactless circuitry may determine that the asset has experienced an event, receive a transaction corresponding to the event from a decentralized entity, generate a hash of the transaction including a device identifier of the contactless circuitry and the transaction received from the decentralized entity, verify the hashed transaction with the decentralized entity, and store the verified hashed transaction on the memristor of the contactless circuitry, wherein the stored verified hash includes information about the event.
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17.发明授权公开(公告)号：US12273394B2
公开(公告)日：2025-04-08
申请号：US17691744
申请日：2022-03-10
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Sathyanarayanan Manamohan , KrishnaPrasad Lingadahalli Shastry , Avinash Chandra Pandey , Ravi Sarveswara
Abstract: The disclosure relates to decentralized management of edge nodes operating outside an enterprise network using blockchain technology. A management node may operate within a firewall of the enterprise to manage the edge nodes operating outside the firewall using blockchain technology. The management node may coordinate management by writing change requests to a decentralized ledger. The edge nodes may read the change requests from its local copy of the distributed ledger and implement the change requests. Upon implementation, an edge node may broadcast its status to the blockchain network. The management node may mine the transactions from the edge nodes into the distributed ledger, thereby creating a secure and scalable way to coordinate management and record the current and historical system state. The system also provides the edge nodes with a cryptographically secured, machine-to-machine maintained, single version of truth, enabling them to take globally valid decision based on local data.
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公开(公告)号：US20240406203A1
公开(公告)日：2024-12-05
申请号：US18799525
申请日：2024-08-09
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Madhusoodhana Chari Sesha , Krishna Prasad Lingadahalli Shastry , Sathyanarayanan Manamohan
IPC: H04L9/40
Abstract: Systems and methods are provided for implementing pattern detection as a first step for security improvements of a computer network. The pattern detection may utilize a machine learning (ML) model for predicting network tuple parameters. The ML model can be trained on labelled data flow information and deployed by a central server for preventing network-wide cyber-security challenges (e.g., including DNS flux, etc.). Networking devices (e.g. switches, etc.) can monitor the data flow traffic that it receives from the networking devices and classify network tuple parameters based on the flow behavior. The system can compare the output of the ML model (e.g., a classification of the data flow traffic, etc.) to an implicit label (e.g., the network tuple parameter included with the data flow traffic, etc.). When the classification matches a particular network tuple parameter, the system can generate an alert and/or otherwise identify potential network intrusions and other abnormalities.
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19.发明公开公开(公告)号：US20240135257A1
公开(公告)日：2024-04-25
申请号：US18528477
申请日：2023-12-04
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Decentralized machine learning to build models is performed at nodes where local training datasets are generated. A blockchain platform may be used to coordinate decentralized machine learning (ML) over a series of iterations. For each iteration, a distributed ledger may be used to coordinate the nodes communicating via a blockchain network. A node can include self-healing features to recover from a fault condition within the blockchain network in manner that does not negatively impact the overall learning ability of the decentralized ML system. During self-healing, the node can determine that a local ML state is not consistent with the global ML state and trigger a corrective action to recover the local ML state. Thereafter, the node can generate a blockchain transaction indicating that it is in-sync with the most recent iteration of training, and informing other nodes to reintegrate the node into ML.
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20.发明授权公开(公告)号：US11966818B2
公开(公告)日：2024-04-23
申请号：US16282098
申请日：2019-02-21
Applicant: Hewlett Packard Enterprise Development LP
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: Decentralized machine learning to build models is performed at nodes where local training datasets are generated. A blockchain platform may be used to coordinate decentralized machine learning (ML) over a series of iterations. For each iteration, a distributed ledger may be used to coordinate the nodes communicating via a blockchain network. A node can include self-healing features to recover from a fault condition within the blockchain network in manner that does not negatively impact the overall learning ability of the decentralized ML system. During self-healing, the node can determine that a local ML state is not consistent with the global ML state and trigger a corrective action to recover the local ML state. Thereafter, the node can generate a blockchain transaction indicating that it is in-sync with the most recent iteration of training, and informing other nodes to reintegrate the node into ML.
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