公开(公告)号：US11349858B2

公开(公告)日：2022-05-31

申请号：US16421044

申请日：2019-05-23

Applicant: Intel Corporation

Inventor： Li Chen

IPC: H04L9/00 ,  G06N20/00 ,  G06N5/00 ,  H04L9/40

Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the time series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.

公开(公告)号：US20190317965A1

公开(公告)日：2019-10-17

申请号：US16457203

申请日：2019-06-28

Applicant: Intel Corporation

Inventor： Luis Carlos Maria Remis ,  Ignacio Javier Alvarez ,  Li Chen ,  Javier Felip Leon ,  David Israel Gonzalez Aguirre ,  Justin Gottschlich ,  Javier Sebastian Turek

IPC: G06F16/9032 ,  G06F16/9038 ,  G06F16/2457

Abstract: Methods and apparatus to facilitate generation of database queries are disclosed. An example apparatus includes a generator to generate a global importance tensor. The global importance tensor based on a knowledge graph representative of information stored in a database. The knowledge graph includes objects and connections between the objects. The global importance tensor includes importance values for different types of the connections between the objects. The example apparatus further includes an importance adaptation analyzer to generate a session importance tensor based on the global importance tensor and a user query, and a user interface to provide a suggested query to a user based on the session importance tensor.

公开(公告)号：US20190044959A1

公开(公告)日：2019-02-07

申请号：US15867251

申请日：2018-01-10

Applicant: Intel Corporation

Inventor： Li Chen

IPC: H04L29/06 ,  G06N99/00 ,  G06N3/04 ,  G06F21/56

Abstract: A technique includes processing a plurality of sets of program code to extract call graphs; determining similarities between the call graphs; applying unsupervised machine learning to an input formed from the determined similarities to determine latent features of the input; clustering the determined latent features; and determining a characteristic of a given program code set of the plurality of program code sets based on a result of the clustering.

公开(公告)号：US20180375885A1

公开(公告)日：2018-12-27

申请号：US15634685

申请日：2017-06-27

Applicant: Intel Corporation

Inventor： Li Chen

IPC: H04L29/06 ,  G06N99/00

CPC classification number: H04L63/1425 ,  G06N20/00 ,  H04L63/1416 ,  H04L63/145

Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the dine series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.

公开(公告)号：US20180260562A1

公开(公告)日：2018-09-13

申请号：US15452991

申请日：2017-03-08

Applicant: Intel Corporation

Inventor： Li Chen ,  Ravi L. Sahita

IPC: G06F21/56 ,  G06F11/36 ,  G06F21/55 ,  G06F17/30 ,  G06F21/52

Abstract: In one embodiments, an apparatus includes: an execution circuit to execute a program; a monitor circuit to monitor the program execution to obtain information regarding a plurality of control transfers incurred during the execution of the program; a graph generation circuit, based on the information, to generate a plurality of control flow graphs each associated with a portion of the execution of the program; a statistic generation circuit to calculate a plurality of feature vectors each associated with one of the plurality of control flow graphs, each of the plurality of feature vectors including a plurality of graph statistics based on the associated control flow graph; and a comparison circuit to compare at least some of the plurality of graph statistics of one or more of the plurality of feature vectors to corresponding graph statistics of a statistical model of the execution of the program, to identify whether an anomaly has occurred in the execution of the program. Other embodiments are described and claimed.

公开(公告)号：US20180241811A1

公开(公告)日：2018-08-23

申请号：US15439668

申请日：2017-02-22

Applicant: Intel Corporation

Inventor： Li Chen ,  Krishnaswamy Viswanathan ,  Khun Ban

IPC: H04L29/08

CPC classification number: H04L67/1012 ,  H04L67/1008

Abstract: Disclosed is a mechanism for determining incompatible co-tenants in a cloud network. Cloud performance data is received indicating resource usage of tenants operating on a per server basis. Cross-correlation analysis is performed on past resource usage for each tenant pair operating on the server to determine correlated tenant pairs. Time series forecasting of predicted resource usage is performed for each tenant in the correlated tenant pairs. Cross-correlation analysis is then performed on the predicted resource usage for each correlated tenant pair to determine incompatible co-tenant pairs. The determined incompatible co-tenant pairs may be forwarded toward an orchestration system for hardware resource allocation in the cloud network.

公开(公告)号：US20230031591A1

公开(公告)日：2023-02-02

申请号：US17853176

申请日：2022-06-29

Applicant: Intel Corporation

Inventor： Luis Carlos Maria Remis ,  Ignacio Javier Alvarez ,  Li Chen ,  Javier Felip Leon ,  David Israel Gonzalez Aguirre ,  Justin Gottschlich ,  Javier Sebastian Turek

IPC: G06F16/9032 ,  G06F16/2457 ,  G06F16/9038

Abstract: Methods and apparatus to facilitate generation of database queries are disclosed. An example apparatus includes a generator to generate a global importance tensor. The global importance tensor based on a knowledge graph representative of information stored in a database. The knowledge graph includes objects and connections between the objects. The global importance tensor includes importance values for different types of the connections between the objects. The example apparatus further includes an importance adaptation analyzer to generate a session importance tensor based on the global importance tensor and a user query, and a user interface to provide a suggested query to a user based on the session importance tensor.

公开(公告)号：US20220126878A1

公开(公告)日：2022-04-28

申请号：US17434713

申请日：2020-03-27

Applicant: Intel Corporation

Inventor： Hassnaa Moustafa ,  Suhel Jaber ,  Darshan Iyer ,  Mehrnaz Khodam Hazrati ,  Pragya Agrawal ,  Naveen Aerrabotu ,  Petrus J. Van Beek ,  Monica Lucia Martinez-Canales ,  Patricia Ann Robb ,  Rita Chattopadhyay ,  Soila P. Kavulya ,  Karthik Reddy Sripathi ,  Igor Tatourian ,  Rita H. Wouhaybi ,  Ignacio J. Alvarez ,  Fatema S. Adenwala ,  Cagri C. Tanriover ,  Maria S. Elli ,  David J. Zage ,  Jithin Sankar Sankaran Kutty ,  Christopher E. Lopez-Araiza ,  Magdiel F. Galán-Oliveras ,  Li Chen

IPC: B60W60/00 ,  G05D1/00 ,  B60W50/14

Abstract: An apparatus comprising at least one interface to receive sensor data from a plurality of sensors of a vehicle; and one or more processors to autonomously control driving of the vehicle according to a path plan based on the sensor data; determine that autonomous control of the vehicle should cease; send a handoff request to a remote computing system for the remote computing system to control driving of the vehicle remotely; receive driving instruction data from the remote computing system; and control driving of the vehicle based on instructions included in the driving instruction data.

公开(公告)号：US11269622B2

公开(公告)日：2022-03-08

申请号：US16457006

申请日：2019-06-28

Applicant: Intel Corporation

Inventor： Mohammad Mejbah Ul Alam ,  David I. Gonzalez Aguirre ,  Shengtian Zhou ,  Justin Gottschlich ,  Li Chen

IPC: G06F8/71 ,  G06F8/75 ,  G06F8/77 ,  G06F17/11 ,  G06F40/40 ,  G06F16/906 ,  G06F16/9035 ,  G06N3/04

Abstract: Apparatus, systems, articles of manufacture, and methods for a context and complexity-aware recommendation system for efficient software development. An example apparatus includes a current state generator to generate a representation of a current state of a new function, an instruction predictor to generate a first recommended software component based on the current state of the new function, a complexity cost determiner to rank the first recommended software component based on a weighted sum of associated partial cost values, the software component to be ranked against second recommended software components based on a comparison of partial cost values corresponding to respective ones of the second recommended software components, a risk identifier to detect vulnerabilities based on an attack surface of a portion of the first recommended software component, and a ranking determiner to generate a third recommended software component, the third recommended software component corresponding to respective ranking metrics.

公开(公告)号：US11032305B2

公开(公告)日：2021-06-08

申请号：US16727500

申请日：2019-12-26

Applicant: Intel Corporation

Inventor： Li Chen

IPC: H04L9/00 ,  H04L29/06 ,  G06N20/00 ,  G06N5/00

Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the time series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.