公开(公告)号：US20210329522A1

公开(公告)日：2021-10-21

申请号：US16852306

申请日：2020-04-17

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： YUANJIE LI ,  Kyu-Han Kim

IPC: H04W36/18 ,  H04W16/22 ,  H04W36/08 ,  H04W36/36 ,  H04L29/08 ,  H04W36/30 ,  H04W36/02 ,  G06N5/04 ,  G06N20/00

Abstract: Systems and methods are provided for predicting handover events in wireless communications systems, such as 4G and 5G communications networks. Machine learning is used to refine the predicting of handover events, where per-cell local handover prediction models may be trained by mobile user devices operating in the wireless communications systems. Parameters gleaned from the localized training of the per-cell local handover prediction models may be shared by multiple mobile user devices and aggregated by a global handover prediction model, which in turn may be used to derive refined per-cell local handover prediction models that can be disseminated to the mobile user devices.

公开(公告)号：US20220272120A1

公开(公告)日：2022-08-25

申请号：US17183195

申请日：2021-02-23

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： YUANJIE LI ,  KYU-HAN KIM ,  QIANRU LI

IPC: H04L29/06

Abstract: Systems and methods for mitigating cyberattacks are described herein. A computing system can detect illegitimate network traffic associated with a cyberattack in network traffic. The computing system can determine an amplification factor of the cyberattack based in part on a probability distribution of the illegitimate network traffic. The computing system can determine a filter to demotivate a generation of the illegitimate network traffic. The determined filter can reduce the amplification factor of the cyberattack. The computing system can implement the determined filter to block the illegitimate network traffic.