Výsledky vyhledávání - "Sanjeev R. Kulkarni"

Convergence of Federated Learning over a Noisy Downlink

Autor: Deniz Gunduz, Mohammad Mohammadi Amiri, Sanjeev R. Kulkarni, H. Vincent Poor

We study federated learning (FL), where power-limited wireless devices utilize their local datasets to collaboratively train a global model with the help of a remote parameter server (PS). The PS has access to the global model and shares it with the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::371c60c49e74a56349000d5df3781aee
https://hdl.handle.net/11380/1280015

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A query system for efficiently investigating complex attack behaviors for enterprise security

Autor: Peng Gao, Sanjeev R. Kulkarni, Kangkook Jee, Xusheng Xiao, Zhichun Li, Prateek Mittal, Fengyuan Xu

Publikováno v: Proceedings of the VLDB Endowment. 12:1802-1805

The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely attack investigation over the monitoring data for uncovering the attack

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2603544a82cfc74dacb9b1a355a3782d
https://doi.org/10.14778/3352063.3352070

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Powered endoscopic dacryocystorhinostomy (DCR), raising the bars

Autor: Sanjeev R. Kulkarni, K.V. Satyamurthy, Arati Jain, Roopa Hiremath

Publikováno v: IP International Journal of Ocular Oncology and Oculoplasty. 5:24-27

Introduction: This study is done to assess the efficacy of powered endoscopic dacryocystorhinostomy (DCR) with large bony ostium exposing of fundus of sac and primary mucosal anastomosis. The study involved prospective interventional case series with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fb8b10703273a41be0bc99f4717cff57
https://doi.org/10.18231/2581-5016.2019.0006

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A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence

Autor: Prateek Mittal, Haoyuan Liu, Dawn Song, Zheng Qin, Sanjeev R. Kulkarni, Fengyuan Xu, Xusheng Xiao, Peng Gao, Xiaoyuan Liu, Fei Shao

Publikováno v: ICDE

Log-based cyber threat hunting has emerged as an important solution to counter sophisticated cyber attacks. However, existing approaches require non-trivial efforts of manual query construction and have overlooked the rich external knowledge about th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b876b0edddf2dad826426d2f62de2670
http://arxiv.org/abs/2101.06761

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Federated Learning with Downlink Device Selection

Autor: H. Vincent Poor, Sanjeev R. Kulkarni, Mohammad Mohammadi Amiri

Publikováno v: SPAWC

We study federated edge learning, where a global model is trained collaboratively using privacy-sensitive data at the edge of a wireless network. A parameter server (PS) keeps track of the global model and shares it with the wireless edge devices for

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17812afb0997f2e488e21110f550359b

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Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence

Autor: Zheng Qin, Sanjeev R. Kulkarni, Fengyuan Xu, Xiaoyuan Liu, Dawn Song, Peng Gao, Xusheng Xiao, Fei Shao, Prateek Mittal

Publikováno v: ICDE

Log-based cyber threat hunting has emerged as an important solution to counter sophisticated attacks. However, existing approaches require non-trivial efforts of manual query construction and have overlooked the rich external threat knowledge provide

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b808e0a9e5cea5018fe21127a2e49fa4
http://arxiv.org/abs/2010.13637

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Querying Streaming System Monitoring Data for Enterprise System Anomaly Detection

Autor: Sanjeev R. Kulkarni, Xusheng Xiao, Haifeng Chen, Prateek Mittal, Kangkook Jee, Ding Li, Peng Gao

Publikováno v: ICDE

The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely abnormal system behavior detection over the stream of monitoring data. H

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a861274a6e1e1eb2d7d0a36e9ac8f724
https://doi.org/10.1109/icde48307.2020.00167

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Update Aware Device Scheduling for Federated Learning at the Wireless Edge

Autor: Mohammad Mohammadi Amiri, Sanjeev R. Kulkarni, H. Vincent Poor, Deniz Gunduz

Publikováno v: ISIT

We study federated learning (FL) at the wireless edge, where power-limited devices with local datasets train a joint model with the help of a remote parameter server (PS). We assume that the devices are connected to the PS through a bandwidth-limited

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12aa72a06777402e2c7df84291f4bdb1
https://hdl.handle.net/11380/1247353

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