Fast and Secure Networks
Hi, I’m Prof. Anat Bremler- Barr (Hebrew: ענת ברמלר-בר), computer network scientist. My work is motivated by a desire to improve the reliability and efficiency of the Internet. My research delves into the fundamentals of network algorithmics and networking device design, especially virtualized middleboxes (i.e., network functions). More recently, I’ve been focused on the new network challenges caused by the transformations in the Internet of Things and cloud computing.
I received my PhD in computer science from Tel Aviv University, graduating with distinction. In 2001, I was co-founder and served as chief scientist at Riverhead Networks Inc., a company providing mitigation systems from Denial of Service attacks. The company was acquired by Cisco Systems in 2004, at which time I joined the Efi Arazi School of Computer Science at Reichman University (formerly the Interdisciplinary Center Herzliya). In 2010, I received a prestigious starting grant from the European Research Council for Deep Packet Inspection of Next Generation Network Devices. I am also the founder and director of the Deepness Lab, which focuses on designing reliable and efficient networks and network devices.
Academic Activities
Editor-at-Large for the IEEE/ACM Transactions on Networking, I served as associate editor from, 2015-2018.
- TPC: SIGCOMM 2022 workshop chair, IEEE INFOCOM 2008-2022, IFIP Networking 2019-2020,2022
News
Daniel’s talk is about his research on Kubernetes service selection, a challenging and practical problem.
This research is part of his master thesis.
Congratulations to Daniel Dubnikov, whose research work “Adaptive DNSSEC” has been accepted to ORAC 37.
“Dynamic-Deep Compression Tuning Cloud Costs and ECG Task Performance” is available here. The paper has been accepted to IEEE/IFIP NOMS Manage-IoT workshop, 2022.
A new tool enabling MUD comparison and generalization is now available here. MUDIS analyzes the network behavior of IoT devices, based on their formal description in the MUD files. MUDIS was developed by Ran Shister and Bar Meyuhas.