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However, the low-level access to the FPGA hardware and associated resources such as the PCIe bus, SSD drives, or DRAM modules also opens up threats of malicious attackers uploading designs that are able to infer information about other users or about the cloud infrastructure itself. In particular, this work presents a new, fast PCIe-contention-based channel that is able to transmit data between FPGA-accelerated virtual machines (VMs) by modulating the PCIe bus usage. This channel further works with different operating systems and achieves bandwidths reaching 20 kbps with 99% accuracy. This is the first cross-FPGA covert channel demonstrated on commercial clouds and has a bandwidth which is over 2000\u00d7 larger than prior voltage- or temperature-based cross-board attacks. This article further demonstrates that the PCIe receivers are able to not just receive covert transmissions, but can also perform fine-grained monitoring of the PCIe bus, including detecting when co-located VMs are initialized, even prior to their associated FPGAs being used. Moreover, the proposed mechanism can be used to infer the activities of other users, or even slow down the programming of the co-located FPGAs as well as other data transfers between the host and the FPGA. Beyond leaking information across different virtual machines, the ability to monitor the PCIe bandwidth over hours or days can be used to estimate the data center utilization and map the behavior of the other users. The article also introduces further novel threats in FPGA-accelerated instances, including contention due to network traffic, contention due to shared NVMe SSDs, as well as thermal monitoring to identify FPGA co-location using the DRAM modules attached to the FPGA boards. This is the first work to demonstrate that it is possible to break the separation of privilege in FPGA-accelerated cloud environments, and highlights that defenses for public clouds using FPGAs need to consider PCIe, SSD, and DRAM resources as part of the attack surface that should be protected.<\/jats:p>","DOI":"10.1145\/3534972","type":"journal-article","created":{"date-parts":[[2022,5,12]],"date-time":"2022-05-12T14:04:08Z","timestamp":1652364248000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Cross-VM Covert- and Side-Channel Attacks in Cloud FPGAs"],"prefix":"10.1145","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3700-2742","authenticated-orcid":false,"given":"Ilias","family":"Giechaskiel","sequence":"first","affiliation":[{"name":"Independent Researcher, London, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1469-4045","authenticated-orcid":false,"given":"Shanquan","family":"Tian","sequence":"additional","affiliation":[{"name":"Yale University, CT, New Haven, CT"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9721-3640","authenticated-orcid":false,"given":"Jakub","family":"Szefer","sequence":"additional","affiliation":[{"name":"Yale University, CT, New Haven, CT"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,22]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2013.12.001"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/FDTC.2019.00015"},{"key":"e_1_3_2_4_2","article-title":"Instance Families","author":"Cloud Alibaba","year":"2022","unstructured":"Alibaba Cloud. 2022. 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