Andrey Marochko

dblp:130/0711 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cyber-physical and IoT security · 50% Systems and software security · 50%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security
trusted computing
0.412019
Dominance as a New Trusted Computing Primitive for the Internet of Things · IEEE Symposium on Security and Privacy 2019

Methods — techniques the papers use, named apart from their topics

trusted computing · 0.8firmware update · 0.8
YearPublicationVenuePosition
2019 Dominance as a New Trusted Computing Primitive for the Internet of Things
abstract
The Internet of Things (IoT) is rapidly emerging as one of the dominant computing paradigms of this decade. Applications range from in-home entertainment to large-scale industrial deployments such as controlling assembly lines and monitoring traffic. While IoT devices are in many respects similar to traditional computers, user expectations and deployment scenarios as well as cost and hardware constraints are sufficiently different to create new security challenges as well as new opportunities. This is especially true for large-scale IoT deployments in which a central entity deploys and controls a large number of IoT devices with minimal human interaction. Like traditional computers, IoT devices are subject to attack and compromise. Large IoT deployments consisting of many nearly identical devices are especially attractive targets. At the same time, recovery from root compromise by conventional means becomes costly and slow, even more so if the devices are dispersed over a large geographical area. In the worst case, technicians have to travel to all devices and manually recover them. Data center solutions such as the Intelligent Platform Management Interface (IPMI) which rely on separate service processors and network connections are not only not supported by existing IoT hardware, but are unlikely to be in the foreseeable future due to the cost constraints of mainstream IoT devices. This paper presents Cider, a system that can recover IoT devices within a short amount of time, even if attackers have taken root control of every device in a large deployment. The recovery requires minimal manual intervention. After the administrator has identified the compromise and produced an updated firmware image, he/she can instruct Cider to force the devices to reset and to install the patched firmware on the devices. We demonstrate the universality and practicality of Cider by implementing it on three popular IoT platforms (HummingBoard Edge, Raspberry Pi Compute Module 3 and Nucleo-L476RG) spanning the range from high to low end. Our evaluation shows that the performance overhead of Cider is generally negligible.
Meng Xu 0001, Manuel Huber 0001, Zhichuang Sun, Paul England, Marcus Peinado, Sangho Lee 0001, Andrey Marochko, Dennis Mattoon, Rob Spiger, Stefan Thom
IEEE Symposium on Security and Privacy7