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Title:A study of covert queueing channels in shared schedulers
Author(s):Ghassami, Amiremad
Advisor(s):Kiyavash, Negar
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Covert Queueing Channel
Capacity Limit
First-Come-First-Served Scheduler
Round Robin Scheduler.
Abstract:We study covert queueing channels (CQCs), which are a kind of covert timing channel that may be exploited in shared queues across supposedly isolated users. In our system model, a user modulates messages to another user via his pattern of access to the shared resource. One example of such a channel is the cross-virtual network covert channel in data center networks resulting from the queueing effects of the shared resource. First, we study a system comprising a transmitter and a receiver that share a deterministic and work-conserving first-come-first-served scheduler, and we compute the maximum reliable data transmission rate, i.e., the capacity, of this channel. Next, we extend the model to include a third user who also uses the shared resource and study the effect of the presence of this user on the information transmission rate. The solution approach presented in this extension may be applied to calculate the capacity of the covert queueing channel among any number of users. We also study a queueing covert channel between two users sharing a round robin scheduler. Such a covert channel can arise when users share a resource such as a computer processor or a router arbitrated by a round robin policy. We present an information-theoretic framework to model and derive the capacity of this channel for both noiseless and noisy scenarios. Our results show that seemingly isolated users can communicate at a high rate over the covert channel. Furthermore, we propose a practical finite-length code construction, which achieves the capacity limit.
Issue Date:2016-11-29
Rights Information:Copyright 2016 AmirEmad Ghassami
Date Available in IDEALS:2017-03-01
Date Deposited:2016-12

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