IT-Forum

Security in Wireless Networks under Imperfect Channel Knowledge in Wireless Networks [IT Forum]

Topic: 
Security in Wireless Networks under Imperfect Channel Knowledge in Wireless Networks
Abstract / Description: 

In this talk we will explore the effect of delayed or no channel state information (CSI) on physical layer security in various wireless channel models. The assumption of perfect eavesdropper CSI being available at the transmitters, though commonly used in the literature as an idealization, is often impractical as it involves feedback of channel state measurements by the passive eavesdropper to the transmitters. Further, delay and network conditions in the feedback link may also impact the CSI quality available at the transmitters. We will discuss how such imperfections in the CSI available at the transmitters affect physical layer security in various channel models, including the wiretap channel with helpers, multiple access wiretap channels, interference channels with an eavesdropper and broadcast channels with confidential messages, determining, in most cases, the optimal secure degrees of freedom of the networks under imperfect CSI conditions.

Date and Time: 
Friday, January 13, 2017 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum: Data-driven methods for sparse network estimation

Topic: 
Data-driven methods for sparse network estimation
Abstract / Description: 

Graphical model is a probabilistic model for which a graph is used to represent the conditional independence between random variables. Such models have become extremely popular tools for modeling complex real-world systems. Learning graphical models is of fundamental importance in machine learning and statistics and is often challenged by the fact that only a small number of samples are available relative to the number of variables. Several methods (such as Graphical Lasso) have been proposed to address this problem. However, there is a glaring lack of concrete case studies that clearly illustrate the limitations of the existing computational methods for learning graphical models. In this talk, I will propose a circuit model that can be used as a platform for testing the performance of different statistical approaches. I will also develop new insights into regularized semidefinite program (SDP) problems by working through the Graphical Lasso algorithm. Graphical Lasso is a popular method for learning the structure of a Gaussian model, which relies on solving a computationally-expensive SDP. I will derive sufficient conditions under which the solution of this large-scale SDP has a simple formula. I will illustrates our results on electrical circuits and fMRI data for finding brain networks.

Date and Time: 
Friday, November 11, 2016 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
Remote state estimation over erasure channels: structure of optimal strategies and fundamental limits
Abstract / Description: 

In many applications such as networked control systems, sensor and surveillance networks, and transportation networks, etc., data must be transmitted sequentially from one node to another under a strict delay deadline. In many of such real-time communication systems, the transmitter is a battery powered device that transmits over a wireless packet-switched network; the cost of switching on the radio and transmitting a packet is significantly more important than the size of the data packet. Therefore, the transmitter does not transmit all the time; but when it does transmit, the transmitted packet is as big as needed to communicate the current source realization. In this talk, we characterize fundamental trade-offs between the estimation error (or distortion) and the cost or average number of transmissions in such systems.

In particular, we consider a sensor that observes a first-order autoregressive Markov process. At each time instant, based on the current state of the process and the history of its past decisions, the sensor determines whether or not to transmit the current state. Transmissions take place over a packet erasure channel. If the sensor does not transmit, the receiver must estimate the state using the previously transmitted values. A per-step distortion function measures the estimation error. We investigate two fundamental trade-offs in this setup: (i) when there is a cost associated with each communication, what is the minimum expected estimation error plus communication cost; and (ii) when there is a constraint on the average number of transmissions, what is the minimum estimation error. For both these cases, we characterize the transmission and estimation strategies that achieve the optimal trade-off and develop algorithms that identify these optimal strategies.

This is a joint work with Jhelum Chakravorty and Jayakumar Subramanian.

Date and Time: 
Friday, November 4, 2016 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
Information Theoretic Privacy in Electricity Networks with Smart Meters
Abstract / Description: 

Smart meters report electricity usage of a user to the utility provider on a real-time basis, which is known to leak sensitive user information. In this talk we will discuss how a rechargeable battery with limited storage capacity at the user's home can be used to mask this information.

We will use the mutual information between the user load and the grid output as our privacy metric and assume that the rechargeable battery satisfies ideal charge conservation. We show that the problem of designing optimal charging policies is equivalent to designing a communication channel subject to certain state constraints. For the case of i.i.d. inputs we derive an explicit solution and provide an intuitive interpretation based on certain invariance properties of the system. For the case of Markov inputs we cast the problem as a Markov Decision Process (MDP) that could be solved using a dynamic program. We will also discuss a generalization when multiple batteries cascaded in series can be used by the system.

This is a joint work with Simon Li and Aditya Mahajan.


The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Friday at 1:00 pm during the academic year.

The Information Theory Forum is organized by graduate students Jiantao Jiao and Yanjun Han. To suggest speakers, please contact any of the students.

Date and Time: 
Friday, October 28, 2016 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
From Wiener process to Bits (and back)
Abstract / Description: 

What is the minimal mean squared error in recovering a path of the Brownian motion from any finite bit per time lag encoded version of it? Is it possible to attain a bounded mean squared error in this case?

Berger's PhD thesis answers these two question by providing a coding theorem for the Brownian motion, showing that its optimal distortion-rate performance are described by Shannon's distortion-rate function. That is, Berger's result implies that for any positive bitrate, there exists a coding scheme that allows recovering of the Brownian path with mean squared error given by Shannon's distortion-rate function (first evaluated by Iaglom).

Berger's result, however, does not take into account practical considerations in encoding analog process. Indeed, hardware and other implementation constraints restrict access to samples of the continuous-time path, taken at a finite time resolution. The question that we ask in thistalk is what is the minimal mean squared error in recovering the original Brownian path from a code that is only a function of these samples. This question is answered by deriving the distortion-rate function as a function of the sampling rate. It can be shown that the ratio between this function and the optimal distortion-rate performance without sampling constraint of Berger, are only a function of the number of bits per sample. For example, our result implies that using 1 bits per sample, one can attain distortion which is no more than 1.12 times the distortion-rate function.

Another interesting question arises in the following case: assume that the source encoder receives the discrete-time samples but is unaware of their underlying continuous-time origin. As a result, the encoder applies an optimal source code with respect to the empirical distribution of these samples, namely with respect to a discrete-time Brownian motion. We show that the maximal loss in this case, compared to an encoder that considers the continuous-time origin, does not exceed 1/6 times the intensity of the process.


 

The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Friday at 1:00 pm during the academic year.

The Information Theory Forum is organized by graduate students Jiantao Jiao and Yanjun Han. To suggest speakers, please contact any of the students.

Date and Time: 
Friday, October 21, 2016 - 1:00pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
Erasure coding for big-data systems: Theory and Practice
Abstract / Description: 

Erasure codes are being increasingly deployed as an alternative to data replication in large-scale distributed storage systems to achieve fault tolerance in a storage-efficient manner. This paradigm shift has opened up exciting challenges and opportunities both on the theoretical as well as the system-design fronts. Specifically, while traditional codes are optimal in utilizing storage space, they significantly increase the usage of other important cluster resources such as network and device I/O. Furthermore, the usage of codes has primarily been limited to achieving space-efficient fault tolerance for storing "cold'' (less-frequently accessed) data, beyond which the potential of codes in big-data systems is largely unexplored.

We present new code constructions, and design and build erasure-coded storage systems, which provably reduce the usage of network and device I/O by a significant amount while not compromising on storage efficiency. Our codes have been evaluated on Facebook's data warehouse cluster in production, and will be a part of the next release of Apache Hadoop. Furthermore, we explore new avenues for coding in big-data systems, in particular for "hot'' (frequently accessed) data, by showing how codes can be employed to achieve significant benefits in load balancing and reducing latency in data-intensive cluster caches.


 

The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Friday at 1:00 pm during the academic year.

The Information Theory Forum is organized by graduate students Jiantao Jiao and Yanjun Han. To suggest speakers, please contact any of the students.

Date and Time: 
Friday, October 7, 2016 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
Part I: Wiretap Channels with Random States; Part II: Differential Privacy as a Mutual Information Constraint
Abstract / Description: 

 

In the first part, we propose a new encoding scheme for the wiretap channel setting where a random state is known non-causally to the encoder but not necessarily to the decoder (the Gelfand-Pinsker setting). This setting combines two scenarios with celebrated results in information theory--the wiretap channel and the Gelfand-Pinsker channel--and it so happens that essentially the same encoding scheme is optimal for both scenarios individually. A decade ago, Chen and Han Vinck analyzed the secrecy rates achieved by that same encoding scheme. Quite surprisingly, Chia and El Gamal more recently showed that a different encoding scheme which explicitly extracts a key from the state to be used for encryption can sometimes outperform that scheme. In this work, we show a simple superposition code design which performs at least as well as both of these competing schemes, accomplishing the key agreement concept in a more subtle way through the selection of the auxiliary random variables.

In the second part, an information theoretic notion of differential privacy will be presented, which establishes an equivalence between differential privacy and a mutual information constraint. This intuitive definition in terms of mutual information admits very simple proofs of several important properties of differential privacy.


 

The Information Theory Forum (IT-Forum) at Stanford ISL is an interdisciplinary academic forum which focuses on mathematical aspects of information processing. With a primary emphasis on information theory, we also welcome researchers from signal processing, learning and statistical inference, control and optimization to deliver talks at our forum. We also warmly welcome industrial affiliates in the above fields. The forum is typically held in Packard 202 every Friday at 1:00 pm during the academic year.

The Information Theory Forum is organized by graduate students Jiantao Jiao and Yanjun Han. To suggest speakers, please contact any of the students.

Date and Time: 
Friday, September 30, 2016 - 1:15pm to 2:15pm
Venue: 
Packard 202

IT-Forum

Topic: 
Deniable/Covert/Stealthy/LPD communication
Abstract / Description: 

The urge to communicate, to speak and be heard, is a fundamental human need. However, embedded within our increasingly sophisticated communication networks, Big Brother is often watching. There are situations where even the fact that communication is happening (not just the content of that communication), can have real-world consequences. For instance, if you are a politically active citizen in an authoritarian society with broad censorship powers, the mere fact that you are communicating with the outside world can be construed by those authorities as sufficient justification for reprisals.

There has been a flurry of recent work in the information theory community dealing with this problem. In general, this problem encompasses models of communication with dual goals. Firstly, all communication from the source (Alice) to the destination (Bob) should be reliable, i.e., the communication protocol should be resilient to random noise, and perhaps even active jamming. Secondly, if the communication is overheard by a third party (Eve), it should be deniable from Eve. That is, not only should Eve should not learn anything about the source's message, in fact Eve should not even be able to reliably decide whether or not the source is indeed communicating to Bob. To be able to instantiate such deniability in communication, there need to be asymmetries that might exist between Bob and Eve (for instance, perhaps the noise on the channel to Eve is higher than the noise on the channel to Bob, or perhaps Eve observes only a subset of the transmissions that Bob does).

The tools used are typically information-theoretic and/or coding-theoretic in nature. Typically, deniability is formally defined in terms of a hypothesis-testing metric, and then one demands that the communication protocol that is reliable to Bob also have "high deniability", regardless of Eve's estimation strategy. Recently, in various communication settings (wired, wireless and quantum channels/networks), fundamental bounds on optimal rates for deniable communication, and also complementary schemes that are close to optimal.

Date and Time: 
Friday, June 3, 2016 - 1:00pm to 2:00pm
Venue: 
Packard 202

IT-Forum

Topic: 
Cooperation Costs and Consequences
Abstract / Description: 

In communication networks, cooperation is a strategy in which communicators exchange information not for the purpose of sending messages one to the other but instead for the purpose of enabling improved communication performance somewhere else in the network. For example, the transmitters of a multiple access channel may exchange information not because either has a message intended for the other but instead to increase the total rate at which both can communicate to the receiver. Measuring the cost of cooperation as the amount of information exchanged and the benefit of cooperation as the increase in sum-capacity to the intended receiver, we can ask simple yet surprisingly rich questions about when cooperation is worth its cost and how big the gains can be.

Date and Time: 
Friday, May 20, 2016 - 1:00pm to 2:00pm
Venue: 
Packard 202

Claude E. Shannon's 100th Birthday

Topic: 
Centennial year of the 'Father of the Information Age'
Abstract / Description: 

From UCLA Shannon Centennial Celebration website:

Claude Shannon was an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". Shannon founded information theory and is perhaps equally well known for founding both digital computer and digital circuit design theory. Shannon also laid the foundations of cryptography and did basic work on code breaking and secure telecommunications.

 

Events taking place around the world are listed at IEEE Information Theory Society.

Date and Time: 
Saturday, April 30, 2016 - 12:00pm
Venue: 
N/A

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