Communications & Security

Communication networks, hardware, information theory and security

Communication systems research is one of ISR's foundational areas of inquiry. ISR’s best-known research breakthrough may be the algorithms and protocols by which internet services can be delivered over satellite, using a high-speed, two-way connection through low-earth-orbit satellites. In addition, high quality joint source-channel coding of images and related modem technologies were developed for voice and data. Modeling, analytic and formal models for cross-layer design of wireless network and mobile ad-hoc network protocols have been developed using a component-based, model-based systems engineering approach. A systems perspective inspired by control and communications theory and methods has brought security to wireless networks beyond traditional cryptographic methods. Current work spans integrated security from the physical layer—hardware and signal processing—to protocols, applications and human users.

Recent publications


Joint Satellite Gateway Placement and Routing for Integrated Satellite-Terrestrial Networks

Nariman Torkzaban, Anousheh Gholami, Chrysa Papagianni, John Baras

Introduces the joint satellite gateway placement and routing problem over an ISTN, for facilitating terrestrial-satellite communications while adhering to propagation latency requirements, in a cost-optimal manner. The corresponding load between selected gateways is also balanced.

A Cross-layer Optimal Co-design of Control and Networking in Time-sensitive Cyber-Physical Systems

Mohammad Mamduhi, Dipankar Maity, John Baras, Karl Johansson

In the design of cyber-physical systems (CPS) where multiple heterogeneous physical systems are coupled via a communication network, a key aspect is to study how network services are distributed among the users. The authors derive the joint optimal time-sensitive control and service allocation policies for each physical system.

KTH Royal Institute of Technology, Stockholm

Distributed Beamforming for Agents with Localization Errors

Erfaun Noorani, Yagiz Savas, Alec Koppel, John Baras, Ufuk Topcu, Brian M. Sadler

In this wireless networks paper, the authors formulate a subset selection problem that aims to find a subset of agents, each of which is equipped with an idealisotropic antenna, that forms a reliable communication linkwith a client through beamforming. They present three algorithms for solving the subset selection problem, and  discussed their computational complexity and optimality. All the proposed algorithms can be thought of as attempts towards approximate trade-off analysis and attempts towards finding desirable Pareto points.




Bounds for Discrepancies in the Hamming Space

Alerander Barg and Maxim Skriganov

Shows that the behavior of discrepancies in the Hamming space differs fundamentally because the volume of the ball in this space depends on its radius exponentially while such a dependence for the Riemannian manifolds is polynomial.

Stolarsky's Invariance Principle for Finite Metric Spaces

Alexander Barg

Considers the case of finite metric spaces, relating the quadratic discrepancy of a subset to a certain function of the distribution of distances in it. Using linear programming, the author finds several bounds on the minimal discrepancy and give examples of minimizing configurations. In particular, we show that all binary perfect codes have the smallest possible discrepancy.

Cyclic and Convolutional Codes with Locality

Zitan Chen, Alexander Barg

The work focuses on cyclic constructions of LRC codes and derives conditions on the zeros of the code that support the property of hierarchical locality. The authors obtain a general family of hierarchical LRC codes for a new range of code parameters.

Enabling optimal access and error correction for the repair of Reed-Solomon codes

Zitan Chen, Min Ye, Alexander Barg

Reed-Solomon codes possess a repair scheme that supports repair of failed nodes with optimal repair bandwidth. This paper extends this result in two directions.


Age of Incorrect Information for Remote Estimation of a Binary Markov Source

Clement Kam, Sastry Kompella, Anthony Ephremides

For monitoring applications, the Age of Information (AoI) metric has been the primary focus of recent research, but closely related to monitoring is the problem of real-time or remote estimation. Age of Information has been shown to be insufficient for minimizing remote estimation error, but recently a metric known as Age of Incorrect Information (AoII) was proposed that characterizes the cost of a monitor being in an erroneous state over time. This work studies the AoII metric in the simple context of monitoring a symmetric binary information source over a delay system with feedback. It compares three different performance metrics: real-time error, AoI, and AoII. For each metric, the optimal sampling problem as a Markov decision process is formulated. A dynamic programming algorithm to compute the optimal performance and policy is applied.

2020 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

Real-Time Reconstruction of a Counting Process through First-Come-First-Serve Queue Systems

Meng Wang, Wei Chen, Anthony Ephremides

One of the most critical problems for the emerging Internet of Things is the real-time remote reconstruction of ongoing signals (or their functions) from a set of measurements that are under-sampled and delayed in the network. The authors address this problem under three special sampling policies.

IEEE Transactions on Information Theory

Optimal Sampling Cost in Wireless Networks with Age of Information Constraints

Emmanouil Fountoulakis, Nikolaos Pappas, Marian Codreanu, Anthony Ephremides

Considers the problem of minimizing the time average cost of sampling and transmitting status updates by users over a wireless channel subject to average Age of Information constraints. A stochastic optimization problem is formulated and solved with a dynamic algorithm that takes decisions in a slot-by-slot basis.

Non-Linear Age of Information in a Discrete Time Queue: Stationary Distribution and Average Performance Analysis

Antzela Kosta, Nikolaos Pappas, Anthony Ephremides, Vangelis Angelakis

Investigates a sample path of the age of information (AoI) stochastic process and provides a general framework that establishes a relation among the AoI, the system delay, and the peak AoI. The aim is to be able to analyze any non-linear function of AoI and provide a wide range of potential uses of information ageing depending on the application.

Status Updates with Priorities: Lexicographic Optimality

Ali Maatouk, Yin Sun, Anthony Ephremides, Mohamad Assaad

Introduces the idea of lex-age-optimality that captures both age-optimality and the order of time-cruciality betweeen streams in a general multi-class priority-based scheduling scenario.

Laboratoire des Signaux & Systemes, L2S Central Supelec, France

On the Optimality of the Whittle’s Index Policy for Minimizing the Age of Information

Ali Maatouk, Saad Kriouile, Mohamad Assaad, Tony Ephremides

The authors prove that the Whittle’s index policy is age-optimal for the general asymmetrical case in the burgeoning many-users regime of Internet of Things interconnected devices.


Bandwidth Partition and Allocation for Efficient Spectrum Utilization in Cognitive Communications

Song Huang, Di Yuan, Anthony Ephremides

This article related to spectrum scarcity studies bandwidth partition and allocation to optimize spectrum utilitzation in cognitive communications under the interweave paradigm.

IEEE Journal of Communications & Networks


Multi-Corpus Acoustic-to-Articulatory Speech Inversion

Nadee Seneviratne, Ganesh Sivaraman, Carol Espy-Wilson

This paper proposes a multi-corpus speech inversion system for automatic speech recognition, pronounciation training and speech therapy.

Interspeech 2019

Assessing Neuromotor Coordination in Depression Using Inverted Vocal Tract Variables

Carol Espy-Wilson, Adam Lammert, Nadee Seneviratne, Thomas Quatieri

A new articulary inversion process provides a potentially powerful way of detecting depression based on speech patterns.

Interspeech 2019

Multi-modal learning for speech emotion recognition: An analysis and comparison of ASR outputs with ground truth transcription

Saurabh Sahu, Vikramjit Mitra, Nadee Seneviratne, Carol Espy-Wilson

The paper leverages multi-modal learning and automated speech recognition (ASR) systems toward building a speech-only emotion recognition model.

Interspeech 2019


Miniature Robot Path Planning for Bridge Inspection: Min-Max Cycle Cover-Based Approach

Michael Lin, Richard La

Develops a new algorithm to position depots where bridge inspection robots would be stored and recharged, and determines a set of sites for each robot to inspect on the bridge.

Queing Subject to Action-Dependent Server Performance: Utilization Rate Reduction

Michael Lin, Nuno Martins, Richard La

This work expands on stabilizability results recently obtained for a framework to establish methods to design scheduling policies that not only stabilize the queue but also reduce the utilization rate—understood as the infinite-horizon time-averaged expected portion of time the server is working.


Queing Subject to Action-Dependent Server Performance: Utilization Rate Reduction

Michael Lin, Nuno Martins, Richard La

This work expands on stabilizability results recently obtained for a framework to establish methods to design scheduling policies that not only stabilize the queue but also reduce the utilization rate—understood as the infinite-horizon time-averaged expected portion of time the server is working.


MagView: A Distributed Magnetic Covert Channel via Video Encoding and Decoding

Juchuan Zhang, Xiaoyu Ji, Wenyuan Xu, Yi-Chao Chen, Yuting Tang, Gang Qu

MagView is a distributed magnetic cover channel, where sensitive information is embedded in other data such as video and can be transmitted over an air-gapped internal network.

IEEE INFOCOM 2020: IEEE Conference on Computer Communications

BWOLF: Bit-Width Optimization for Statistical Divergence with -Logarithmic Functions

Qian Xu, Guowei Sun, Gang Qu

Approximate computing is a promising technique in improving the energy efficiency for error-resilient applications such as multimedia, signal processing and neural network. The paper shows how to apply the truncation method to the floating-point logarithmic operation. It analyzes the tradeoff between the precision of computation and the energy it requires, and derives a formula on the most energy-efficient implementation of the logarithm unit for a given error variance range. Based on this theoretical result, the paper proposes BWOLF (Bit-Width optimization for Logarithmic Function), which uses a sequential quadratic programming algorithm to determine the way to truncate data (i.e., bit-width optimization) in a program with logarithm and other arithmetic operations such that the energy consumption is minimized under a fixed error budget.

2020 IEEE 31st International Conference on Application-Specific Systems, Architectures and Processors

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

Huimin Hu, Ke Xiong, Gang Qu, Qiang Ni, Pingyi Fan, Khaled Ben Letaief

UAVs equipped with  communication transceivers can be used as aerial relays or mobile base stations to help improve the performance of terrestrial wireless communication systems. This paper investigates a UAV-assisted wireless powered IoT system, where a UAV takes off from a data center, flies to each of the ground sensor nodes (SNs) in order to transfer energy and collect data form the SNs, and then returns to the data center.

IEEE Internet of Things Journal

TCIM: Triangle Counting Acceleration with Processing-in-MRAM Architecture

Xueyan Wang, Jianlei Yang, Yinglin Zhao, Yingjie Qi, Meichen Liu, Xingzhou Cheng, Xiaotao Jia, Xiaoming Chen, Gang Qu and Weisheng Zhao

Triangle counting (TC) is a fundamental problem in graph analysis and has found numerous applications, which motivates many TC acceleration solutions in the traditional computing platforms like GPU and FPGA. However, these approaches suffer from the bandwidth bottleneck because TC calculation involves a large amount of data transfers. This paper proposes to overcome the challenge by designing a TC accelerator utilizing the emerging processing-in-MRAM (PIM) architecture.

New Secure Scan Design with PUF-based Key for Authentication

Gang Qu, Qidong Wang, Aijiao Cui, Huawei Li

A new secure scan design scheme for integrated circuit manufacturing with a unique PUF-based key for each design, to provide authentication and alleviate security concerns.

2020 IEEE 38th VLSI Test Symposium

Hardware security in spin-based computing-in-memory: Analysis, exploits and mitigation techniques

Xueyan Wang, Jianlei Yang, Yinglin Zhao, Xiaotao Jia, Gang Qu, Weisheng Zhao

Computing-in-memory (CIM) could alleviate the processor-memory data transfer bottleneck in traditional Von-Neumann architectures, and spintronics-based magnetic memory has demonstrated many facilitations in implementing CIM paradigm. Hardware security has become one of the major concerns in circuit designs. This paper, for the first time, investigates spin-based CIM from a security perspective.

ACM Journal on Emerging Technologies in Computing Systems

A Guaranteed Secure Scan Design based on Test Data Obfuscation by Cryptographic Hash

Aikiao Cui, Mengyang Li, Gang Qu, Huawei Li

A proposal to use 'cryptographic hash' to thwart attackers seeking the cipher keys of sensitive integrated circuits during manufacturing and testing.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

VoltJockey: Breaking SGX by Software-Controlled Voltage-Induced Hardware Faults

Pengfei Qiu, Dongsheng Wang, Yongqiang Lyu, Gang Qu

Intel software-guard extensions (SGX) allows applications to run in a trusted space (enclave), which provides a highly secure primitive for the running codes and data. The authors propose the first fault injection attack to break SGX by using voltage-induced hardware faults.


VoltJockey: Breaching TrustZone by Software-ControlledVoltage Manipulation over Multi-Core Frequencies

Pengfei Qiu, Dongsheng Wang, Yongqiang Lyu, Gang Qu

VoltJockey is an innovative software-controlled, hardware fault-based attack on multi-core processors that adopt dynamic voltage and frequency scaling (DVFS) techniques for energy efficiency.

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security

Physical Unclonable Function-based Key Sharing via Machine Leaning for IoT Security

Jiliang Zhang, Gang Qu

In many Industry Internet of Things (IIoT) applications, resources like CPU, memory, and battery power are limited and cannot afford the classic cryptographic security solutions. Silicon Physical Unclonable Function (PUF) is a lightweight security primitive that exploits manufacturing variations during the chip fabrication process for key generation and/or device authentication. The paper proposes a PUF-based key sharing method for the first time.

IEEE Transactions on Industrial Electronics

LEAP: A Lightweight Encryption and Authentication Protocol for In-Vehicle Communications

Zhaojun Lu, Qian Wang, Xi Chen, Gang Qu, Yongqiang Lyu, Zhenglin Liu

Controller Area Network is standard for in-vehicle communications, but attackers can compromise to remotely control vehicles. The researchers have developed a low-cost, high-efficiency encryption and authentication protocol to improve security.

Pass and Run: A Privacy Preserving Delay Tolerant Network Communication Protocol for CyberVehicles

Zhaojun Lu, Zhenglin Liu, Carson Dunbar, Mingze Gao, Gang Qu

This paper on intelligent transportation systems proposes pass and run protocol for vehicular delay tolerant networks to address vehicle location privacy in communicating with roadside units.

IEEE Design & Test



Benchmarking at the Frontier of Hardware Security: Lessons from Logic Locking

Michael Zuzak, Ankur Srivastava and 33 others

The authors prepared, ran, and reflected on the first benchmarking effort in logic locking for ICs, demonstrating the value of coordinated evaluation of hardware security techniques. With industry, government, and academic support, logic locking and other hardware security techniques can benefit from formal and ongoing evaluation. By making these processes regular and structured, researchers could submit new techniques on an ongoing basis for rigorous assessment. Such a process would increase confidence in hardware security technologies.

Spintronics-based Reconfigurable Ising Model Architecture

Ankit Mondal, Ankur Srivastava

The Ising model has been explored as a framework for modeling NP-hard problems, with several diverse systems proposed to solve it. The Magnetic Tunnel Junction (MTJ)-based Magnetic RAM is capable of replacing CMOS in memory chips. The authors propose the use of MTJs for representing the units of an Ising model and leveraging its intrinsic physics for finding the ground state of the system through annealing.


DRAMsim3: a Cycle-Accurate, Thermal-Capable DRAM Simulator

Ankur Srivastava , Zhiyuan Yang, Bruce Jacob, Shang Li, Dhiraj Reddy

The paper develops DRAMsim3, a successor to the earlier simulator DRAMSim2 developed by Jacob and his two former students Paul Rosenfeld (ECE Ph.D. 2014), and Elliott Cooper-Balis (ECE Ph.D. 2012). It is is a fast, cycle-accurate, validated, thermal-capable DRAM simulator that can simulate and model almost all modern DRAM protocols along with many of their unique features.

IEEE Computer Architecture Letters


Hardware-Software Co-Design Based Obfuscation of Hardware Accelerators

Abhishek Chakraborty and Ankur Srivastava

Paper on hardware-software co-design based obfuscation of hardware accelerators proposes hardware-software co-design based obfuscation approach to render unactivated accelerator chip functionally useless.

IEEE Annual Symposium on VLSI 2019

Energy-efficient Design of MTJ-based Neural Networks with Stochastic Computing

Ankit Mondal, Ankur Srivastava

The research proposes the use of magnetic tunnel junctions as stochastic number generators in an SC-based hardware implementation of neural networks. The proposed algorithm brings about a 40% reduction in energy consumption with less than 1% accuracy loss on the 2-layer MNIST network.

ACM Journal on Emerging Technologies in Computing Systems

Keynote: A Disquisition on Logic Locking

Abhishek Chakraborty, Nithyashankari Gummidipoondi Jayasankaran, Yuntao Liu, Jeyavijayan Rajendran, Ozgur Sinanoglu, Ankur Srivastava, Yang Xie, Muhammad Yasin, Michael Zuzak

A survey of the evolution of logic locking and a primer for researchers interested in developing novel techniques in new domains. The authors introduce various “cat and mouse” games involved in logic locking along with its novel applications—including, processor pipelines, graphics-processing units, and analog circuits.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems




Adversarial Attacks with Multiple Antennas against Deep Learning-Based Modulation Classifiers

Brian Kim, Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu, and Sennur Ulukus

From an adversarial machine learning perspective, the work shows how to use multiple antennas at the adversary to improve the adversarial (evasion) attack performance.

How to make 5G communications "invisible": Adversarial machine learning for wireless privacy

Brian Kim, Yalin Sagduyu, Kemal Davaslioglu, Tugba Erpek, Sennur Ulukus

Demonstrates the feasibility of covert communications in a wireless communication system when a cooperative jammer designs its perturbation signal to fool an eavesdropper's DL-based classfier into classifying ongoing transmissions as noise.

Private Set Intersection using Multi-Message Symmetric Private Information Retrieval

Zhusheng Wang, Karim Banawan, Sennur Ulukus

A study of the problem of private set intersection. Presents a novel capacity-achieving scheme that builds seamlessly over the multi-message private information retrieval scheme.

conference paper

Information Freshness in Cache Updating Systems

Melih Bastopcu, Sennur Ulukus

For a cache updating system with a source, a cache, and a user, the authors provide an alternating maximization-based method to find update rates for the cache(s) and the user to maximize the freshness of files at the user.

Channel-Aware Adversarial Attacks against Deep Learning-based Wireless Signal Classifiers

Brian Kim, Yalin E. Sagduyu, Kemal Davaslioglu, Tugba Erpek, Sennur Ulukus

Presents over-the-air adversarial attacks against deep learning-based modulation classifiers, accounting for realistic channel and broadcast transmission effects. A certified defense method using randomized smoothing is also included.

Selective Encoding Policies for Maximizing Information Freshness

Melih Bastopcu, Baturalp Buyukates, Sennur Ulukus

Proposes a selective encoding scheme for a status updating system in which an information source generates independent and identically distributed update packets based on an observed random variable X which takes n values based on a known pmf.

Semantic Private Information Retrieval

Sajani Vithana, Karim Banawan, Sennur Ulukus

The paper proposes two achievable schemes for achieving semantic private information retrieval capacity.

Age of Information with Gilbert-Elliot Servers and Samplers

Baturalp Buyukates, Sennur Ulukus

This work looks at an information update system in which status update packets are generated by a sampler and sent to a monitor node through a server node. Two scenarios are considered: Gilbert-Elliot service times and i.i.d. interarrival times; and Gilbert-Elliot interarrival times and i.i.d. service times. The authors determined the average age at the monitor node for both scenarios and characterized the age-optimal state transition matrix for the underlying Markov chain with and without an average cost constraint on the operation of the system.

Partial Updates: Losing Information for Freshness

Melih Bastopcu, Sennur Ulukus

This work considers an information updating system where a source produces updates as requested by a transmitter, and observes a tradeoff between the attained average age and the mutual information between the original and partial updates.

Who Should Google Scholar Update More Often?

Melih Bastopcu, Sennur Ulukus

This work addresses the problem of optimal operation of a resource-constrained sampler that wishes to track multiple independent counting processes in a way that is as up to date as possible.

Optimal Selective Encoding for Timely Updates

Melih Bastopcu, Baturalp Buyukates, Sennur Ulukus

The researchers consider a status updating system in which an information source generates independent and identically distributed update packets based on an observed random variable X which takes n values based on a known probability mass function (pmf). The proposed selective policy achieves a lower average age than encoding all the realizations and determine the age-optimal k values for arbitrary pmfs.

Optimal Selective Encoding for Timely Updates with Empty Symbol

Baturalp Buyukates, Melih Bastopcu, Sennur Ulukus

The authors consider two scenarios: when the empty symbol does not reset the age, and when the empty symbol resets the age. They find the time average age of information and the age-optimal real codeword lengths, including the codeword length for the empty symbol, for both of these scenarios. Through numerical evaluations for arbitrary pmfs, the authors show that this selective encoding policy yields a lower age at the receiver than encoding every realization, and find the corresponding age-optimal k values.

conference paper

Scaling Laws for Age of Information in Wireless Networks

Baturalp Buyukates, Alkan Soysal, Sennur Ulukus

A study of age of information in a multiple source-multiple destination setting with a focus on its scaling in large wireless networks.

Private Set Intersection: A Multi-Message Symmetric Private Information Retrieval Perspective

Zhusheng Wang, Karim Banawan, Sennur Ulukus

An information theoretic approach to the Private Set Intersection (PSI) problem shows that it can be successfully recast as a multi-message symmetric private information retrieval (MM-SPIR) problem with message size 1.


Age of Information for Updates with Distortion: Constant and Age-Dependent Distortion Constraints

Melih Bastopcu, Sennur Ulukus

The authors design an information update system that strikes a desired balance between information quality and freshness by solving for the optimum update scheme subject to a desired distortion level.

Timely Distributed Computation with Stragglers

Baturalp Buyukates, Sennur Ulukus

Investigates the age performance of uncoded and coded computation distribution algorithms and shows that a minimum data set-coded task distribution scheme asymptotically outperforms uncoded and repetition coded schemes.

Secure Degrees of Freedom in Networks with User Misbehavior

Karim Banawan, Sennur Ulukus

Explores the secure degrees of freedom of three new channel models: broadcast channel with combating helper, interference channel with selfish users, and multiple-access wiretap channel with deviating users. The paper investigates various malicious interactions that arise in networks, including active adversaries, and proves that a deviating user can drive the secure degrees of freedom to zero. However, the remaining users can exploit the intentional jamming signals as cooperative jamming signals against the eavesdropper and achieve an optimum secure degrees of freedom.



Exploiting Micro-Signals for Physiological Forensics

Min Wu

A variety of nearly invisible “micro-signals” have played important roles in media security and forensics. These noise-like micro-signals are ubiquitous and typically an order of magnitude lower in strength or scale than the dominant ones. They are traditionally removed or ignored as nuances outside the forensic domain. This talk discusses the recent research harnessing micro-signals to infer a person’s physiological conditions. One type of such signals is the subtle changes in facial skin color in accordance with the heartbeat. Video analysis of this repeating change provides a contact-free way to capture photo-plethysmogram (PPG). While heart rate can be tracked from videos of resting cases, it is challenging to do so for cases involving substantial motion, such as when a person is walking around, running on a treadmill, or driving on a bumpy road. It will be shown in this talk how the expertise with micro-signals from media forensics has enabled the exploration of new opportunities in physiological forensics and a broad range of applications.

Keynote Invited Talk at 8th ACM Workshop on Information Hiding and Multimedia Security June 22–24, 2020 (virtual conference)

Towards Threshold Invariant Fair Classification

Mingliang Chen, Min Wu

Introduces the notion of threshold invariant fairness, which enforces equitable performances across different groups independent of the decision threshold. The paper proposes to equalize the risk distributions among the groups via two approximation methods.

Time Reversal Based Robust Gesture Recognition Using Wifi

Sai Deepika Regani, Beibei Wang, Min Wu, K. J. Ray Liu

Gesture recognition using wireless sensing opened a plethora of applications in the field of human-computer interaction. However, most existing works are not robust without requiring wearables or tedious training/calibration. WiGRep is a time reversal-based gesture recognition approach using Wi-Fi, which can recognize different gestures by counting the number of repeating gesture segments. Built upon the time reversal phenomenon in RF transmission, the Time Reversal Resonating Strength is used to detect repeating patterns in a gesture. A robust low-complexity algorithm is proposed to accommodate possible variations of gestures and indoor environments. WiGRep is calibration-free and location and environment independent.

2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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