Communications, Networks, 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.

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Recent publications


On the Importance of Trust in Next-Generation Networked CPS Systems: An AI Perspective

Anousheh Gholami, Nariman Torkzaban, John Baras

The paper proposes trust as a measure to evaluate the status of network agents and improve the decision making process. The authors interpret trust as a relation among entities that participate in various protocols.

Value of Information in Feedback Control: Global Optimality

Touraj Soleymani, John Baras, Sandra Hirche, Karl Johansson

The rate-regulation trade-off defined between two objective functions, one penalizing the packet rate and the other, the state deviation and control effort, can express the performance bound of a networked control system. However, the characterization of the set of globally optimal solutions in this trade-off for multi-dimensional controlled Gauss-Markov processes has been an open problem. In the present article, we characterize a policy profile that belongs to this set. We prove that such a policy profile consists of a symmetric threshold triggering policy, which can be expressed in terms of the value of information, and a certainty-equivalent control policy, which uses a conditional expectation with linear dynamics.

Joint Satellite Gateway Deployment & Controller Placement in Software-Defined 5G-Satellite Integrated Networks

Nariman Torkzaban, John Baras

Several challenging optimization problems arise while considering the deployment of the space-air-ground integrated networks (SAGINs), among which the optimal satellite gateway deployment problem is of significant importance. Moreover, with the increasing interest in the software-defined integration of 5G networks and satellites, the existence of an effective scheme for optimal placement of SDN controllers, is essential. The authors discuss the interrelation between the two problems above and propose suitable methods to solve them under various network design criteria.

Value of Information in Networked Control Systems Subject to Delay

Siyi Wang, Qingchen Liu, Precious Ugo Abara, John Baras, Sandra Hirche

The authors address the trade-off between control performance and communication cost for a multi-loop NCS. They analytically characterize the relationship between quality of control and VoI function. The derived VoI functions properly reflect the relevance of information including temporal aspects for the control task and are parameterized by the coupling variables such as delay induced by the network. The data packet is transmitted through the network whenever the value of information is positive to preserve the control tasks. Finally, the numerical simulation is provided to verify the effectiveness of the VoI-based scheduling policy.


Detection of Dynamically Changing Leaders in Complex Swarms from Observed Dynamic Data

Christos Mavridis, Nilesh Suriyarachchi, John Baras

Considers the problem of defending against adversarial attacks from UAV swarms performing complex maneuvers,driven by multiple, dynamically changing, leaders.

GameSec 2020 Conference

Trust-Aware Service Function Chain Embedding: A Path-Based Approach

Nariman Torkzaban, John Baras

Introduces a framework for the path-based trust-aware service chain embedding problem. The paper extends a previous work on trust-aware service chain embedding with generalizing the role of trust by incorporating the trustworthiness of the service network links and substrate network paths into the SFC embedding decision process.

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.


Repair of RS codes with optimal access and error correction

Zitan Chen, Min Ye, Alexander Barg

Addresses two aspects of the repair problem of Reed-Solomon codes.

2020 IEEE International Symposium on Information Theory (ISIT)

Cyclic LRC codes with hierarchy and availability

Zitan Chen, Alexander Barg

Locally recoverable (LRC) codes form a family of erasure codes, motivated by applications in distributed storage, that support repair of a failed storage node by contacting a small number of other nodes in the cluster. This paper presents two results regarding codes with hierarchical locality and codes with availability.

2020 IEEE International Symposium on Information Theory (ISIT)

Recoverable Systems

Ohad Elishco, Alexander Barg

Motivated by the established notion of storage codes, the authors consider sets of infinite sequences over a finite alphabet such that every k-tuple of consecutive entries is uniquely recoverable from its l-neighborhood in the sequence.

Bounds for Discrepancies in the Hamming Space

Alexander Barg, 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.


Semantic Communications in Networked Systems

Elif Uysal, Onur Kaya, Anthony Ephremides, James Gross, Marian Codreanu, Petar Popovski, Mohamad Assaad, Gianluigi Liva, Andrea Munari, Touraj Soleymani, Beatriz Soret, Karl Henrik Johansson

A vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information for communications and control in networked systems.

Age of Information: An Indirect Way To Improve Control System Performance

Onur Ayan, Anthony Ephremides, Wolfgang Kellerer

The authors consider N heterogeneous control sub-systems sharing a wireless communication channel. Network resources are limited and are allocated by a centralized scheduler. Each transmission is lost with a probability that is higher or lower depending on the portion each sub-system receives from the pool of network resources. Furthermore, state measurements go through a first come first serve (FCFS) Geo/Geo/1 transmission queue after they are generated by each sensor. In such a setting, the information at each remote controller that is observing the state measurements through the wireless channel gets outdated. Age of Information (AoI)captures this effect and measures the information freshness a teach controller. By definition, AoI is control unaware thus not a standalone metric to capture the heterogeneous requirements of control sub-systems. However, we show how the stationary distribution of Age of information (AoI) can be employed as an intermediate metric to obtain the expected control performance in the network. As a result, we solve the resource allocation problem optimally and show by simulations that we are able to improve the control performance indirectly through AoI.

IEEE INFOCOM: Age of Information Workshop 2021

Joint Sampling and Transmission Policies for Minimizing Cost under AoI Constraints

Emmanouil Fountoulakis, Marian Codreanu, Anthony Ephremides, Nikolaos Pappas

This work considers the problem of jointly minimizing the average cost of sampling and transmitting status updates by users over a wireless channel subject to average Age of Information (AoI) constraints.

Minimizing Age of Incorrect Information for Unreliable Channel with Power Constraint

Yuotao Chen, Anthony Ephremides

Age of Incorrect Information (AoII) is a newly introduced performance metric that is adaptable to a variety of communication goals. The fundamental nature of AoII has been elusive so far. In this work, the authors consider the AoII in a system where a transmitter sends updates about a multi-state Markovian source to a remote receiver through an unreliable channel. The communication goal is to minimize AoII subject to a power constraint. The problem is cast into a Constrained Markov Decision Process. The research proves that the optimal policy is a mixture of two deterministic threshold policies.


Dynamic Power Control for Time-Critical Networking with Heterogeneous Traffic

Emmanouil Fountoulakis, Nikolaos Pappas, Anthony Ephremides

Future wireless networks will be characterized by heterogeneous traffic requirements. Such requirements can below-latency or minimum-throughput, so the network must adjust to different needs. Usually, users with low-latency requirements have to deliver their demand within a specific time frame, i.e., before a deadline, and they co-exist with throughput-oriented users. In addition, the users are mobile and they share the same wireless channel. Therefore, they have to adjust their power transmission to achieve reliable communication. However, due to the limited-power budget of wireless mobile devices, a power-efficient scheduling scheme is required by the network. The authors cast a stochastic network optimization problem for minimizing the packet drop rate while guaranteeing a minimum-throughput and taking into account the limited-power capabilities of the users.

Asymptotically Optimal Scheduling Policy For Minimizing The Age of Information

Ali Maatouk, Saad Kriouile, Mohamad Assaad, Anthony Ephremides

This paper considers the average age minimization problem where a central entity schedules M users among the N available users for transmission over unreliable channels.

2020 IEEE International Symposium on Information Theory (ISIT)

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


Speech acoustics and mental health assessment

Carol Espy-Wilson

Dr. Espy-Wilson discusses a speech inversion system her group has developed that maps the acoustic signal to vocal tract variables (TVs). The trajectories of the TVs show the timing and spatial movement of speech gestures. She explains how her group uses machine learning techniques to compute articulatory coordination features (ACFs) from the TVs. The ACFs serve as an input into a deep learning model for mental health classification. Espy-Wilson also illustrates the key acoustic differences between speech produced by subjects when they are mentally ill relative to when they are in remission and relative to healthy controls. The ultimate goal of this research is the development of a technology (perhaps an app) for patients that can help them, their therapists and caregivers monitor their mental health status between therapy sessions.

Keynote speech at the 2021 Acoustical Society of America Annual Meeting, June 8, 2021
View a press release from the Acoustical Society of America about this speech

Speech-based Depression Severity Level Classification Using a Multi-Stage Dilated CNN-LSTM Model

Nadee Seneviratne, Carol Espy-Wilson

The paper proposes a new multi-stage architecture trained on vocal tract variable (TV)-based articulatory coordination features (ACFs) for depression severity classification which clearly outperforms the baseline models. The authors establish that the robustness of ACFs based on TVs holds beyond mere detection of depression and even in severity level classification. This work can be extended to develop a multi-modal system that can take advantage of textual information obtained through Automatic Speech Recognition tools. Linguistic features can reveal important information regarding the verbal content of a depressed patient relating to their mental health condition.; accepted for Interspeech2021, Aug. 30-Sept. 3, 2021

Inverted Vocal Tract Variables and Facial Action Units to Quantify Neuromotor Coordination in Schizophrenia

Yashish Maduwantha, Chris Kitchen, Deanna L. Kelly, Carol Espy-Wilson

This study, conducted with AIM-HI funding, investigates speech articulatory coordination in schizophrenia subjects exhibiting strong positive symptoms (e.g.hallucinations and delusions), using a time delay embedded correlation analysis. It finds a distinction between healthy and schizophrenia subjects in neuromotor coordination in speech.


Deep Learning Based Generalized Models for Depression Classification

Nadee Seneviratne, Carol Espy-Wilson

The paper develops a generalized classifier for depression detection using a dilated convolutional neural network which is trained on articulatory coordination features (ACFs) extracted from two depression databases.; accepted for Interspeech2021, Aug. 30-Sept. 3, 2021

Extended Study on the Use of Vocal Tract Variables to Quantify Neuromotor Coordination in Depression

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

Changes in speech production that occur as a result of psychomotor slowing, a key feature of Major Depressive Disorder(MDD), are used to non-invasively diagnose MDD. In previous work using data from seven subjects, the authors showed that using speech-inverted vocal tract variables (TVs) as a direct measure of articulation to quantify changes in the way speech is produced when depressed relative to being not depressed out-performs formant information as a proxy for articulatory information. In this paper, the authors make significant extensions by using more subjects, taking into account more eigenvalue features and incorporating TVs related to place of articulation and the glottal source, resulting in a significant improvement in accuracy.

Interspeech 2020


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.


Distribution Privacy Under Function Recoverability

Ajaykrishnan Nageswaran; Prakash Narayan

In this paper, a user generates n independent and identically distributed data random variables with a probability mass function that must be guarded from a querier. The querier must recover, with a prescribed accuracy, a given function of the data from each of n independent and identically distributed user-devised query responses. The user chooses the data pmf and the random query responses to maximize distribution privacy as gauged by the divergence between the pmf and the querier's best estimate of it based on the n query responses. A general lower bound is provided for distribution privacy; and, for the case of binary valued functions, upper and lower bounds that converge to said bound as n grows. Explicit strategies for the user and querier are identified.

2020 IEEE International Symposium on Information Theory (ISIT)


Using Online Planning and Acting to Recover from Cyberattacks on Software-defined Networks

Sunandita Patra, Alexander Velazquez, Myong Kang, Dana Nau

The authors describe ACR-SDN, a system to monitor, diagnose, and quickly respond to attacks or failures that may occur in software-defined networks (SDNs). An integral part of ACR-SDN is its use of RAE+UPOM, an automated acting and planning engine that uses hierarchical refinement. To advise ACR-SDN on how to recover a target system from faults and attacks, RAE+UPOM uses attack recovery procedures writ-ten as hierarchical operational models. Our experimental results show that the use of refinement planning in ACR-SDN is successful in recovering SDNs from attacks with respect to three performance metrics: estimated time for recovery, efficiency, and retry ratio.

Association for the Advancement of Artificial Intelligence


Novel Memristor-based Nonvolatile D Latch and Flip-flop Designs

Zhenxing Chang, Aijiao Cui, Ziming Wang, Gang Qu

Sequential devices are the fundamental building blocks for almost all digital electronic systems with memory. Due to the importance of instant data recovery after unexpected data loss such as unplanned power down, sequential devices need to have the nonvolatile property, which motivates the recent research and practice in integrating the nonvolatile memristor into CMOS devices. In this paper, the authors study how to apply this approach to improve the quality of nonvolatile D latch.

22nd IEEE International Symposium on Quality Electronic Design, 2021

Don't forget to sign the gradients!

Omid Aramoon, Pin-Yu Chen, Gang Qu

Engineering a top-notch deep learning model is an expensive procedure that involves collecting data, hiring human resources with expertise in machine learning, and providing high computational resources. For that reason, deep learning models are considered as valuable Intellectual Properties(IPs) of the model vendors. To ensure reliable commercialization of deep learning models, it is crucial to develop techniques to protect model vendors against IP infringements. One of such techniques that recently has shown great promise is digital watermarking. The authors present GradSigns, a novel watermarking framework for deep neural networks (DNNs). GradSigns is robust against all known counter-watermark attacks and can embed a large amount of information into DNNs.

Proceedings of the 4th MLSys Conference, 2021

AutoTEA: Automated Transistor-level Efficient and Accurate Optimization for GRM FPGA Design

Yanze Li, Yufan Zhang, Jiafeng Liu, Jian Wang, Jinmei Lai, Gang Qu

With emerging applications such as AI/ML, exploring the FPGA design space for optimal performance becomes important and challenging. The popular tool COFFE was built on an academic architecture and cannot be applied directly to modern FPGA chips with GRM (general routing matrix) architecture. This paper presents a recently developed fully Automated Transistor-level Efficient and Accurate tool, AutoTEA, which features accurate area and delay models, and a fast solution space exploration method for GRM FPGA circuit optimization. The results show that AutoTEA is able to improve a previously manually optimized design (on the tape-out FPGA chip) by 11%.

IEEE 29th Annual International Symposium on Field-Programmable Custom Computing Machines

Voltage Over-scaling-based Lightweight Authentication for IoT Security

Jiliang Zhang, Chaoqun Shen, Haihan Su, Md Tanvir Arafin, Gang Qu

The paper presents machine learning-based modeling attacks to break authentication.

IEEE Transactions on Computers

RIME: A Scalable and Energy-Efficient Processing-In-Memory Architecture for Floating-Point Operations

Zhaojun Lu, Md Tanvir Arafin, Gang Qu

Explores the analog properties of the resistive random access memory (RRAM) crossbar and propose a scalable RRAM-based in-memory floating-point computation architeture (RIME).

ASPDAC '21: Proceedings of the 26th Asia and South Pacific Design Automation Conference

Security of Neural Networks from Hardware Perspective: A Survey and Beyond

Qian Xu, Md Tanvir Arafin, Gang Qu

A survey of the security challenges and opportunities in computing hardware used in implementing deep neural networks.

ASPDAC '21: Proceedings of the 26th Asia and South Pacific Design Automation Conference

Integrated Circuit Digital Fingerprinting–Based Authentication

Xi Chen, Gang Qu

Digital fingerprinting was first proposed in 1999 for the protection of very large scale integration (VLSI) design intellectual properties (IP). Various techniques have been developed to make each copy of the IP unique in order to track the usage of the IP and trace any traitors who have misused the IP. The authors review the general requirements and the available schemes to create digital fingerprints for IP protection. They discuss the challenges of applying these methods for device authentication in IoT applications and how to overcome these difficulties.

Chapter 1 in Authentication of Embedded Devices (Springer book)

Hardware-Based Authentication Applications

Md Tanvir Arafin, Gang Qu

The authors discuss hardware-oriented security applications for the authentication of users, devices, and data. These applications illustrate the use of physical properties of computing hardware such as main memory, computing units, and clocks for authentication applications in low power on the IoT devices and systems.

Chapter 6 in Authentication of Embedded Devices (Springer book)


VoltJockey: Abusing the Processor Voltage to Break Arm TrustZone

Pengfei Qui, Dongsheng Wang, Yongqiang Lyu, Gang Qu

Based on the concept of hardware separation, ARM introduced TrustZone to build a trusted execution environment for applications. It has been quite successful in defending against various software attacks and forcing attackers to explore vulnerabilities in interface designs and side channels. In this article, we propose an innovative software-controlled hardware fault-based attack, VoltJockey, on multi-core processors that adopt dynamic voltage and frequency scaling (DVFS) techniques for energy efficiency. We deliberately manipulate the processor voltage via DVFS to induce hardware faults into the victim cores, and therefore breaking TrustZone. The entire attack process is based on software without any involvement of hardware, which makes VoltJockey stealthy and hard to prevent.

ACM GetMobile: Mobile Computing and Communications

VoltJockey: Abusing the Processor Voltage to Break Arm TrustZone

Pengfei Qui, Dongsheng Wang, Yongqiang Lyu, Gang Qu

Based on the concept of hardware separation, ARM introduced TrustZone to build a trusted execution environment for applications. It has been quite successful in defending against various software attacks and forcing attackers to explore vulnerabilities in interface designs and side channels. In this article, we propose an innovative software-controlled hardware fault-based attack, VoltJockey, on multi-core processors that adopt dynamic voltage and frequency scaling (DVFS) techniques for energy efficiency. We deliberately manipulate the processor voltage via DVFS to induce hardware faults into the victim cores, and therefore breaking TrustZone. The entire attack process is based on software without any involvement of hardware, which makes VoltJockey stealthy and hard to prevent.

ACM GetMobile: Mobile Computing and Communications

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



Trace Logic Locking: Improving the Parametric Space of Logic Locking

Michael Zuzak, Yuntao Liu, Ankur Srivastava

The paper proposes trace logic locking (TLL), a provably secure and scalable enhancement to existing logic locking techniques which locks a sequence of primary inputs, known as a trace. Through architectural simulations, the paper shows that TLL achieved both error severity and SAT resilience simultaneously.

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

Evaluating the Security of Delay-Locked Circuits

Abhishek Chakraborty, Yuntao Liu, Ankur Srivastava

A novel SAT formulation-based attack approach called TimingSAT to deobfuscate the functionalities of such delay locked designs.

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

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




Guest Editorial: Age of Information

Roy Yates, Yin Sun, D. Richard Brown III, Sanjit K. Kaul, Eytan Modiano, Sennur Ulukus

The authors are guest editors for a special issue on Age of Information of the IEEE Journal on Selected Areas in Communications. These editors have contributed a survey that introduces research in data freshness and provides a broad summary of recent work. The survey is followed by 20 contributed papers that reflect the state of the art in AoI research.

IEEE Journal on Selected Areas in Communications, special issue on Age of Information in real-time cyberphysical systems

Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyond

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

The authors present an adversarial attack by generating adversarial perturbations to manipulate over-the-air captured RSSs as input to the DNN. This attack reduces the IA performance significantly and fools the DNN into choosing beams with small RSSs compared to jamming attacks with Gaussian or uniform noise.

Age of Gossip in Networks with Community Structure

Baturalp Buyukates, Melih Bastopcu, Sennur Ulukus

The authors use the version age metric to quantify information timeliness at receiver nodes. They consider disconnected, ring, and fully connected network topologies for each cluster.

Symmetric Private Information Retrieval with User-Side Common Randomness

Zhusheng Wang, Sennur Ulukus

A look at the problem of symmetric private information retrieval (SPIR) with user-side common randomness.

Freshness Based Cache Updating in Parallel Relay Networks

Priyanka Kaswan, Melih Bastopcu, Sennur Ulukus

The paper observes that freshness for a file increases with increase in consolidation of rates across caches. To solve the multi-cache problem, the authors first solve the auxiliary problem of a single-cache system. They then rework this auxiliary solution to a parallel-cache network by consolidating rates to single routes as much as possible. This yields an approximate (sub-optimal) solution for the original problem.

Cache Freshness in Information Updating Systems

Melih Bastopcu, Sennur Ulukus

The authors consider a cache updating system with a source, m caches and a user. They note that for a given set of update rates for the user (resp. for the caches), the optimal rate allocation policy for the caches (resp. for the user) is a threshold policy, where the optimal update rates for rapidly changing files at the source may be equal to zero.

Sennur Ulukus website


Timely Communication in Federated Learning

Baturalp Buyukates, Sennur Ulukus

Considers a federated learning framework in which a parameter server trains a global model by using n clients without actually storing the client data centrally at a cloud server. Focusing on a setting where the client datasets are highly changing and temporal in nature, the authors investigate the timeliness of model updates and propose a novel timely communication scheme.

Timely Updates in Distributed Computation Systems with Stragglers

Baturalp Buyukates, Sennur Ulukus

A study of the age performance of uncoded and coded (repetition coded, MDS coded, and multi-message MDS (MM-MDS) coded) schemes in the presence of stragglers under i.i.d. exponential transmission delays and i.i.d. shifted exponential computation times.

2020 Asilomar Conference on Signals, Systems and Computers

Gradient Coding with Dynamic Clustering for Straggler Mitigation

Baturalp Buyukates, Emre Ozfatura, Sennur Ulukus, and Deniz Gündüz

Proposes a novel gradient coding (GC) scheme that utilizes dynamic clustering, denoted by GC-DC, to speed up the gradient calculation.

Multi-Party Private Set Intersection: An Information-Theoretic Approach

Zhusheng Wang, Karim Banawan, Sennur Ulukus

Proposes a novel achievable scheme for the MP-PSI problem. The scheme hinges on a careful design and sharing of randomness between client parties prior to commencing the MP-PSI operation.

Maximizing Information Freshness in Caching Systems with Limited Caching Storage Capacity

Melih Bastopcu, Sennur Ulukus

Considers a cache updating system with a source, a cache with limited storage capacity, and a user. Studies the tradeoff between storing files at the cahce and directly opbtining files from the source at the expense of additional transmission times.

Semantic Private Information Retrieval: Effects of Heterogeneous Message Sizes and Popularities

Sajani Vithana, Karim Banawan, Sennur Ulukus

The authors derive conditions for the semantic PIR capacity to exceed the classical PIR capacity with equal priors and sizes. Our results show that the semantic PIR capacity can be larger than the classical PIR capacity when longer messages have higher popularities.

Age of Information: An Introduction and Survey

Roy D. Yates, Yin Sun, D. Richard Brown III, Sanjit K. Kaul, Eytan Modiano, Sennur Ulukus

A summary of recent contributions in the broad area of age of information (AoI).

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

Brian Kim, Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu, 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)