Ioannis Zografopoulos

@umb.edu

Assistant Professor
University of Massachusetts Boston

https://researchid.co/zografop

Ioannis Zografopoulos is an assistant professor in the Engineering Department of the College of Science and Mathematics at the University of Massachusetts (UMass) Boston. He received his Ph.D. in Electrical and Computer Engineering from King Abdullah University of Science and Technology (KAUST) in 2023. Prior, he graduated with B.Eng. and M.Eng. degrees in Computer, Communications, and Network Engineering, and an M.Sc. degree in Electrical and Computer Engineering from the University of Thessaly, Volos, Greece, in 2014 and 2015, respectively.

His research interests include cyber-physical systems security, with an emphasis on embedded systems for industrial, distributed energy, and power grid applications.

EDUCATION

King Abdullah University of Science and Technology Thuwal, Saudi Arabia
Ph.D. candidate in Electrical & Computer Engineering, CEMSE division (Sep 2021 - Jul 2023)

Florida State University Tallahassee, Florida
Ph.D. candidate in Electrical & Computer Engineering, dep. ECE (Jan 2019 - Aug 2021)

University of Thessaly Volos, Greece
M.Sc. in Science and Technology of Electrical & Computer Engineering (Nov 2015)

University of Thessaly Volos, Greece
Diploma (5-year B.Eng. + M.Eng.) in Computer, Communications & Networks Engineering (Aug 2014)

RESEARCH INTERESTS

Electric grid security and resilience with integration of renewable and distributed energy resources;
Cyberphysical systems and Internet-of-Things (IoT);
Hardware security and embedded systems security;
Industrial system and critical infrastructure security;
Real-time controller- and hardware-

Scopus Publications

1119

Scholar Citations

Scholar h-index

Scholar i10-index

Scopus Publications

Event-triggered islanding in inverter-based grids
Ioannis Zografopoulos and Charalambos Konstantinou
Elsevier BV

Cyber-Physical Interdependence for Power System Operation and Control
Ioannis Zografopoulos, Ankur Srivastava, Charalambos Konstantinou, Junbo Zhao, Amir Abiri Jahromi, Astha Chawla, Bang Nguyen, Bu Siqi, Chendan Li, Fei Teng,et al.
Institute of Electrical and Electronics Engineers (IEEE)

Distribution System Behind-the-Meter DERs: Estimation, Uncertainty Quantification, and Control
Ankur Srivastava, Junbo Zhao, Hao Zhu, Fei Ding, Shunbo Lei, Ioannis Zografopoulos, Rabab Haider, Soroush Vahedi, Wenyu Wang, Gustavo Valverde,et al.
Institute of Electrical and Electronics Engineers (IEEE)

Distributed Energy Resources Cybersecurity Outlook: Vulnerabilities, Attacks, Impacts, and Mitigations
Ioannis Zografopoulos, Nikos D. Hatziargyriou, and Charalambos Konstantinou
Institute of Electrical and Electronics Engineers (IEEE)
The digitization and decentralization of the electric power grid are key thrusts for an economically and environmentally sustainable future. Towards this goal, distributed energy resources (DER), including rooftop solar panels, battery storage, electric vehicles, etc., are becoming ubiquitous in power systems. Power utilities benefit from DERs as they minimize operational costs; at the same time, DERs grant users and aggregators control over the power they produce and consume. DERs are interconnected, interoperable, and support remotely controllable features, thus, their cybersecurity is of cardinal importance. DER communication dependencies and the diversity of DER architectures widen the threat surface and aggravate the cybersecurity posture of power systems. In this work, we focus on security oversights that reside in the cyber and physical layers of DERs and can jeopardize grid operations. Existing works have underlined the impact of cyberattacks targeting DER assets, however, they either focus on specific system components (e.g., communication protocols), do not consider the mission-critical objectives of DERs, or neglect the adversarial perspective (e.g., adversary/attack models) altogether. To address these omissions, we comprehensively analyze adversarial capabilities and objectives when manipulating DER assets, and then present how protocol and device-level vulnerabilities can materialize into cyberattacks impacting power system operations. Finally, we provide mitigation strategies to thwart adversaries and directions for future DER cybersecurity research.

Experimental Impact Analysis of Cyberattacks in Power Systems Using Digital Real-Time Testbeds
Kalinath Katuri, Ioannis Zografopoulos, Ha Thi Nguyen, and Charalambos Konstantinou
IEEE
Smart grid advancements and the increased integration of digital devices have transformed the existing power grid into a cyber-physical energy system. This reshaping of the current power system can make it vulnerable to cyber-attacks, which could cause irreversible damage to the energy infrastructure resulting in the loss of power, equipment damage, etc. Constant threats emphasize the importance of cybersecurity investigations. At the same time, developing cyber-physical system (CPS) simulation testbeds is crucial for vulnerability assessment and the implementation and validation of security solutions. In this paper, two separate real-time CPS testbeds are developed based on the availability of local research facilities for impact analysis of denial-of-service (DoS) attacks on microgrids. The two configurations are implemented using two different digital real-time simulator systems, one using the real-time digital simulator (RTDS) with a hardware-in-the-loop (HIL) setup and the other one using OPAL-RT with ExataCPS to emulate the cyber-layer infrastructure. Both testbeds demonstrate the impact of DoS attacks on microgrid control and protection operation.

A Resource Allocation Scheme for Energy Demand Management in 6G-enabled Smart Grid
Shafkat Islam, Ioannis Zografopoulos, Md Tamjid Hossain, Shahriar Badsha, and Charalambos Konstantinou
IEEE
Smart grid (SG) systems enhance grid resilience and efficient operation, leveraging the bidirectional flow of energy and information between generation facilities and prosumers. For energy demand management (EDM), the SG network requires computing a large amount of data generated by massive Internet-of-things sensors and advanced metering infrastructure (AMI) with minimal latency. This paper proposes a deep reinforcement learning (DRL)-based resource allocation scheme in a 6G-enabled SG edge network to offload resource-consuming EDM computation to edge servers. Automatic resource provisioning is achieved by harnessing the computational capabilities of smart meters in the dynamic edge network. To enforce DRL-assisted policies in dense 6G networks, the state information from multiple edge servers is required. However, adversaries can “poison” such information through false state injection (FSI) attacks, exhausting SG edge computing resources. Toward addressing this issue, we investigate the impact of such FSI attacks with respect to abusive utilization of edge resources, and develop a lightweight FSI detection mechanism based on supervised classifiers. Simulation results demonstrate the efficacy of DRL in dynamic resource allocation, the impact of the FSI attacks, and the effectiveness of the detection technique.

Time series-based detection and impact analysis of firmware attacks in microgrids
Ioannis Zografopoulos, Abraham Peedikayil Kuruvila, Kanad Basu, and Charalambos Konstantinou
Elsevier BV

Detection of Malicious Attacks in Autonomous Cyber-Physical Inverter-Based Microgrids
Ioannis Zografopoulos and Charalambos Konstantinou
Institute of Electrical and Electronics Engineers (IEEE)
The distributed generation capabilities of microgrids (MGs) arise as essential assets in enhancing grid resilience. The integration of distributed energy sources, controllable loads, and prosumers necessitates the deployment of potent control and communication synergies. While those synergies transform MGs into cyber-physical systems through information technologies able to sense, control, and actuate local resources and loads, they inadvertently expose MGs to cyber-attack threats. Increasing the security of critical communication and control systems against “black swan” events, i.e., high-impact low-probability cyber-physical incidents, is a major priority for MG operations. Such incidents, if left unabated, can intensify and elicit system dynamics instability, eventually causing outages and system failures. In this article, we develop an integrated approach for multiagent MG systems able to perform the detection of malicious cyber-physical attacks based on subspace methods. We employ the small-signal model of an autonomous/islanded MG and consider different attack models targeting the MG’s secondary frequency control. The attack detector is constructed via identifying the stable kernel representation of the autonomous cyber-physical MG in the attack-free case. We illustrate the impact of the attack models as well as the feasibility of the developed detection method in simulation models of the Canadian urban benchmark distribution system.

Mitigation of Cyberattacks through Battery Storage for Stable Microgrid Operation
Ioannis Zografopoulos, Panagiotis Karamichailidis, Andreas T. Procopiou, Fei Teng, George C. Konstantopoulos, and Charalambos Konstantinou
IEEE
In this paper, we present a mitigation methodology that leverages battery energy storage system (BESS) resources in coordination with microgrid (MG) ancillary services to maintain power system operations during cyberattacks. The control of MG agents is achieved in a distributed fashion, and once a misbehaving agent is detected, the MG,${}^{\\prime}\\mathbf{s}$ mode supervisory controller (MSC) isolates the compromised agent and initiates self-healing procedures to support the power demand and restore the compromised agent. Our results demonstrate the practicality of the proposed attack mitigation strategy and how grid resilience can be improved using BESS synergies. Simulations are performed on a modified version of the Canadian urban benchmark distribution model.

Behind Closed Doors: Process-Level Rootkit Attacks in Cyber-Physical Microgrid Systems
Suman Rath, Ioannis Zografopoulos, Pedro P. Vergara, Vassilis C. Nikolaidis, and Charalambos Konstantinou
IEEE
Embedded controllers, sensors, actuators, advanced metering infrastructure, etc. are cornerstone components of cyber-physical energy systems such as microgrids (MGs). Harnessing their monitoring and control functionalities, sophisticated schemes enhancing MG stability can be deployed. However, the deployment of ‘smart’ assets increases the threat surface. Power systems possess mechanisms capable of detecting abnormal operations. Furthermore, the lack of sophistication in attack strategies can render them detectable since they blindly violate power system semantics. On the other hand, the recent increase of process-aware rootkits that can attain persistence and compromise operations in undetectable ways requires special attention. In this work, we investigate the steps followed by stealthy rootkits at the process level of control systems pre- and post-compromise. We investigate the rootkits' precompromise stage involving the deployment to multiple system locations and aggregation of system-specific information to build a neural network-based virtual data-driven model (VDDM) of the system. Then, during the weaponization phase, we demonstrate how the VDDM measurement predictions are paramount, first to orchestrate crippling attacks from multiple system standpoints, maximizing the impact, and second, impede detection blinding system operator situational awareness.

Consumer, Commercial, and Industrial IoT (In)Security: Attack Taxonomy and Case Studies
Christos Xenofontos, Ioannis Zografopoulos, Charalambos Konstantinou, Alireza Jolfaei, Muhammad Khurram Khan, and Kim-Kwang Raymond Choo
Institute of Electrical and Electronics Engineers (IEEE)
Internet of Things (IoT) devices are becoming ubiquitous in our lives, with applications spanning from the consumer domain to commercial and industrial systems. The steep growth and vast adoption of IoT devices reinforce the importance of sound and robust cybersecurity practices during the device development life cycles. IoT-related vulnerabilities, if successfully exploited can affect, not only the device itself but also the application field in which the IoT device operates. Evidently, identifying and addressing every single vulnerability are an arduous, if not impossible, task. Attack taxonomies can assist in classifying attacks and their corresponding vulnerabilities. Security countermeasures and best practices can then be leveraged to mitigate threats and vulnerabilities before they emerge into catastrophic attacks and ensure overall secure IoT operation. Therefore, in this article, we provide an attack taxonomy, which takes into consideration the different layers of the IoT stack, i.e., device, infrastructure, communication, and service, and each layer’s designated characteristics, which can be exploited by adversaries. Furthermore, using nine real-world cybersecurity incidents that had targeted IoT devices deployed in the consumer, commercial, and industrial sectors, we describe the IoT-related vulnerabilities, exploitation procedures, attacks, impacts, and potential mitigation mechanisms and protection strategies. These (and many other) incidents highlight the underlying security concerns of IoT systems and demonstrate the potential attack impacts of such connected ecosystems, while the proposed taxonomy provides a systematic procedure to categorize attacks based on the affected layer and corresponding impact.

Hardware-assisted detection of firmware attacks in inverter-based cyberphysical microgrids
Abraham Peedikayil Kuruvila, Ioannis Zografopoulos, Kanad Basu, and Charalambos Konstantinou
Elsevier BV

Contactless Technologies for Smart Cities: Big Data, IoT, and Cloud Infrastructures
Arunmozhi Manimuthu, Venugopal Dharshini, Ioannis Zografopoulos, M. K. Priyan, and Charalambos Konstantinou
Springer Science and Business Media LLC

Stealthy Rootkit Attacks on Cyber-Physical Microgrids: Poster
Suman Rath, Ioannis Zografopoulos, and Charalambos Konstantinou
ACM
Cyber-physical microgrids hold the key to a carbon-neutral power sector since they enable renewable and distributed energy resource integration, can alleviate overloaded distribution systems, and provide economic energy by generating and consuming power locally. The utilization of cyber-physical assets such as controllers, IoT sensors and actuators, and communication devices can enhance the stability and improve the control of microgrids. However, such assets, if maliciously operated, can become attack entry points and jeopardize the grid operation. Blind and uncoordinated cyber-attacks can be identified by existing security measures overcoming potential operational disruptions. However, rootkit attacks can stay hidden within cyber-physical systems and leverage system information to mask their presence. Rootkit detection is a strenuous process and requires advanced security methods due to their sophisticated operation. A careful analysis of possible rootkit target locations and their exploitation techniques is necessary to design effective threat detection and mitigation mechanisms. This paper discusses the cyber kill chain of a rootkit which can simultaneously deploy itself at multiple locations in a microgrid in a coordinated and stealthy way in order to maximize the impact on power system operations. The rootkit leverages system measurements to hide its presence and its attack impact from the detection mechanisms.

Faster than real-time simulation: Methods, tools, and applications
XioRui Liu, Juan Ospina, Ioannis Zografopoulos, Alonzo Russel, and Charalambos Konstantinou
ACM
Real-time simulation enables the understanding of system operating conditions by evaluating simulation models of physical components running synchronized at the real-time wall clock. Leveraging the real-time measurements of comprehensive system models, faster than real-time (FTRT) simulation allows the evaluation of system architectures at speeds faster than real-time. FTRT simulation can assist in predicting the system's behavior efficiently, thus assisting the operation of system processes. Namely, the provided acceleration can be used for improving system scheduling, assessing system vulnerabilities, and predicting system disruptions in real-time systems. The acceleration of simulation times can be achieved by utilizing digital real-time simulators (RTS) and high-performance computing (HPC) architectures. FTRT simulation has been widely used, among others, for the operation, design, and investigation of power system events, building emergency management plans, wildfire prediction, etc. In this paper, we review the existing literature on FTRT simulation and its applications in different disciplines, with a particular focus on power systems. We present existing system modeling approaches, simulation tools and computing frameworks, and stress the importance of FTRT accuracy.

Security assessment and impact analysis of cyberattacks in integrated T&D power systems
Ioannis Zografopoulos, Charalambos Konstantinou, Nektarios Georgios Tsoutsos, Dan Zhu, and Robert Broadwater
ACM
In this paper, we examine the impact of cyberattacks in an integrated transmission and distribution (T&D) power grid model with distributed energy resource (DER) integration. We adopt the OCTAVE Allegro methodology to identify critical system assets, enumerate potential threats, analyze, and prioritize risks for threat scenarios. Based on the analysis, attack strategies and exploitation scenarios are identified which could lead to system compromise. Specifically, we investigate the impact of data integrity attacks in inverted-based solar PV controllers, control signal blocking attacks in protective switches and breakers, and coordinated monitoring and switching time-delay attacks.

Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies
Ioannis Zografopoulos, Juan Ospina, Xiaorui Liu, and Charalambos Konstantinou
Institute of Electrical and Electronics Engineers (IEEE)
Cyber-physical systems (CPS) are interconnected architectures that employ analog and digital components as well as communication and computational resources for their operation and interaction with the physical environment. CPS constitute the backbone of enterprise (e.g., smart cities), industrial (e.g., smart manufacturing), and critical infrastructure (e.g., energy systems). Thus, their vital importance, interoperability, and plurality of computing devices make them prominent targets for malicious attacks aiming to disrupt their operations. Attacks targeting cyber-physical energy systems (CPES), given their mission-critical nature within the power grid infrastructure, can lead to disastrous consequences. The security of CPES can be enhanced by leveraging testbed capabilities in order to replicate and understand power systems operating conditions, discover vulnerabilities, develop security countermeasures, and evaluate grid operation under fault-induced or maliciously constructed scenarios. Adequately modeling and reproducing the behavior of CPS could be a challenging task. In this paper, we provide a comprehensive overview of the CPS security landscape with an emphasis on CPES. Specifically, we demonstrate a threat modeling methodology to accurately represent the CPS elements, their interdependencies, as well as the possible attack entry points and system vulnerabilities. Leveraging the threat model formulation, we present a CPS framework designed to delineate the hardware, software, and modeling resources required to simulate the CPS and construct high-fidelity models that can be used to evaluate the system’s performance under adverse scenarios. The system performance is assessed using scenario-specific metrics, while risk assessment enables the system vulnerability prioritization factoring the impact on the system operation. The overarching framework for modeling, simulating, assessing, and mitigating attacks in a CPS is illustrated using four representative attack scenarios targeting CPES. The key objective of this paper is to demonstrate a step-by-step process that can be used to enact in-depth cybersecurity analyses, thus leading to more resilient and secure CPS.

EProfiler: High-Precision Power Monitoring System for IoT Devices Featuring Extreme Dynamic Range of Operation
Giannis Kazdaridis, Ioannis Zografopoulos, Nikos Sidiropoulos, Polychronis Symeonidis, and Thanasis Korakis
ACM

DEMO: Trustworthy Cyberphysical Energy Systems: Time-Delay Attacks in a Real-Time Co-Simulation Environment
Juan Ospina, Ioannis Zografopoulos, XiaoRui Liu, and Charalambos Konstantinou
ACM
In this work, we present the impact of time-delay attacks in cyberphysical energy systems. The evaluation is performed in a real-time co-simulation environment that captures the interdependency between the system's cyber and physical models.

Nano-things: Pushing sleep current consumption to the limits in IoT platforms
Giannis Kazdaridis, Nikos Sidiropoulos, Ioannis Zografopoulos, Polychronis Symeonidis, and Thanasis Korakis
ACM
In this work we illustrate a novel power management architecture towards eliminating the power draw of IoT platforms during inactive periods. Our principle suggests the employment of an off-chip Real-Time-Clock (RTC) configured to control the power supply of the under consideration mote, by enabling or disabling its power in a power-gating fashion. The selected RTC features an ultra-low power profile and it is the only module that remains powered during sleep, hence the overall mote's consumption is substantially diminished. Additionally, we introduce an alternative topology in which the host MCU remains powered in sleep state while the power-gating scheme is applied only in the rest of the peripherals of the IoT node, in an effort to exploit the MCUs benefits such as RAM retention and ultra-fast wake-ups. The proposed principle can be adopted by any IoT mote, in order to extend the life expectancy of battery-powered applications, by pushing sleep currents an order of magnitude lower. Moreover, we demonstrate the ICARUS mote, the first sensor that draws a sleep current of only 22 nA on a 3 V supply. Direct comparison of power draw in sleep state with state-of-the-art sensors illustrates improvements of roughly 98 % - 99.8 %, while we demonstrate that the life expectancy of the same motes can be prolonged from 2.7 years to 19 years under specific duty-cycles.

The ICARUS Mote: Employing Off-Chip RTC to Attain 22 nA Sleep Current in Duty-Cycled IoT Devices
Giannis Kazdaridis, Nikos Sidiropoulos, Ioannis Zografopoulos, Polychronis Symeonidis, and Thanasis Korakis
ACM
In this work we demonstrate the ICARUS mote, the first wireless sensor node that features the extremely-low sleep current of 22 nA. To achieve this, we employ an off-chip on-board Real-Time-Clock (RTC) circuit with an ultra-low power consumption profile. The RTC is configured to control the power supply of the under consideration mote, by enabling or disabling its power in a power-gating fashion, while it is the only module that remains powered during sleep, hence the overall mote’s consumption is substantially diminished. The proposed principle can be adopted by any IoT mote, in order to extend the life expectancy of battery-powered applications, by pushing sleep currents an order of magnitude lower.

Special Session: Harness the Power of DERs for Secure Communications in Electric Energy Systems
Ioannis Zografopoulos, Juan Ospina, and Charalambos Konstantinou
IEEE
Electric energy systems are undergoing significant changes to improve system reliability and accommodate increasing power demands. The penetration of distributed energy resources (DERs) including roof-top solar panels, energy storage, electric vehicles, etc., enables the on-site generation of economically dispatchable power curtailing operational costs. The effective control of DERs requires communication between utilities and DER system operators. The communication protocols employed for DER management and control lack sophisticated cybersecurity features and can compromise power systems secure operation if malicious control commands are issued to DERs. To overcome authentication-related protocol issues, we present a bolt-on security extension that can be implemented on Distributed Network Protocol v3 (DNP3). We port an authentication framework, DERauth, into DNP3, and utilize real-time measurements from a simulated DER battery energy storage system to enhance communication security. We evaluate our framework in a testbed setup using DNP3 master and outstation devices performing secure authentication by leveraging the entropy of DERs.

Survey of machine learning methods for detecting false data injection attacks in power systems
Ali Sayghe, Yaodan Hu, Ioannis Zografopoulos, Xiaorui Liu, R. Dutta, Yier Jin and Charalambos Konstantinou

Over the last decade, the number of cyber attacks targeting power systems and causing physical and economic damages has increased rapidly. Among them, false data injection attacks (FDIAs) are a class of cyber-attacks against power grid monitoring systems. Adversaries can successfully perform FDIAs to manipulate the power system state estimation (SE) by compromising sensors or modifying system data. SE is an essential process performed by the energy management system towards estimating unknown state variables based on system redundant measurements and network topology. SE routines include bad data detection algorithms to eliminate errors from the acquired measurements, e.g. in case of sensor failures. FDIAs can bypass BDD modules to inject malicious data vectors into a subset of measurements without being detected, and thus manipulate the results of the SE process. To overcome the limitations of traditional residual-based BDD approaches, data-driven solutions based on machine learning algorithms have been widely adopted for detecting malicious manipulation of sensor data due to their fast execution times and accurate results. This study provides a comprehensive review of the most up-to-date machine learning methods for detecting FDIAs against power system SE algorithms.

DERauth: A battery-based authentication scheme for distributed energy resources
Ioannis Zografopoulos and Charalambos Konstantinou
IEEE
Over the past decades, power systems have experienced drastic transformations in order to address the growth in energy demand, reduce carbon emissions, and enhance power quality and energy efficiency. This shift to the smart grid concept involves, among others, the utilization of distributed energy resources (DERs) such as rooftop solar panels and storage systems, contributing towards grid decentralization while improving control over power generation. In order to seamlessly integrate DERs into power systems, embedded devices are used to support the communication and control functions of DERs. As a result, vulnerabilities of such components can be ported to the industrial environment. Insecure control networks and protocols further exacerbate the problem. Towards reducing the attack surface, we present an authentication scheme for DERs, DERauth, which leverages the inherent entropy of the DER battery energy storage system (BESS) as a root-of-trust. The DER authentication is achieved using a challenge-reply mechanism that relies on the corresponding DER's BESS state-of-charge (SoC) and voltage measurements. A dynamically updating process ensures that the BESS state is up-to-date. We evaluate our proof-of-concept in a prototype development that uses lithium-ion (li-ion) batteries for the BESS. The robustness of our design is assessed against modeling attacks performed by neural networks.

Demo: Nano power draw in duty-cycled wireless sensor networks
Giannis Kazdaridis, Ioannis Zographopoulos, Nikos Sidiropoulos, Polychronis Symeonidis, and Thanasis Korakis
ACM
In this work we present a novel power management architecture for Wireless Sensor Network devices towards minimizing the power consumption when nodes remain in sleep state. Specifically, we propose the employment of an on-board timer circuit that consumes only few nano Amperes, along with a power switch that controls the power rail of the under consideration node. According to our principle, the node remains solely disconnected from power when in sleep state in an effort to minimize the quiescent draw, while the timer is responsible for reinforcing the node back in active mode when required. Our implementation achieves the minimization of power draw in sleep state down to 33 nA, while it can easily be integrated with any IoT platform.

RECENT SCHOLAR PUBLICATIONS

Event-triggered islanding in inverter-based grids
I Zografopoulos, C Konstantinou
Electric Power Systems Research 243, 111472 2025

Cyber-Physical Interdependence for Power System Operation and Control
I Zografopoulos, A Srivastava, C Konstantinou, J Zhao, AA Jahromi, ...
IEEE Transactions on Smart Grid 2025

Distribution system behind-the-meter ders: Estimation, uncertainty quantification, and control
A Srivastava, J Zhao, H Zhu, F Ding, S Lei, I Zografopoulos, R Haider, ...
IEEE Transactions on Power Systems 2024

Cyber-Physical Interdependence for Power System Operation and Control
AA Jahromi, A Srivastava, A Chawla, B Nguyen, B Tan, S Bu, C Li, ...
IEEE Power and Energy Society 2023

Distributed energy resources cybersecurity outlook: Vulnerabilities, attacks, impacts, and mitigations
I Zografopoulos, ND Hatziargyriou, C Konstantinou
IEEE Systems Journal 17 (4), 6695-6709 2023

Experimental impact analysis of cyberattacks in power systems using digital real-time testbeds
K Katuri, I Zografopoulos, HT Nguyen, C Konstantinou
2023 IEEE Belgrade PowerTech, 1-6 2023

A resource allocation scheme for energy demand management in 6G-enabled smart grid
S Islam, I Zografopoulos, MT Hossain, S Badsha, C Konstantinou
2023 IEEE Power & Energy Society Innovative Smart Grid Technologies 2023

Cybersecure and Resilient Power Systems with Distributed Energy Resources
I Zografopoulos
2023

Time series-based detection and impact analysis of firmware attacks in microgrids
I Zografopoulos, AP Kuruvila, K Basu, C Konstantinou
Energy Reports 8, 11221-11234 2022

Mitigation of cyberattacks through battery storage for stable microgrid operation
I Zografopoulos, P Karamichailidis, AT Procopiou, F Teng, ...
2022 IEEE International Conference on Communications, Control, and Computing 2022

Behind closed doors: Process-level rootkit attacks in cyber-physical microgrid systems
S Rath, I Zografopoulos, PP Vergara, VC Nikolaidis, C Konstantinou
2022 IEEE Power & Energy Society General Meeting (PESGM), 1-5 2022

Detection of malicious attacks in autonomous cyber-physical inverter-based microgrids
I Zografopoulos, C Konstantinou
IEEE Transactions on Industrial Informatics 18 (9), 5815-5826 2021

Hardware-assisted detection of firmware attacks in inverter-based cyberphysical microgrids
AP Kuruvila, I Zografopoulos, K Basu, C Konstantinou
International Journal of Electrical Power & Energy Systems 132, 107150 2021

Contactless technologies for smart cities: big data, IoT, and cloud infrastructures
A Manimuthu, V Dharshini, I Zografopoulos, MK Priyan, C Konstantinou
SN computer science 2 (4), 334 2021

Stealthy rootkit attacks on cyber-physical microgrids: Poster
S Rath, I Zografopoulos, C Konstantinou
Proceedings of the Twelfth ACM International Conference on Future Energy 2021

Faster than real-time simulation: Methods, tools, and applications
XR Liu, J Ospina, I Zografopoulos, A Russel, C Konstantinou
Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical 2021

Security assessment and impact analysis of cyberattacks in integrated T&D power systems
I Zografopoulos, C Konstantinou, NG Tsoutsos, D Zhu, R Broadwater
Proceedings of the 9th workshop on modeling and simulation of cyber-physical 2021

A Novel Architecture for Semi-Active Wake-Up Radios Attaining Sensitivity Beyond-70 dBm: Demo Abstract
G Kazdaridis, N Sidiropoulos, I Zografopoulos, T Korakis
Proceedings of the 20th International Conference on Information Processing 2021

Consumer, commercial, and industrial iot (in) security: Attack taxonomy and case studies
C Xenofontos, I Zografopoulos, C Konstantinou, A Jolfaei, MK Khan, ...
IEEE Internet of Things Journal 9 (1), 199-221 2021

EWake: A novel architecture for semi-active wake-up radios attaining ultra-high sensitivity at extremely-low consumption
G Kazdaridis, N Sidiropoulos, I Zografopoulos, T Korakis
arXiv preprint arXiv:2103.15969 2021

MOST CITED SCHOLAR PUBLICATIONS

Cyber-physical energy systems security: Threat modeling, risk assessment, resources, metrics, and case studies
I Zografopoulos, J Ospina, X Liu, C Konstantinou
IEEe Access 9, 29775-29818 2021
Citations: 271

Survey of machine learning methods for detecting false data injection attacks in power systems
A Sayghe, Y Hu, I Zografopoulos, XR Liu, RG Dutta, Y Jin, C Konstantinou
IET Smart Grid 2020
Citations: 154

Distributed energy resources cybersecurity outlook: Vulnerabilities, attacks, impacts, and mitigations
I Zografopoulos, ND Hatziargyriou, C Konstantinou
IEEE Systems Journal 17 (4), 6695-6709 2023
Citations: 90

Contactless technologies for smart cities: big data, IoT, and cloud infrastructures
A Manimuthu, V Dharshini, I Zografopoulos, MK Priyan, C Konstantinou
SN computer science 2 (4), 334 2021
Citations: 68

Detection of malicious attacks in autonomous cyber-physical inverter-based microgrids
I Zografopoulos, C Konstantinou
IEEE Transactions on Industrial Informatics 18 (9), 5815-5826 2021
Citations: 47

DERauth: A Battery-based Authentication Scheme for Distributed Energy Resources
I Zografopoulos, C Konstantinou
2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 560-567 2020
Citations: 24

Evaluation of lora performance in a city-wide testbed: Experimentation insights and findings
G Kazdaridis, S Keranidis, P Symeonidis, P Tzimotoudis, ...
Proceedings of the 13th International Workshop on Wireless Network Testbeds 2019
Citations: 16

Nano-things: Pushing sleep current consumption to the limits in IoT platforms
G Kazdaridis, N Sidiropoulos, I Zografopoulos, P Symeonidis, T Korakis
Proceedings of the 10th International Conference on the Internet of Things, 1-8 2020
Citations: 14

Time series-based detection and impact analysis of firmware attacks in microgrids
I Zografopoulos, AP Kuruvila, K Basu, C Konstantinou
Energy Reports 8, 11221-11234 2022
Citations: 13

In-situ power consumption meter for sensor networks supporting extreme dynamic range
G Kazdaridis, I Zographopoulos, P Symeonidis, P Skrimponis, T Korakis, ...
Proceedings of the 11th Workshop on Wireless Network Testbeds, Experimental 2017
Citations: 13

On the development of energy-efficient communications for marine monitoring deployments
G Kazdaridis, P Symeonidis, I Zographopoulos, T Korakis, K Klun, ...
2017 13th International Conference on Advanced Technologies, Systems and 2017
Citations: 11

Trustworthy cyberphysical energy systems: Time-delay attacks in a real-time co-simulation environment
J Ospina, I Zografopoulos, XR Liu, C Konstantinou
Proceedings of the 2020 Joint Workshop on CPS&IoT Security and Privacy, 69-69 2020
Citations: 10

Special session: Harness the power of ders for secure communications in electric energy systems
I Zografopoulos, J Ospina, C Konstantinou
2020 IEEE 38th International Conference on Computer Design (ICCD), 49-52 2020
Citations: 10