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Nima Karimian - IEEE Xplore Author Profile
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Nima Karimian

Publications
36
Citations
608
Publications by Year
20152025
Co-Authors:
Show All Co-Authors (68)
Image of author Nima Karimian

Nima Karimian

Affiliation

Lane Department of Computer Science and Electrical Engineering
Benjamin M. Statler College of Engineering and Mineral Resources
West Virginia University, Morgantown, WV, USA

Publication Topics

Biography

Nima Karimian is currently an Assistant Professor with the Department of Computer Engineering, San Jose State University, San Jose, CA, USA. His research is mainly focused on security and privacy of biometrics, Internet-of-Things and hardware security, and machine learning. He is the recipient of IAPR TC4 Best Paper Award in International Joint Conference on Biometrics (IJCB), 2017.Contact him at nima.karimian@sjsu.edu.(Based on document published on 15 June 2020).
Publications
36
Citations
608
Publications by Year
20152025
Co-Authors:
Show All Co-Authors (68)
Author's Published Works

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Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering

P. Banerjee;Anurag K. Srivastava;Donald A. Adjeroh;Ramana Reddy;Nima Karimian

IEEE Access
Year: 2025 | Volume: 13 | Journal Article |
Large Language Models (LLMs) like ChatGPT have become the most popular regenerative AI applications, used for obtaining responses for queries in different domains. The responses of ChatGPT are already becoming mainstream and are challenging conventional methods of learning. This article focuses on the application of ChatGPT for academic instructional purposes in the field of computer engineering a...Show More

Understanding ChatGPT: Impact Analysis and Path Forward for Teaching Computer Science and Engineering

P. Banerjee;Anurag K. Srivastava;Donald A. Adjeroh;Ramana Reddy;Nima Karimian

Year: 2025 | Volume: 13 | Journal Article |

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal

MohammadReza Hosseinzadehketilateh;Banafsheh Adami;Nima Karimian

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2024 | Conference Paper |
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constrained by challenges related to generalization and scalability, primarily due to using all subjects’ ECG in training without considering unseen subjects—a ...Show More

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal

MohammadReza Hosseinzadehketilateh;Banafsheh Adami;Nima Karimian

Year: 2024 | Conference Paper |

Face Liveness Detection Competition (LivDet-Face) - 2024

Lambert Igene;Afzal Hossain;Mohammad Zahir Uddin Chowdhury;Humaira Rezaie;Ayden Rollins;Jesse Dykes;Rahul Vijaykumar;Alain Komaty;Sébastien Marcel;Stephanie Schuckers;Juan E. Tapia;Carlos Aravena;Daniel Schulz;Banafsheh Adami;Nima Karimian;Diogo Nunes;João Marcos;Nuno Gonçalves;Lovro Sikošek;Borut Batagelj;Aleksandr Alenin;Alhasan Alkhaddour;Anton Pimenov;Artem Tregubov;Igor Avdonin;Maxim Kazantsev;Mikhail Pozigun;Vasiliy Pryadchenko;Nima Schei;David Pabon;Manuela Tiedemann

2024 IEEE International Joint Conference on Biometrics (IJCB)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Imagine a world where a copy of your face could trick the most advanced security systems. This isn’t science fiction; it’s a real challenge today. LivDet-Face is a competition that aims to advance the detection of attacks at the biometric sensor, known as Presentation Attack Detection (PAD). This international contest is a key benchmark in biometric security, offering an unbiased look at the lates...Show More

Face Liveness Detection Competition (LivDet-Face) - 2024

Lambert Igene;Afzal Hossain;Mohammad Zahir Uddin Chowdhury;Humaira Rezaie;Ayden Rollins;Jesse Dykes;Rahul Vijaykumar;Alain Komaty;Sébastien Marcel;Stephanie Schuckers;Juan E. Tapia;Carlos Aravena;Daniel Schulz;Banafsheh Adami;Nima Karimian;Diogo Nunes;João Marcos;Nuno Gonçalves;Lovro Sikošek;Borut Batagelj;Aleksandr Alenin;Alhasan Alkhaddour;Anton Pimenov;Artem Tregubov;Igor Avdonin;Maxim Kazantsev;Mikhail Pozigun;Vasiliy Pryadchenko;Nima Schei;David Pabon;Manuela Tiedemann

Year: 2024 | Conference Paper |

Contactless Fingerprint Biometric Anti-Spoofing: An Unsupervised Deep Learning Approach

Banafsheh Adami;MohammadReza Hosseinzadehketilateh;Nima Karimian

2024 IEEE International Joint Conference on Biometrics (IJCB)
Year: 2024 | Conference Paper |
Cited by: Papers (2)
Contactless fingerprint recognition offers a higher level of user comfort and addresses hygiene concerns more effectively. However, it is also more vulnerable to presentation attacks, such as photo-paper, paper printout, and various display attacks, making it more challenging to implement in biometric systems compared to contact-based modalities. Limited research has been conducted on presentation...Show More

Contactless Fingerprint Biometric Anti-Spoofing: An Unsupervised Deep Learning Approach

Banafsheh Adami;MohammadReza Hosseinzadehketilateh;Nima Karimian

Year: 2024 | Conference Paper |

Human-to-Device (H2D) Authentication Using Biometrics

MohammadReza Hosseinzadehketilateh;Sara Tehranipoor;Nima Karimian

2024 Silicon Valley Cybersecurity Conference (SVCC)
Year: 2024 | Conference Paper |
An increasing array of intelligent computing devices operate within vulnerable environments where they are susceptible to capture or physical assault. The data and intellectual property (IP) stored within these devices are often compassionate. This paper explores the potential advantages and challenges of integrating biometrics into electronic devices. By combining cutting-edge biometrics, such as...Show More

Human-to-Device (H2D) Authentication Using Biometrics

MohammadReza Hosseinzadehketilateh;Sara Tehranipoor;Nima Karimian

Year: 2024 | Conference Paper |

Combating Deepfakes: A Novel Hybrid Hardware-Software Approach

Kamrul Hasan;Nima Karimian;Sara Tehranipoor

2024 Silicon Valley Cybersecurity Conference (SVCC)
Year: 2024 | Conference Paper |
In the era of Artificial Intelligence, Deepfake technology has become one of the major threats to privacy, creativity, and authenticity. Deepfakes initially gained attention in the context of manipulated adult content. However, they have extended their influence across various domains, involving the manipulation of texts, audios, videos, images, political and creative contents. With growing concer...Show More

Combating Deepfakes: A Novel Hybrid Hardware-Software Approach

Kamrul Hasan;Nima Karimian;Sara Tehranipoor

Year: 2024 | Conference Paper |

NAND Flash-Based Digital Fingerprinting for Robust and Secure Hardware Authentication

Kamrul Hasan;Sara Tehranipoor;Nima Karimian;Surbhi Vasudeva

2024 25th International Symposium on Quality Electronic Design (ISQED)
Year: 2024 | Conference Paper |
In today’s world, embedded systems and microcontroller-based modules have become increasingly integrated into our daily lives. However, the security of these embedded devices and the assurance of hardware authenticity have raised concerns within the expanding realm of the Internet of Things (IoT). In this study, we established an experimental environment to observe the disturbance of SLC flash mem...Show More

NAND Flash-Based Digital Fingerprinting for Robust and Secure Hardware Authentication

Kamrul Hasan;Sara Tehranipoor;Nima Karimian;Surbhi Vasudeva

Year: 2024 | Conference Paper |

A Universal Anti-Spoofing Approach for Contactless Fingerprint Biometric Systems

Banafsheh Adami;Sara Tehranipoor;Nasser Nasrabadi;Nima Karimian

2023 IEEE International Joint Conference on Biometrics (IJCB)
Year: 2023 | Conference Paper |
Cited by: Papers (7)
With the increasing integration of smartphones into our daily lives, fingerphotos are becoming a potential contactless authentication method. While it offers convenience, it is also more vulnerable to spoofing using various presentation attack instruments (PAI). The contactless fingerprint is an emerging biometric authentication but has not yet been heavily investigated for anti-spoofing. While ex...Show More

A Universal Anti-Spoofing Approach for Contactless Fingerprint Biometric Systems

Banafsheh Adami;Sara Tehranipoor;Nasser Nasrabadi;Nima Karimian

Year: 2023 | Conference Paper |

Breaking AES-128: Machine Learning-Based SCA Under Different Scenarios and Devices

Sara Tehranipoor;Nima Karimian;Jack Edmonds

2023 IEEE International Conference on Cyber Security and Resilience (CSR)
Year: 2023 | Conference Paper |
Machine learning-based side-channel attacks (MLSCAs) have demonstrated the capability to extract secret keys from AES by learning the correlation between leakages from power traces or timing of AES execution. Previous work has focused on unmasked AES, the captured power traces for profiling and testing have been collected from the same device, and they are primarily implemented on microcontrollers...Show More

Breaking AES-128: Machine Learning-Based SCA Under Different Scenarios and Devices

Sara Tehranipoor;Nima Karimian;Jack Edmonds

Year: 2023 | Conference Paper |

Never Lose Your ECG: A Novel Key Generation and Authentication Scheme for Implantable Medical Devices

Nima Karimian;Gokay Saldamli;Younghee Park;Victor Lui

IEEE Access
Year: 2023 | Volume: 11 | Journal Article |
Cited by: Papers (2)
Implantable medical devices, such as pacemakers, cardiac defibrillators, and insulin pumps, play a crucial role in monitoring patients’ vital signs within healthcare systems. However, these networked devices are susceptible to external attacks and breaches of trust, hindering the potential innovation and social benefits of eHealth services. To address these concerns, we propose a novel ECG-based k...Show More

Never Lose Your ECG: A Novel Key Generation and Authentication Scheme for Implantable Medical Devices

Nima Karimian;Gokay Saldamli;Younghee Park;Victor Lui

Year: 2023 | Volume: 11 | Journal Article |

Trustworthy of Implantable Medical Devices using ECG Biometric

Nima Karimian;Sara Tehranipoor;Thomas Lyp

2023 Silicon Valley Cybersecurity Conference (SVCC)
Year: 2023 | Conference Paper |
Implantable medical devices (IMD) such as pace-makers, and cardiac defibrillators are becoming increasingly interconnected to networks for remote patient monitoring. However, networked devices are vulnerable to external attacks that could allow adversaries to gain unauthorized access to devices/data and break patient privacy. To design a lightweight computational trustworthy of IMD, we propose nov...Show More

Trustworthy of Implantable Medical Devices using ECG Biometric

Nima Karimian;Sara Tehranipoor;Thomas Lyp

Year: 2023 | Conference Paper |

Leveraging Timing Side-Channel Information and Machine Learning for IoT Security

Kratika Sahu;Rasika Kshirsagar;Surbhi Vasudeva;Taghreed Alzahrani;Nima Karimian

2021 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
In the recent era, adoption of IoT technology can be seen in nearly every other field. However, with its fast growth rate, the IoT brings several advanced security challenges. To alleviate these problems, we propose an inventive framework that could be introduced into the IoT package to gather side-channel information (execution timing) for inconsistency and attack location. We observed that when ...Show More

Leveraging Timing Side-Channel Information and Machine Learning for IoT Security

Kratika Sahu;Rasika Kshirsagar;Surbhi Vasudeva;Taghreed Alzahrani;Nima Karimian

Year: 2021 | Conference Paper |

ECG Biometric Spoofing Using Adversarial Machine Learning

Amit Garg;Nima Karimian

2021 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
As the Covid-19 pandemic becomes a nationwide problem, physical contact is no longer acceptable. Therefore, biometric technology can be used for practicing social distancing to prevent the spread of the virus. However, face and fingerprint are vulnerable to presentation attacks. Hence alternative modalities such as ECG based biometric become popular. In this paper, we develop a novel presentation ...Show More

ECG Biometric Spoofing Using Adversarial Machine Learning

Amit Garg;Nima Karimian

Year: 2021 | Conference Paper |

LISH: A New Random Number Generator using ECG Noises

Thomas Lyp;Nima Karimian;Fatemeh Tehranipoor

2021 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
In this paper, we propose a novel method, "Lift and Shift" (LISH), where it can generate a unique true random number based on the patient's unique ECG noise signal. The advantage of the proposed LISH method is that the ECG signal noise is nearly impossible to replicate or measure without the user's consent, and it is a readily available signal in most modern health sensors. To validate LISH, multi...Show More

LISH: A New Random Number Generator using ECG Noises

Thomas Lyp;Nima Karimian;Fatemeh Tehranipoor

Year: 2021 | Conference Paper |

ECG biometric using 2D Deep Convolutional Neural Network

Siddartha Thentu;Renato Cordeiro;Youngee Park;Nima Karimian

2021 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
We propose a novel multi-scale continuous wavelet transform feature method to accurately obtain micro-texture and multi-scale ECG characteristics and demonstrate how it could benefit from the state-of-the-art deep convolutional neural network techniques. In other words, we performed transfer learning with popular CNN architectures such as InceptionV3, VGG16, VGG19, Inception ResNetV2, MobileNetV2,...Show More

ECG biometric using 2D Deep Convolutional Neural Network

Siddartha Thentu;Renato Cordeiro;Youngee Park;Nima Karimian

Year: 2021 | Conference Paper |

Leveraging Deep CNN and Transfer Learning for Side-Channel Attack

Amit Garg;Nima Karimian

2021 22nd International Symposium on Quality Electronic Design (ISQED)
Year: 2021 | Conference Paper |
Cited by: Papers (9)
The adoption of deep neural networks for profiled side-channel attacks provides powerful options for leakage detection and key retrieval of secure products. Although deep learning is being widely adopted for computer vision, less research has been prominent in template-based profiling power SCA attacks. In addition, most of the existing works fall into a one-dimensional (1-D) CNN technique rather ...Show More

Leveraging Deep CNN and Transfer Learning for Side-Channel Attack

Amit Garg;Nima Karimian

Year: 2021 | Conference Paper |

A New Foe in GPUs: Power Side-Channel Attacks on Neural Network

Hyeran Jeon;Nima Karimian;Tamara Lehman

2021 22nd International Symposium on Quality Electronic Design (ISQED)
Year: 2021 | Conference Paper |
GPUs have been increasingly adopted as hardware accelerators for neural networks (NN). Prior studies show that the unique execution model and many DC-DC units on GPUs make it uneasy to reverse engineer detailed information of encryption algorithms through power side-channel attacks. However, we observe that a few core parameters of NN can be acquired through power profiling when victim and attacke...Show More

A New Foe in GPUs: Power Side-Channel Attacks on Neural Network

Hyeran Jeon;Nima Karimian;Tamara Lehman

Year: 2021 | Conference Paper |

DRAM-Based Authentication Using Deep Convolutional Neural Networks

Michael Yue;Nima Karimian;Wei Yan;Nikolaos Athanasios Anagnostopoulos;Fatemeh Tehranipoor

IEEE Consumer Electronics Magazine
Year: 2021 | Volume: 10, Issue: 4 | Magazine Article |
Cited by: Papers (7)
Authentication is the act of proving that an integrated circuit (IC) is not counterfeit. One application of a physical unclonable function (PUF) circuit is to authenticate the identity of the chip using raw bits of the memory. However, several previous works present machine learning-based modeling attacks on PUFs. To alleviate this issue, we propose a novel authentication scheme involving unique D...Show More

DRAM-Based Authentication Using Deep Convolutional Neural Networks

Michael Yue;Nima Karimian;Wei Yan;Nikolaos Athanasios Anagnostopoulos;Fatemeh Tehranipoor

Year: 2021 | Volume: 10, Issue: 4 | Magazine Article |

ECG-Based Authentication Using Timing-Aware Domain-Specific Architecture

Renato Cordeiro;Dhruv Gajaria;Ankur Limaye;Tosiron Adegbija;Nima Karimian;Fatemeh Tehranipoor

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Year: 2020 | Volume: 39, Issue: 11 | Journal Article |
Cited by: Papers (18)
Electrocardiogram (ECG) biometric authentication (EBA) is a promising approach for human identification, particularly in consumer devices, due to the individualized, ubiquitous, and easily identifiable nature of ECG signals. Thus, computing architectures for EBA must be accurate, fast, energy efficient, and secure. In this article, first, we implement an EBA algorithm to achieve 100% accuracy in u...Show More

ECG-Based Authentication Using Timing-Aware Domain-Specific Architecture

Renato Cordeiro;Dhruv Gajaria;Ankur Limaye;Tosiron Adegbija;Nima Karimian;Fatemeh Tehranipoor

Year: 2020 | Volume: 39, Issue: 11 | Journal Article |

ECG Biometric Authentication: A Comparative Analysis

Mohit Ingale;Renato Cordeiro;Siddartha Thentu;Younghee Park;Nima Karimian

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (78)
Robust authentication and identification methods become an indispensable urgent task to protect the integrity of the devices and the sensitive data. Passwords have provided access control and authentication, but have shown their inherent vulnerabilities. The speed and convenience factor are what makes biometrics the ideal authentication solution as they could have a low probability of circumventio...Show More

ECG Biometric Authentication: A Comparative Analysis

Mohit Ingale;Renato Cordeiro;Siddartha Thentu;Younghee Park;Nima Karimian

Year: 2020 | Volume: 8 | Journal Article |

ECG Biometric: Spoofing and Countermeasures

Nima Karimian;Damon Woodard;Domenic Forte

IEEE Transactions on Biometrics, Behavior, and Identity Science
Year: 2020 | Volume: 2, Issue: 3 | Journal Article |
Cited by: Papers (28)
The increased need for access control has motivated a widespread deployment of biometric systems in the last few years. However, recent works indicate that some modalities are fragile and more susceptible to malicious presentation attacks. This has in turn led to the exploration of alternative modalities such as electrocardiogram (ECG) due to its individualized and ubiquitous nature, difficulty in...Show More

ECG Biometric: Spoofing and Countermeasures

Nima Karimian;Damon Woodard;Domenic Forte

Year: 2020 | Volume: 2, Issue: 3 | Journal Article |

Unlock Your Heart: Next Generation Biometric in Resource-Constrained Healthcare Systems and IoT

Nima Karimian;Mark Tehranipoor;Damon Woodard;Domenic Forte

IEEE Access
Year: 2019 | Volume: 7 | Journal Article |
Cited by: Papers (30)
With the emergence of the Internet-of-Things, there is a growing need for access control and data protection on low-power, pervasive devices. Key-based biometric cryptosystems are promising for IoT due to its convenient nature and lower susceptibility to attacks. However, the costs associated with biometric processing and template protection are nontrivial for smart cards, and so forth. In this pa...Show More

Unlock Your Heart: Next Generation Biometric in Resource-Constrained Healthcare Systems and IoT

Nima Karimian;Mark Tehranipoor;Damon Woodard;Domenic Forte

Year: 2019 | Volume: 7 | Journal Article |

Low-cost authentication paradigm for consumer electronics within the internet of wearable fitness tracking applications

Fatemeh Tehranipoor;Nima Karimian;Paul A. Wortman;John A. Chandy

2018 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2018 | Conference Paper |
Cited by: Papers (15)
Nowadays, the consumer electronic (CE) market has grown to include smart devices for the Internet of Things. With increased adoption of these smart IoT devices, there is a high demand for safe and secure authentication for the purpose of maintaining effective access control. This paper addresses the concerns of authenticating consumer electronic devices using low-cost methods for implementation wi...Show More

Low-cost authentication paradigm for consumer electronics within the internet of wearable fitness tracking applications

Fatemeh Tehranipoor;Nima Karimian;Paul A. Wortman;John A. Chandy

Year: 2018 | Conference Paper |

DVFT: A Lightweight Solution for Power-Supply Noise-Based TRNG Using Dynamic Voltage Feedback Tuning System

Fatemeh Tehranipoor;Paul Wortman;Nima Karimian;Wei Yan;John A. Chandy

IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year: 2018 | Volume: 26, Issue: 6 | Journal Article |
Cited by: Papers (19)
True random number generators (TRNGs) are central to many computing applications, particularly in security domains such as cryptography. In this paper, we consider the design and implementation of a low-cost and lightweight TRNG. In the interest of being thorough, we examined six different power supplies in order to verify the noncyclostationary behavior of the voltage sources. Our novel TRNG mode...Show More

DVFT: A Lightweight Solution for Power-Supply Noise-Based TRNG Using Dynamic Voltage Feedback Tuning System

Fatemeh Tehranipoor;Paul Wortman;Nima Karimian;Wei Yan;John A. Chandy

Year: 2018 | Volume: 26, Issue: 6 | Journal Article |

On the vulnerability of ECG verification to online presentation attacks

Nima Karimian;Damon L. Woodard;Domenic Forte

2017 IEEE International Joint Conference on Biometrics (IJCB)
Year: 2017 | Conference Paper |
Cited by: Papers (19)
Electrocardiogram (ECG) has long been regarded as a biometric modality which is impractical to copy, clone, or spoof. However, it was recently shown that an ECG signal can be replayed from arbitrary waveform generators, computer sound cards, or off-the-shelf audio players. In this paper, we develop a novel presentation attack where a short template of the victim's ECG is captured by an attacker an...Show More

On the vulnerability of ECG verification to online presentation attacks

Nima Karimian;Damon L. Woodard;Domenic Forte

Year: 2017 | Conference Paper |

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