Mahmoud Daneshmand, Ph.D

Mahmoud Daneshmand, Ph.D

Stevens Institute of Technology

H-index: 32

North America-United States

About Mahmoud Daneshmand, Ph.D

Mahmoud Daneshmand, Ph.D, With an exceptional h-index of 32 and a recent h-index of 28 (since 2020), a distinguished researcher at Stevens Institute of Technology, specializes in the field of Big Data Analytics & ML, Internet of Things (IoT), Data Science, Streaming Data Analytics, AI & Deep Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

In Memory of Dr. David Belanger:(12/8/1944–11/18/2022)

An edge-AI enabled autonomous connected ambulance route resource recommendation protocol (ACA-R3) for eHealth in smart cities

Chatbots to chatgpt in a cybersecurity space: Evolution, vulnerabilities, attacks, challenges, and future recommendations

A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges

A three factor based authentication scheme of 5G wireless sensor networks for IoT system

A new technology perspective of the Metaverse: Its essence, framework and challenges

Guest Editorial Special Issue on Empowering the Future Generation Systems: Opportunities by the Convergence of Cloud, Edge, AI, and IoT

Guest Editorial Special Issue on Smart Cities and Systems: Theories, Tools, Trends, Applications, Challenges, and Opportunities

Mahmoud Daneshmand, Ph.D Information

University

Stevens Institute of Technology

Position

Industry Professor Former Assistant Chief Scientist AT&T Bell

Citations(all)

5485

Citations(since 2020)

3710

Cited By

2586

hIndex(all)

32

hIndex(since 2020)

28

i10Index(all)

71

i10Index(since 2020)

52

Email

University Profile Page

Stevens Institute of Technology

Mahmoud Daneshmand, Ph.D Skills & Research Interests

Big Data Analytics & ML

Internet of Things (IoT)

Data Science

Streaming Data Analytics

AI & Deep Learning

Top articles of Mahmoud Daneshmand, Ph.D

In Memory of Dr. David Belanger:(12/8/1944–11/18/2022)

Authors

George Avirappattu,Mahmoud Daneshmand,Matthew Hale,Margaret Brennan-Tonetta,Jim Samuel,Rashmi Jain

Journal

Journal of Big Data and Artificial Intelligence

Published Date

2024/1/9

As Big Data emerged as a significant factor in the industry, David was called upon to lead the IEEE’s “Big Data Initiative”—a worldwide effort that included defining data strategy and data standards. He also led the IEEE’s DataPort project, which offers 2,500 datasets and has over 2.5 million users.In 2012, David joined Stevens as Senior Research Fellow/Senior Lecturer. As a BIA faculty member, he developed several courses in the Big Data concentration and certificate programs. David was a superb teacher, and he touched the lives of hundreds of students who looked to him as a source of inspiration throughout their careers. He played a leading role in the BIA Industry Advisory Board, where his presence attracted leading industry experts and animated discussions of trends and issues of importance to the program. David had a positive impact on all of us. He was an inspiring, innovative thinker, role model, and …

An edge-AI enabled autonomous connected ambulance route resource recommendation protocol (ACA-R3) for eHealth in smart cities

Authors

Syed Thouheed Ahmed,Syed Muzamil Basha,Manikandan Ramachandran,Mahmoud Daneshmand,Amir H Gandomi

Journal

IEEE Internet of Things Journal

Published Date

2023/2/7

The autonomous connected ambulance (ACA) has been an unprecedented necessity in the demand–supply management sector of the healthcare sector. However, the traditional prototypes designed for such an unmanned vehicle do not match the demands of the advanced communication technologies incorporated in today’s sophisticated distributed networks. As a result, in the current era of edge computing strengthened by many AI-enabled algorithms, there is an urgent need to design a route resource recommendation (R3) protocol for ACA under Edge-AI. Designing such a protocol requires addressing the major challenges to optimize the routes for ACA and, thereby, enhance the services of emergency eHealth centers through a governing telehealth monitoring administrator. Therefore, in this article, a dedicated and novel ACA-R3 protocol is proposed to address the issues of connectivity and resource …

Chatbots to chatgpt in a cybersecurity space: Evolution, vulnerabilities, attacks, challenges, and future recommendations

Authors

Attia Qammar,Hongmei Wang,Jianguo Ding,Abdenacer Naouri,Mahmoud Daneshmand,Huansheng Ning

Journal

arXiv preprint arXiv:2306.09255

Published Date

2023/5/29

Chatbots shifted from rule-based to artificial intelligence techniques and gained traction in medicine, shopping, customer services, food delivery, education, and research. OpenAI developed ChatGPT blizzard on the Internet as it crossed one million users within five days of its launch. However, with the enhanced popularity, chatbots experienced cybersecurity threats and vulnerabilities. This paper discussed the relevant literature, reports, and explanatory incident attacks generated against chatbots. Our initial point is to explore the timeline of chatbots from ELIZA (an early natural language processing computer program) to GPT-4 and provide the working mechanism of ChatGPT. Subsequently, we explored the cybersecurity attacks and vulnerabilities in chatbots. Besides, we investigated the ChatGPT, specifically in the context of creating the malware code, phishing emails, undetectable zero-day attacks, and generation of macros and LOLBINs. Furthermore, the history of cyberattacks and vulnerabilities exploited by cybercriminals are discussed, particularly considering the risk and vulnerabilities in ChatGPT. Addressing these threats and vulnerabilities requires specific strategies and measures to reduce the harmful consequences. Therefore, the future directions to address the challenges were presented.

A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges

Authors

Huansheng Ning,Hang Wang,Yujia Lin,Wenxi Wang,Sahraoui Dhelim,Fadi Farha,Jianguo Ding,Mahmoud Daneshmand

Published Date

2023/5/22

In recent years, the concept of the Metaverse has attracted considerable attention. This article provides a comprehensive overview of the Metaverse. First, the development status of the Metaverse is presented. We summarize the policies of various countries, companies, and organizations relevant to the Metaverse, as well as statistics on the number of Metaverse-related publications. Characteristics of the Metaverse are identified: 1) multitechnology convergence; 2) sociality; and 3) hyper-spatio-temporality. For the multitechnology convergence of the Metaverse, we divide the technological framework of the Metaverse into five dimensions. For the sociality of the Metaverse, we focus on the Metaverse as a virtual social world. Regarding the characteristic of hyper-spatio-temporality, we introduce the Metaverse as an open, immersive, and interactive 3-D virtual world which can break through the constraints of time and …

A three factor based authentication scheme of 5G wireless sensor networks for IoT system

Authors

Shreeya Swagatika Sahoo,Sujata Mohanty,Kshira Sagar Sahoo,Mahmoud Daneshmand,Amir H Gandomi

Journal

IEEE internet of things journal

Published Date

2023/5/1

Internet of Things (IoT) is an expanding technology that facilitate physical devices to interconnect each other over a public channel. Moreover, the security of the next-generation wireless mobile communication technology, namely, 5G with IoT, has been a field of much interest among researchers in the last several years. Previously, Sharif et al. have suggested an IoT-based lightweight three-party authentication scheme proclaiming a secured scheme against different threats. However, it was found that the scheme could not achieve user anonymity and guarantee session key security. Additionally, the scheme fails to provide proper authentication in the login phase, and it s unable to update a new password in the password change phase. Thus, we propose an improved three-factor-based data transmission authentication scheme (TDTAS) to address the weaknesses. The formal security analysis has been proved …

A new technology perspective of the Metaverse: Its essence, framework and challenges

Authors

Feifei Shi,Huansheng Ning,Xiaohong Zhang,Rongyang Li,Qiaohui Tian,Shiming Zhang,Yuanyuan Zheng,Yudong Guo,Mahmoud Daneshmand

Journal

Digital Communications and Networks

Published Date

2023/3/3

The Metaverse depicts a parallel digitalized world where virtuality and reality are fused. It has economic and social systems like those in the real world and provides intelligent services and applications. In this paper, we introduce the Metaverse from a new technology perspective, including its essence, corresponding technical framework, and potential technical challenges. Specifically, we analyze the essence of the Metaverse from its etymology and point out breakthroughs promising to be made in time, space, and contents of the Metaverse by citing Maslow's Hierarchy of Needs. Subsequently, we conclude four pillars of the Metaverse, named ubiquitous connections, space convergence, virtuality and reality interaction, and human-centered communication, and establish a corresponding technical framework. Additionally, we envision open issues and challenges of the Metaverse in the technical aspect. The work …

Guest Editorial Special Issue on Empowering the Future Generation Systems: Opportunities by the Convergence of Cloud, Edge, AI, and IoT

Authors

Farshad Firouzi,Mahmoud Daneshmand,Jaeseung Song,Kunal Mankodiya

Journal

IEEE Internet of Things Journal

Published Date

2023/2/20

The future generation of the Internet of Things (IoT) systems is characterized by the fusion of technologies—from edge–fog–cloud computing to artificial intelligence (AI) and blockchain—closing the gap between the physical and digital worlds [A1]. Although these technologies have been developed separately over time, the synergy among them has taken a giant leap. We are witnessing a fast-paced convergence of these technologies resulting in a fundamental paradigm shift unlocking vast benefits and opportunities across vertical markets. However, there are still several barriers, such as a lack of consensus toward any reference models or best practices, hindering the full fusion of these technologies [A1]. To tackle these challenges and facilitate this promising transformation, this special issue was organized to provide a holistic multidisciplinary reference for solutions, architectures, protocols, services, and …

Guest Editorial Special Issue on Smart Cities and Systems: Theories, Tools, Trends, Applications, Challenges, and Opportunities

Authors

Amrit Mukherjee,Mahmoud Daneshmand,Kathy Grise,Amir H Gandomi

Published Date

2023/10/19

This comprehensive abstract of the special issue presents an extensive array of collections of research studies that focus on the integration of state-of-the-art technologies and methodologies to advance healthcare services in smart cities through Internet of Things (IoT) applications. The studies explore innovative solutions across multiple aspects of healthcare, including privacy preservation, telemedicine, smart healthcare systems, security, abnormality detection, functional assessment, feature selection, health monitoring, diagnostics, medical vehicle routing, behavioral patterns discovery, federated learning, and personalized healthcare.

Guest Editorial Special Issue on AI-Driven IoT Data Monetization: A Transition From Value Islands to Value Ecosystems

Authors

Farshad Firouzi,Bahar Farahani,Mahmoud Daneshmand,Cesare Pautasso

Journal

IEEE Internet of Things Journal

Published Date

2022/4/6

As The trajectory of the Internet of Things (IoT) is moving at a rapid pace, most companies and organizations are awash and drowning in massive amounts of data. Determining how to profit from data deluge and unlock its value can give companies an edge in the market because data have the potential to add tremendous value to many aspects of a business [A1]. The market has already seen a level of monetization across vertical domains e.g., in the form of layering connected devices with a variety of Insights-as-a- Service options. Out of this arena, the data economy concept has been evolving, characterized by correctly monetizing data rather than simply hoarding it, which will provide a significant advantage in a competitive digital environment [A1]. The recent advent of technological advances in the fields of Big Data, Analytics, and Artificial Intelligence (AI) has opened new avenues of competition, where IoT data …

Artificial Intelligence And Machine Learning

Authors

Niklas Kühl,Max Schemmer,Marc Goutier,Gerhard Satzger

Journal

Electronic Markets

Published Date

2022/12

Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia and industry—sometimes as synonyms, sometimes with different meanings. With this work, we try to clarify the relationship between these concepts. We review the relevant literature and develop a conceptual framework to specify the role of machine learning in building (artificial) intelligent agents. Additionally, we propose a consistent typology for AI-based information systems. We contribute to a deeper understanding of the nature of both concepts and to more terminological clarity and guidance—as a starting point for interdisciplinary discussions and future research.

How matching theory enables multi-access edge computing adaptive task scheduling in iiot

Authors

Jiancheng Chi,Chao Xu,Tie Qiu,Di Jin,Zhaolong Ning,Mahmoud Daneshmand

Journal

IEEE Network

Published Date

2022/8/16

Fifth-generation mobile communication technology (5G) is a powerful driving force for the Industrial Internet of Things (IIoT). In the 5G-based IIoT, multi-access edge computing (MEC) can move traffic and service computing from the centralized cloud to the edge networks, thus, effectively improving the real-time performance of task processing. In this context, it is crucial to assign real-time tasks generated by numerous edge devices to MEC servers. Existing schemes usually schedule tasks in batches within time slots and ignore the situations where edge tasks arrive with time-varying density. However, the problem is that these schemes can lead to extra waiting delay in the slots with sparse tasks, thus, resulting in additional latency in task processing. To solve this problem, we propose a task scheduling scheme based on two-stage hybrid matching. The proposed scheme measures the time-varying density of tasks and …

Communication Technologies for Edge Learning and Inference: A Novel Framework, Open Issues, and Perspectives

Authors

Khan Muhammad,Javier Del Ser,Naercio Magaia,Ramon Fonseca,Tanveer Hussain,Amir H Gandomi,Mahmoud Daneshmand,Victor Hugo C de Albuquerque

Journal

IEEE Network

Published Date

2022/12/26

With the continuous advancement of smart devices and their demand for data, the complex computation that was previously exclusive to the cloud server is now moving toward the edge of the network. For numerous reasons (e.g., applications demanding low latencies and data privacy), data-based computation has been brought closer to the originating source, forging the edge computing paradigm. Together with machine learning, edge computing has become a powerful local decision-making tool, fostering the advent of edge learning. However, the latter has become delay-sensitive and resource-thirsty in terms of hardware and networking. New methods have been developed to solve or minimize these issues, as proposed in this study. We first investigated representative communication methods for edge learning and inference (ELI), focusing on data compression, latency, and resource management. Next, we …

Fusion of IoT, AI, edge–fog–cloud, and blockchain: Challenges, solutions, and a case study in healthcare and medicine

Authors

Farshad Firouzi,Shiyi Jiang,Krishnendu Chakrabarty,Bahar Farahani,Mahmoud Daneshmand,Jaeseung Song,Kunal Mankodiya

Journal

IEEE Internet of Things Journal

Published Date

2022/7/18

The digital transformation is characterized by the convergence of technologies—from the Internet of Things (IoT) to edge–fog–cloud computing, artificial intelligence (AI), and Blockchain—in multiple dimensions, blurring the lines between the physical and digital worlds. Although these innovations have evolved independently over time, they are increasingly becoming more intertwined, driving the development of new business models. With more adaptation, embracement, and development, we are witnessing a steady convergence and fusion of these technologies resulting in an unprecedented paradigm shift that is expected to disrupt and reshape the next-generation systems in vertical domains in a way that the capabilities of the technologies are aligned in the best possible way to complement each other. Despite the fact that the convergence of the four technologies can potentially tackle the main shortcomings of …

Human health activity intelligence based on mmwave sensing and attention learning

Authors

Yichen Gao,Noah Ziems,Shaoen Wu,Honggang Wang,Mahmoud Daneshmand

Published Date

2022/12/4

Human daily activity monitoring has its particular significance in smart health. Human activity recognition based on mmWave has drawn enormous research efforts and achieved significant progress. Most of these solutions, however, work on data that has been manually segmented for each piece to contain only a single activity, which is impractical in reality where the sensor continuously generates data containing a series of activities. To address this challenge, this paper proposes a multi-head attention model that can detect the transition from one activity to another in a stream of mmWave sensor data of various human activities by analyzing the inner correlation of mmWave radar data fragments with a sliding window mechanism. Furthermore, the model then recognizes the new activity type in the data once it detects an activity transition. The solution has been extensively evaluated with a sparse point cloud dataset …

SocialNet of Things: a ubiquitous relationship network inspired by social space

Authors

Huansheng Ning,Wenxi Wang,Fadi Farha,Jinsheng Xie,Mahmoud Daneshmand

Journal

IEEE Network

Published Date

2022/7/13

The things existing in cyberspace, physical space, social space, and thinking space (CPSTs) are connected through relationships and interactions. The SocialNet, a ubiquitous network containing these relationships, is getting complex as a result of the interaction between social space and other spaces. Social space plays an important role in promoting the connection and convergence of the other three spaces. While the Internet of Things is described from the cyber view, this article puts forward the concept of SocialNet of Things (SoT) from the social view. The evolution of SoT is determined by the social attributes of things and the changes of SocialNet expounded from the perspectives of philosophy, science, and technology. The case of fighting against the COVID-19 pandemic is explored to explain and support the applicability of SoT. Finally, this article discusses the challenges facing SoT and its future …

Cyberology: Cyber–Physical–Social-Thinking Spaces-Based Discipline and Interdiscipline Hierarchy for Metaverse (General Cyberspace)

Authors

Huansheng Ning,Yujia Lin,Wenxi Wang,Hang Wang,Feifei Shi,Xiaohong Zhang,Mahmoud Daneshmand

Journal

IEEE Internet of Things Journal

Published Date

2022/10/28

It is well known that the metaverse, also named general cyberspace (GC), is virtual-real fusion spaces, consisting of a virtual space, namely, cyberspace and virtual-real spaces, namely, cyber-enabled physical, social, and thinking (cyber-enabled) spaces. This article discusses the open issues of the metaverse in terms of science and technology and proposes a new discipline and interdiscipline hierarchy for the metaverse (GC), namely, cyberology first. Then, it explores various relevant standards of discipline classification and a discipline and interdiscipline hierarchy based on physical, social, and thinking spaces, and investigates the cyberspace and cyber-enabled spaces. On the basis of the above research, this article enriches the contents of cyberology in two terms: 1) the disciplines in cyberspace and 2) the interdisciplines in cyber-enabled spaces. Finally, this article gives predictions of cyberology on the future …

Blockchain Security using Merkle hash zero correlation distinguisher for the IoT in Smart Cities

Authors

Rizwan Patan,Ramachandran Manikandan,Ramalingam Parameshwaran,Sivanesan Perumal,Mahmoud Daneshmand,Amir H Gandomi

Journal

IEEE Internet of Things Journal

Published Date

2022/4/29

Internet of Things (IoT) data is one of the most important assets in business models for offering various ubiquitous and brilliant services. The IoT is provided with the advantage of susceptibility that cybercriminals and other malicious users. Even though smart cities are intended to extend productivity and efficiency, residents and authorities face risks when they avoid cybersecurity. The conventional blockchain methods were introduced to ensure the secure management and examination of the smart city big data. But, the blockchains are found to have computationally high costs, and failed to improve the security, not adequate resource-constrained IoT devices have been designated for smart cities. In order to address these issues, the proposed novel blockchain model called blockchain secured Merkle hash zero correlation distinguisher (BSMH-ZCD) is suitable for IoT devices within the cloud infrastructure. The …

MCDM-based routing for IoT-enabled smart water distribution network

Authors

Hitesh Mohapatra,Bhabendu Kumar Mohanta,Mohammad Reza Nikoo,Mahmoud Daneshmand,Amir H Gandomi

Journal

IEEE Internet of Things Journal

Published Date

2022/10/27

The work consists of two subapproaches. In the first approach, an analytical model is developed using trapezium fuzzy numbers in decision-making problems for an Internet of Things-based water distribution network. The second phase explains the integration of the previous phase with the MCDM-based location routing protocol (M-LRP). The water distribution network has three components static water source, the utility center (UC) which can be located in the proper position, and the consumer. The objective of this work is to select an optimal route between the UC and the consumer by considering multiple criteria. The simulation result shows that the proposed multicriterion-based decision-making (MCDM)-based routing protocol outperforms both existing MCDM-based and non-MCDM-based routing schemes. The proposed model outperforms the existing models like non-MCDM-based and MCDM-based routing …

Special issue on robustness and efficiency in the convergence of artificial intelligence and IoT

Authors

Meikang Qiu,Bhavani Thuraisingham,Mahmoud Daneshmand,Huansheng Ning,Payam Barnaghi

Journal

IEEE Internet of Things Journal

Published Date

2021/6/4

Today, the Internet of Things (IoT) is increasingly flourishing with establishing ubiquitous connections between smart devices and objects, and by 2020, there will be a total of 30 billion connected things reported by IDC. The unprecedented data explosion provides immense opportunities for valuable information mining. At the same time, it also floods the infrastructure with tremendous values it necessarily handles and proposes high challenges to traditional data storing or processing techniques. On the other hand, artificial intelligence (AI) has become a key component for many applications that profoundly change our lives. Machine learning, especially deep learning (DL) technologies, vastly improves traditional computer science and networking technologies. The convergence of AI and IoT enables data to be quickly explored and turned into significant decisions. For companies and enterprises, AI enhances the …

Authentication and key management in distributed iot using blockchain technology

Authors

Soumyashree S Panda,Debasish Jena,Bhabendu Kumar Mohanta,Somula Ramasubbareddy,Mahmoud Daneshmand,Amir H Gandomi

Journal

IEEE Internet of Things Journal

Published Date

2021/3/4

The exponential growth in the number of connected devices as well as the data produced from these devices call for a secure and efficient access control mechanism that can ensure the privacy of both users and data. Most of the conventional key management mechanisms depend upon a trusted third party like a registration center or key generation center for the generation and management of keys. Trusting a third party has its own ramifications and results in a centralized architecture; therefore, this article addresses these issues by designing a Blockchain-based distributed IoT architecture that uses hash chains for secure key management. The proposed architecture exploits the key characteristics of the Blockchain technology, such as openness, immutability, traceability, and fault tolerance, to ensure data privacy in IoT scenarios and, thus, provides a secure environment for communication. This article also …

See List of Professors in Mahmoud Daneshmand, Ph.D University(Stevens Institute of Technology)

Mahmoud Daneshmand, Ph.D FAQs

What is Mahmoud Daneshmand, Ph.D's h-index at Stevens Institute of Technology?

The h-index of Mahmoud Daneshmand, Ph.D has been 28 since 2020 and 32 in total.

What are Mahmoud Daneshmand, Ph.D's top articles?

The articles with the titles of

In Memory of Dr. David Belanger:(12/8/1944–11/18/2022)

An edge-AI enabled autonomous connected ambulance route resource recommendation protocol (ACA-R3) for eHealth in smart cities

Chatbots to chatgpt in a cybersecurity space: Evolution, vulnerabilities, attacks, challenges, and future recommendations

A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges

A three factor based authentication scheme of 5G wireless sensor networks for IoT system

A new technology perspective of the Metaverse: Its essence, framework and challenges

Guest Editorial Special Issue on Empowering the Future Generation Systems: Opportunities by the Convergence of Cloud, Edge, AI, and IoT

Guest Editorial Special Issue on Smart Cities and Systems: Theories, Tools, Trends, Applications, Challenges, and Opportunities

...

are the top articles of Mahmoud Daneshmand, Ph.D at Stevens Institute of Technology.

What are Mahmoud Daneshmand, Ph.D's research interests?

The research interests of Mahmoud Daneshmand, Ph.D are: Big Data Analytics & ML, Internet of Things (IoT), Data Science, Streaming Data Analytics, AI & Deep Learning

What is Mahmoud Daneshmand, Ph.D's total number of citations?

Mahmoud Daneshmand, Ph.D has 5,485 citations in total.

What are the co-authors of Mahmoud Daneshmand, Ph.D?

The co-authors of Mahmoud Daneshmand, Ph.D are Honggang Wang, Professor, Department Chair and IEEE Fellow, AAIA Fellow.

    Co-Authors

    H-index: 51
    Honggang Wang, Professor, Department Chair and IEEE Fellow, AAIA Fellow

    Honggang Wang, Professor, Department Chair and IEEE Fellow, AAIA Fellow

    University of Massachusetts Dartmouth

    academic-engine

    Useful Links