Reza M. PariziKennesaw State University, Atlanta, USA · Software Engineering and Game Development
Reza M. Parizi
Doctor of Philosophy
About
213
Publications
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Introduction
Dr. Parizi is the Director of the Decentralized Science Lab (dSL) and a consummate technologist and cybersecurity researcher with an entrepreneurial spirit at KSU. He is a senior IEEE member, IEEE Blockchain Community, and ACM. Before joining KSU, he was with the New York Institute of Technology. His interests are R&D in federated learning, decentralized AI, IoT security, Blockchain, and emerging issues in secure software-run world applications.
Publications
Publications (213)
The expansion of Industrial Cyber-Physical Systems (ICPS) has introduced new challenges in security and privacy, highlighting a research gap in effective anomaly detection while preserving data confidentiality. In the ICPS landscape, where vast amounts of sensitive industrial data are exchanged, ensuring privacy is not just a regulatory compliance...
Although federated learning offers a level of privacy by aggregating user data without direct access, it remains inherently vulnerable to various attacks, including poisoning attacks where malicious actors submit gradients that reduce model accuracy. In addressing model poisoning attacks, existing defense strategies primarily concentrate on detecti...
Multi-stage threats like advanced persistent threats (APT) pose severe risks by stealing data and destroying infrastructure, with detection being challenging. APTs use novel attack vectors and evade signature-based detection by obfuscating their network presence, often going unnoticed due to their novelty. Although machine learning models offer hig...
Federated learning (FL) is a collaborative artificial intelligence (AI) approach that enables distributed training of AI models without data sharing, thereby promoting privacy by design. However, it is essential to acknowledge that FL only offers a partial solution to safeguard the confidentiality of AI and machine learning (ML) models. Unfortunate...
Cardiovascular diseases (CVD) are the leading cause of death globally, and early detection can significantly improve outcomes for patients. Machine learning (ML) models can help diagnose CVDs early, but their performance is limited by the data available for model training. Privacy concerns in healthcare make it harder to acquire data to train accur...
Artificial Intelligence (AI) refers to the intelligence demonstrated by machines, and within the realm of AI, Machine Learning (ML) stands as a notable subset. ML employs algorithms that undergo training on data sets, enabling them to carry out specific tasks autonomously. Notably, AI holds immense potential in the field of software engineering, pa...
Advancements in wearable medical devices using the IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), efficient healthcare services can be provided to patients. Healthcare professionals have effectively used AI-based models to analyze the data collected from IoHT devices to treat...
Advancements in wearable medical devices in IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), we are witnessing how efficient healthcare services are provided to patients and how healthcare professionals are effectively used AI-based models to analyze the data collected from IoH...
Ethereum blockchain has shown great potential in providing the next generation of the decentralized platform beyond crypto payments. Recently, it has attracted researchers and industry players to experiment with developing various Web3 applications for the Internet of Things (IoT), Defi, Metaverse and many more. Although Ethereum provides a secure...
Blockchain is a revolutionary technology, and its growth started in various industries (such as IT, education, business, banking, and many others) to capitalize on it. Currently, in higher education institutions (HEIs) adoption of blockchain education needs to be improved in the academic programs and curriculums. In addition, HEIs must make many in...
Integrating blockchain into the Internet of Things (IoT) for security is a new development in computational communication systems. While security threats are changing their strategies and constructing new threats on blockchain-based IoT systems. Also, in combining blockchain with IoT networks, malicious transactions and active attacks deliver more...
Industrial Internet of Things (IIoT) systems depend on a growing number of edge devices such as sensors, controllers, and robots for data collection, transmission, storage, and processing. Any kind of malicious or abnormal function by each of these devices can jeopardize the security of the entire IIoT. Moreover, they can allow malicious software i...
Federated learning (FL) is known to perform machine learning tasks in a distributed manner. Over the years, this has become an emerging technology, especially with various data protection and privacy policies being imposed. FL allows for performing machine learning tasks while adhering to these challenges. As with the emergence of any new technolog...
By the emergence of the fourth industrial revolution, interconnected devices and sensors generate large-scale, dynamic, and inharmonious data in Industrial Internet of Things (IIoT) platforms. Such vast heterogeneous data increase the challenges of security risks and data analysis procedures. As IIoT grows, cyber-attacks become more diverse and com...
Adopting cryptography has given rise to a significant evolution in Artificial Intelligence (AI). This paper studies the path and stages of this evolution. We start with reviewing existing relevant surveys, noting their shortcomings, especially the lack of a close look at the evolution process and solid future roadmap. These shortcomings justify the...
Presents the introductory editorial for this issue of the publication.
Searchable Encryption (SE) enables data owners to search remotely stored ciphertexts selectively. A practical model that is closest to real life should be able to handle search queries with multiple keywords and multiple data owners/users, and even return the top-k most relevant search results when requested. We refer to a model that satisfies all...
Nowadays, blockchain-based technologies are being developed in various industries to improve data security. In the context of the Industrial Internet of Things (IIoT), a chain-based network is one of the most notable applications of blockchain technology. IIoT devices have become increasingly prevalent in our digital world, especially in support of...
Nowadays, blockchain-based technologies are being
developed in various industries to improve data security. In the
context of the Industrial Internet of Things (IIoT), a chain-based
network is one of the most notable applications of blockchain
technology. IIoT devices have become increasingly prevalent in
our digital world, especially in support of...
The beginning of 2020 is associated with the emergence and spread of the COVID-19 disease. The characteristics of this virus, such as high transmission power and lack of definitive treatment have caused problems in all aspects of organizational economics. Restrictions that were imposed to deal with the virus affected the global economy. Fear of bei...
Software-defined networks (SDN) has emerged with the capability to program in order to enhance flexibility, management, and testing of new ideas in the next generation of networks by removing current network limitations. Network virtualization and functionalization are critical elements supporting the delivery of future network services, especially...
Internet of Things (IoT) devices are mass-produced and rapidly released to the public, designed for different applications ranging from monitoring of the environment to on-demand electrical switches and so on. These IoT devices are often heterogeneous in nature, only to receive updates at infrequent inter- vals, and can remain ‘out of sight’ on a h...
Federated learning involves training statistical models over remote devices such as mobile phones while keeping data localized. Training in heterogeneous and potentially massive networks introduces opportunities for privacy-preserving data analysis and diversifying these models to become more inclusive of the population. Federated learning can be v...
The Internet of Things (IoT) is a technology built upon various physical objects equipped with different types of sensors, which are connected together using communication methods. These devices have been applied to several domains, especially healthcare. In addition to the numerous benefits that IoT has demonstrated in healthcare, this technology...
Today's business environment is characterized by uncertainty and competition, so the capability to adapt to the evolving era and unforeseen challenges is essential in business strategies. Recent studies on extended enterprise indicate that collaboration among different stakeholders is beneficial for surviving these unexpected changes. However, the...
In today’s world, industries are looking to improve their productivity through effective logistics and supply chain management. The efficiency of the supply chain in dealing with the huge volumes of data plays a key role in the overall performance of businesses. Supply Chain Finance (SCF) aims to improve the robustness and efficiency of companies’...
Researchers working on cancer datasets often encounter two major challenges in their data science tasks. First, the numbers of samples are often low while the numbers of features needed for extraction are high. Secondly, the existence of noise and uncertainties in datasets can cause issues with any data science related tasks. Addressing such issues...
Federated learning (FL) enables collaborative training of machine learning (ML) models while preserving user data privacy. Existing FL approaches can potentially facilitate collaborative ML, but ensuring secure trading/sharing of training data is challenging in practice, particularly in the presence of adversarial FL clients. The ongoing security c...
Blockchain technology has found extensive applications in recent years, especially in financial and currency exchange applications, due to improved trustworthiness and security. Although blockchain technology improves security by design, it is not immune to security threats and vulnerabilities. Ethereum, as a decentralized, open-source blockchain,...
Developing successful software with no defects is one of the main goals of software projects. In order to provide a software project with the anticipated software quality, the prediction of software defects plays a vital role. Machine learning, and particularly deep learning, have been advocated for predicting software defects, however both suffer...
Hadoop Distributed File System (HDFS) is one of the widely used distributed file systems in Big Data analysis for frameworks such as Hadoop. It is used to manage a large volume of data with low-cost commodity hardware. However, vulnerabilities in HDFS can be exploited for nefarious activities, as the security seems to be inconsistent and not of a p...
The rise in popularity of Internet of Things (IoT) devices has attracted hackers to develop IoT-specific attacks. The microservice architecture of IoT devices relies on the Internet to provide their intended services. An unguarded IoT network makes inter-connected devices vulnerable to attacks. It will be a tedious and ineffective process to manual...
Industrial Control System (ICSs), one type of Operational Technology (OT), plays an essential role in monitoring and controlling critical infrastructures such as power plants, smart grids, oil and gas industries, and transportation. To maintain the security of ICSs from cyber-attacks, they were placed on isolated communication networks, where they...
In this paper, we introduce a robust authentication protocol for Vehicle-to-Grid (V2G) communication through lightweight and secure cryptographic primitives. In addition, we utilize signcrypt and unsigncrypt functions which facilitate the consumers to have secure access to the services. The security evaluation of the introduced framework shows its...
Federated Learning (FL) is known to perform Machine Learning tasks in a distributed manner. Over the years, this has become an emerging technology especially with various data protection and privacy policies being imposed FL allows performing machine learning tasks whilst adhering to these challenges. As with the emerging of any new technology, the...
As online retail services proliferate and are pervasive in modern lives, applications for classifying fashion apparel features from image data are becoming more indispensable. Online retailers, from leading companies to start-ups, can leverage such applications in order to increase profit margin and enhance the consumer experience. Many notable sch...
The massive integration of low-cost communication networks and Internet of Things (IoT) in today’s cyber-physical grids has been accompanied by significant concerns regarding potential security threats. Specifically, wireless communication technology introduces additional vulnerability in terms of network security. In addition to cyber-security iss...
The ever-rising applications of drones in the Internet of Things (IoT) era is offering many opportunities and challenges. Owing to drone abilities (silent flying, capturing photos and videos, etc.), there is widespread concern about drone authentication and which drones allow to fly. In this regard, there are several machine learning (ML) proposals...
The Internet of Things (IoT) is made up of billions of physical devices connected to the Internet via networks that perform tasks independently with less human intervention. Such brilliant automation of mundane tasks requires a considerable amount of user data in digital format, which in turn makes IoT networks an open-source of Personally Identifi...
Due to the influence of information fusion in Industrial Internet of Things (IIoT) environments, there are many problems, such as weak intelligent visual target positioning, dissapearing features, large error in visual positioning processes, and so on. Therefore, this paper proposes a weak target positioning method based on multi-information fusion...
The need for cyber resilience is increasingly important in our technology-dependent society where computing devices and data have been, and will continue to be, the target of cyber-attackers, particularly advanced persistent threat (APT) and nation-state/sponsored actors. APT and nation-state/sponsored actors tend to be more sophisticated, having a...
Machine learning (ML) has demonstrated great potential to revolutionize the networking field. In this paper, we present a large-scale empirical study to evaluate the effectiveness of state-of-the-art ML algorithms for network application security. In our experiments, six classical ML algorithms and three neural network algorithms are evaluated over...
When people are in an interview, with the interview questions, people’s emotions will change differently. Therefore, it is very helpful to detect people’s emotions in real-time. To do so, comprehensive data collection was performed through the voice recording platform and the Empatica E4 wristband (biofeedback). Also, through using both existing fe...
COVID-19 was first discovered in December 2019 and has continued to rapidly spread across countries worldwide infecting thousands and millions of people. The virus is deadly, and people who are suffering from prior illnesses or are older than the age of 60 are at a higher risk of mortality. Medicine and Healthcare industries have surged towards fin...
When focusing on the general area of data mining, high-utility itemset mining (HUIM) can be defined as an offset of frequent itemset mining (FIM). It is known to emphasize more factors critically, which gives HUIM its intrinsic edge. Due to the flourishing development of the IoT technique, the uncertainty patterns mining is also attractive. Potenti...
In recent years, a new generation of architecture has emerged in the world of computer networks, known as software-defined networking (SDN), that aims to improve and remove the limitations of traditional networks. Although SDN provides viable benefits, it has faced many security threats and vulnerability-related issues. To solve security issues in...
Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integ...
In recent years, the Internet of Things (IoT) has drawn convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems incorporating technological, economic, and social prospects. It is evolving healthcare systems from c...
The Internet of Things (IoT) provides smart solutions for future urban communities to address key benefits with the least human intercession. A smart home offers the necessary capabilities to promote efficiency and sustainability to a resident with their healthcare-related, social, and emotional needs. In particular, it provides an opportunity to a...
Universal Serial Bus (USB) is widely used, for example to facilitate hot-swapping and plug-and-play. However, USB ports can be exploited by an adversary to extract private or personal data from the connected devices. Hence, a number of organizations and workplaces have prohibited their employees from using USB devices, and there have been efforts t...
A flaky test is a test that may lead to different results in different runs on a single code under test without any change in the test code. Test flakiness is a noxious phenomenon that slows down software deployment, and increases the expenditures in a broad spectrum of platforms such as software-defined networks and Internet of Things environments...
Vehicle visual tracking is a challenging issue in intelligent transportation systems. The tracking gets more challenging when vehicles change direction at intersections. Undetermined motion flows, occlusion, and congestion are the potential issues of vehicle tracking at intersections. In this study, a new method for tracking multiple vehicles from...
In recent years, we have witnessed the dramatic growth of mobile devices in the IoT domain, which enables people and services to interconnect and exchange information constantly. The number of IoT mobile users tends to grow larger connecting more and more people and devices. On the flip side, IoT mobile devices are subject to insecure design, imple...