Gautam Srivastava

Brandon University · Department of Computer Science

We present a novel approach for addressing computer vision tasks in intelligent transportation systems, with a strong focus on data security during training through federated learning. Our method leverages visual transformers, training multiple models for each image. By calculating and storing visual image features as well as loss values, we propos...

The agriculture sector contributes significantly to the overall development of the Indian economy. This sector can be revamped by modern technological interventions like the Internet of Things (IoT) and Machine Learning (ML) along with traditional processes. To improve sustainable growth in the agriculture field, monitoring of parameters like tempe...

The presence of threats and anomalies in the Internet of Things infrastructure is a rising concern. Attacks, such as Denial of Service, User to Root, Probing, and Malicious operations can lead to the failure of an Internet of Things system. Traditional machine learning methods rely entirely on feature engineering availability to determine which dat...

Internet of Things (IoT) devices like wearable devices have enabled quick monitoring of ECG signals with lower resources than multi-electrode ECG devices, opening up development opportunities for sustainable ECG-based emotion recognition. However, existing methods that rely on pre-designed features extracted from single-lead ECG signals cannot auto...

Federated Learning (FL) has emerged as a pivotal technology for the Internet of Things (IoT) that models distributed client data without compromising privacy. The IoT-based wearable generates data and FL running on a private edge performing Human Activity Recognition (HAR). In this paper, we proposed a novel technique to protect sensitive data duri...

In recent years, the Internet has facilitated the emergence of social media platforms as significant channels for individuals to express their thoughts and engage in instantaneous interactions. However, the reliance on online reviews has also given rise to deceptive practices, where anonymous spammers generate fake reviews to manipulate the percept...

With the rapid growth of the Internet of Things, sensors have become integral components of smart homes, enabling real-time monitoring and control of various aspects ranging from energy consumption to security. In this context, we cannot underestimate the importance of sensor-based data in ensuring the safety and well-being of occupants, particular...

The rapid proliferation of Unmanned Aircraft Systems (UAS) introduces new threats to national security. UAS technologies have dramatically revolutionized legitimate business operations while providing powerful weaponizing systems to malicious actors and criminals. Due to their inherited wireless capabilities, they are an easy target for cyber threa...

Counterfeit medical devices pose a threat to patient safety, necessitating a secure device authentication system for medical applications. Resource‐constrained sensory nodes are vulnerable to hacking, prompting the need for robust security measures. Token‐based authentication schemes, such as one‐time passwords (OTPs), smart cards, key fobs, and mo...

Remote diagnosis enables healthcare professionals to evaluate and diagnose patients from a distance using telecommunication technologies, enhancing healthcare delivery by improving accessibility, especially for those in remote or underserved areas. One of the significant sustainability challenges in remote medical diagnostics is offering timely ass...

Blockchains are usually managed by blockchain nodes, which maintain a copy of all the blockchain's data and participate in validating transactions and reaching consensus with other blockchain nodes. However, running a blockchain node on your own is not easy due to the high maintenance costs and specialized hardware needed. Blockchain-as-a-service h...

Air pollution poses a significant threat to urban environments, and accurate prediction of multiple air pollutants is crucial for effective mitigation strategies. This study introduces a novel time-aware auto-regressive long-short-term memory (TAR LSTM) approach to address this challenge by developing a multivariate prediction model using artificia...

In remote teaching, massive resource data types have heterogeneous diversity attributes. Currently, recommendation algorithms only consider the optimal solution in the local domain under an attention mechanism to ensure efficiency, without considering the embedding correlation of recommendation features in the entire local domain, resulting in subo...

The widespread implementation of Artificial Intelligence (AI) has led to significant advancements in disease diagnosis. Personalized Federated Learning (FL) trains models tailored to each patient’s needs but often overlooks model architecture heterogeneity. We propose a novel Co-training-based personalized FL with Generative Adversarial Networks (G...

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...

Sixth-generation (6G) mobile computing is a wireless, cutting-edge technology that is made possible by the digital interconnectedness of everything (IoE). 6G connection depends on mobile edge and fog computing integration. Due to the mobility of various end users, task offloading in these computing devices is hard and unpredictable. The unexpected...

Open radio access networks (RAN) enhance the capabilities of traditional RAN by introducing features such as interoperability, open interfaces, software/hardware separation, and intelligence. Open RAN has several use cases in cellular vehicle-to-everything communications such as low-latency information exchange between vehicles and RAN intelligence...

The detrimental effects on human health caused by air pollution show that being able to predict air quality is a task of utmost significance. The application of Artificial Intelligence (AI) and the Internet of Things (IoT) is seen as promising in this domain. The performances of state-of-the-art models in terms of prediction accuracy vary with diff...

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...

The Cenozoic era is the digital age where people, things, and any device with network capabilities can communicate with each other, and the Internet of Things (IoT) paves the way for it. Almost all domains are adopting IoT from smart home appliances, smart healthcare, smart transportation, Industrial IoT and many others. As the adoption of IoT incr...

Consumer electronics are substantially compromised by malware, which can traverse numerous operating systems and file formats. Considerable effort has been devoted to developing malware detection systems that employ Machine Learning (ML) and Deep Learning (DL). However, these models are susceptible to adversarial attacks, where maliciously crafted...

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...

Software Defined Networking (SDN) has brought significant advancements in network management and programmability. However, this evolution has also heightened vulnerability to Advanced Persistent Threats (APTs), sophisticated and stealthy cyberattacks that traditional detection methods often fail to counter, especially in the face of zero-day exploi...

Intrusion detection and prevention has been an area of active research in the use of machine learning for cyber security practices. Artificial Neural Networks (ANN) are one of the best-known models when it comes to accurately classifying intrusions into attack classes or benign profiles but they are resource-intensive. A server is typically associa...

Recently, Cooperative Spectrum Sensing (CSS) for Cognitive Radio Networks (CRN) plays a significant role in efficient 5G wireless communication. Spectrum sensing is a significant technology in CRN to identify underutilized spectrums. The CSS technique is highly applicable due to its fast and efficient performance. 5G wireless communication is widel...

Defect detection in additive manufacturing refers to the evaluation of collected industrial images and the identification of parts that cause anomalies to optimize decision-making in an industrial production context. The advent of the Internet of Things and the widespread installation of electronic sensors, such as image sensors in industrial produ...

Time-series prediction is increasingly popular in a variety of applications, such as smart factories and smart transportation. Researchers have used various techniques to predict power consumption, but existing models lack discussion of collaborative learning and privacy issues among multiple clients. To address these issues, we propose Multi-Head...

This paper introduces a novel solution for personal recommendation in consumer electronic applications. It addresses, on the one hand, the data confidentiality during the training, by exploring federated learning and trusted authority mechanisms. On the other hand, it deals with data quantity, and quality by exploring both transformers and consumer...

Grey Wolf optimization (GWO) is a newly developed stochastic meta-heuristic technique motivated by nature. It shows potential in diverse optimization challenges. It replicates grey wolf hunting behaviour and social hierarchy, exploring the solution space similar to their natural process. The algorithm efficiently explores and converges to the optim...

Combining deep learning (DL) with nanotechnology holds promise for transforming key facets of nanoscience and technology. This synergy could pave the way for groundbreaking advancements in the creation of novel materials, devices, and applications, unlocking unparalleled capabilities. In addition, monitoring psychological, emotional, and physical s...

The recent advancement of the Internet of Things (IoT) and information technology has led to the rapid expansion of interconnectivity among a billion devices across various applications. The advent of massive data has resulted in greater computational dependence, posing obstacles to applying security policies in energy-sensitive devices. However, p...

Based on the development needs of Industry 5.0, Advanced On-orbit Systems (AOS) can be integrated with terrestrial 5G networks, with large-scale IoT links as well as with flexible deployment and resource optimization, enabling efficient transmission of multiple types of industrial data, human-machine collaboration, and improving the flexibility, in...

The recent tragic events in Sikkim and other Himalayan regions highlight the urgent need for research on flash floods in steep channels. Catastrophic floods like those at Lhonak Lake in Sikkim, caused by heavy rainfall and a glacial lake burst, resulted in loss of life and extensive damage. Similar incidents in Solan and Shimla underscore the vulne...

Human perception heavily relies on two primary senses: vision and hearing, which are closely inter-connected and capable of complementing each other. Consequently, various multimodal learning tasks have emerged, with audio-visual event localization (AVEL) being a prominent example. AVEL is a popular task within the realm of multimodal learning, wit...

The Internet of Things (IoT) has significantly impacted the evolution of consumer-oriented smart environments, primarily due to its capacity for transformative device-to-device communication. While this capability enhances user convenience and experience in the Consumer IoT sector, it also generates vast amounts of data. While beneficial for consum...

Drug-drug interactions (DDIs) are an important biological phenomenon which can result in medical errors from medical practitioners. Drug interactions can change the molecular structure of interacting agents which may prove to be fatal in the worst case. Finding drug interactions early in diagnosis can be pivotal in side-effect prevention. The growt...

The continuing, unprecedented growth in urban population has placed renewed emphasis on aspects such as sustainable development, environmental impact, public health, and mobility. Urban sensing plays a vital role in the ability to monitor and control infrastructure and also to make data-driven urban planning and management. This special issue of th...

The most advanced power grid design, known as a ‘smart power grid’, integrates information and communication technology (ICT) with a conventional grid system to enable remote management of electricity distribution. The intelligent cyber‐physical architecture enables bidirectional, real‐time data sharing between electricity suppliers and consumers t...

Smart grids have become an emerging topic due to net-zero emissions and the rapid development of artificial intelligence (AI) technology focused on achieving targeted energy distribution and maintaining operating reserves. In order to prevent cyber-physical attacks, issues related to the security and privacy of grid systems are receiving much atten...

As the adoption of Consumer Internet of Things (CIoT) devices surges, so do concerns about security vulnerabilities and privacy breaches. Given their integration into daily life and data collection capabilities, it is crucial to safeguard user privacy against unauthorized access and potential leaks proactively. Federated learning, an advanced machi...

The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the domain of natural language processing, which is propelling us toward the development of machines that can understand and communicate using language in a manner that closely resembles that of humans. GPT is based on the transformer architecture, a deep neural netwo...

The increased charging demand resulting from the rapid development of electric vehicles (EVs) poses various challenges to the stable operation of the distribution network and smart grid. Due to the stochastic EV charging behaviour, the high charging demand at the charging stations (CSs) elevates the load curve which may lead to a spatially imbalanc...

The integration of Unmanned Aerial Vehicles (UAVs) in agriculture has advanced precision farming by enhancing the ability to monitor and optimize agricultural plots. Object detection-critical for identifying crops, pests, and diseases-presents challenges due to data availability and varying environmental conditions. To address these challenges, we...

This article presents a highly efficient technique for pattern mining in the realm of customer behavior analysis, termed hybrid clustering patterns for customer behavior analysis (HCP-CBA). It leverages decomposition techniques to uncover relevant patterns by examining correlations among customer transactions within the dataset. Initially, the tran...

Future Fog computing networks are basis of many smart customer applications in the areas of transportation and healthcare. Timely execution of application related tasks is a key challenge in such fog computing networks so that application reliability and customer satisfaction can be maximized. In this paper, we focus on vehicular fog computing scen...

The rapid advancement of big data and artificial intelligence (AI) in healthcare heightens the urgency for accurate medical text sentiment analysis. The privacy protection of medical data has been a crucial concern due to its sensitivity. The Internet of Medical Things (IoMT) facilitates large-scale data collection at lower cost, enabling precision...

Due to global warming and climate change, power generation from renewable resources, such as solar, wind, fuel cells, and others, is becoming increasingly important. The smart grid’s incorporation of renewable energy resources makes Peer-to-Peer (P2P) energy trading through the local energy market possible. Due to its distributed nature, Peer-to-Pe...

Recent developments in the Internet of Vehicles (IoV) and Vehicular Adhoc Networks (VANET) have revolutionized our infrastructure, making it safer, more convenient, and efficient. VANET provide smart traffic control, event allocation, and real-time information. Existing vehicles in VANET are now equipped with intelligent navigation, entertainment,...

Deep learning approaches for malware attacks are effective when trained on the same organizational network. However, it is challenging to develop a trustworthy distributed malware detection model that employs diverse training data from multiple sources. This is primarily due to privacy concerns and the lack of a standardized dataset. Confidentialit...

Decomposition MapReduce mining for fake news analysis (DMRM-FNA), a novel generic parallel pattern-mining framework, is developed in this article to solve difficulties in social network analysis using big data exploration. The first difficulty faced by existing techniques is the inability to retrieve actionable insights into the structure of fake n...

The deployment of artificial intelligence (AI) in Intelligent Transportation Systems (ITS), especially in the field of Intelligent Transportation Cyber-Physical Systems (ITCPS) has a strong potential to achieve higher efficiency, reliability, and increased safety in both transportation and traffic. This work focuses on the real-world implementation...

The widespread presence of explicit content on social media platforms has far-reaching consequences for individuals, relationships, and society as a whole. It is crucial to tackle this problem by implementing efficient content moderation, educating users, and creating technologies and policies that foster a more secure and wholesome online atmosphe...