Throughout the course of human history, owing to innovations that shape the future of mankind, many technologies have been innovated and used towards making people's lives easier. Such technologies have made us who we are today and are involved with every domain that is vital for human survival such as agriculture, healthcare, and transportation. The Internet of Things (IoT) is one such technology that revolutionizes almost every aspect of our lives, found early in the 21st century with the advancement of Internet and Information Communication (ICT) Technologies. As of now, the IoT is served in almost every domain, as we mentioned above, allowing the connectivity of digital objects around us to the Internet, thus allowing the remote monitoring, control, and execution of actions based on underlying conditions, making such objects smarter. Over time, the IoT has progressively evolved and paved the way towards the Internet of Nano-Things (IoNT) which is the use of nano-size miniature IoT devices. The IoNT is a relatively new technology that has lately begun to establish a name for itself, and many are not aware of it, even in academia or research. The use of the IoT always comes at a cost, owing to the connectivity to the Internet and the inherently vulnerable nature of IoT, wherein it paves the way for hackers to compromise security and privacy. This is also applicable to the IoNT, which is the advanced and miniature version of IoT, and brings disastrous consequences if such security and privacy violations were to occur as no one can notice such issues pertaining to the IoNT, due to their miniaturized nature and novelty in the field. The lack of research in the IoNT domain has motivated us to synthesize this research, highlighting architectural elements in the IoNT ecosystem and security and privacy challenges pertaining to the IoNT. In this regard, in the study, we provide a comprehensive overview of the IoNT ecosystem and security and privacy pertaining to the IoNT as a reference to future research.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007150 | PMC |
| http://dx.doi.org/10.3390/s23052807 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The Venus score for the assessment of the quality and trustworthiness of biomedical datasets.
BioData Min
January 2025
Fondazione Bruno Kessler, Trento, Italy.
Biomedical datasets are the mainstays of computational biology and health informatics projects, and can be found on multiple data platforms online or obtained from wet-lab biologists and physicians. The quality and the trustworthiness of these datasets, however, can sometimes be poor, producing bad results in turn, which can harm patients and data subjects. To address this problem, policy-makers, researchers, and consortia have proposed diverse regulations, guidelines, and scores to assess the quality and increase the reliability of datasets.
View Article and Find Full Text PDFA Bibliometric Review of Software Tools in Plastic Surgery: How They Benefit Surgeons and Improve Practice from 2004 to 2024.
Aesthetic Plast Surg
January 2025
Department of Craniomaxillofacial Surgery, Plastic Surgery Hospital, CAMS&PUMC (Chinese Academy of Medical Sciences and Peking Union Medical College), Beijing, 100144, China.
Background: Bibliometric analyses of software applications in plastic surgery are relatively limited. This study aims to address this gap by summarizing current research trends and providing insights that may guide future developments in this field.
Methods: Data were retrieved from the Web of Science Core Collection.
Integration of large language models and federated learning.
Patterns (N Y)
December 2024
Zhejiang University, Hangzhou, China.
As the parameter size of large language models (LLMs) continues to expand, there is an urgent need to address the scarcity of high-quality data. In response, existing research has attempted to make a breakthrough by incorporating federated learning (FL) into LLMs. Conversely, considering the outstanding performance of LLMs in task generalization, researchers have also tried applying LLMs within FL to tackle challenges in relevant domains.
View Article and Find Full Text PDFInnovative Approaches in Regulatory Affairs: Leveraging Artificial Intelligence and Machine Learning for Efficient Compliance and Decision-Making.
AAPS J
January 2025
Department of Regulatory Affairs, National Institute of Pharmaceutical Education and Research (NIPER), Hyderabad, Telangana, India.
Artificial Intelligence (AI) and AI-driven technologies are transforming industries across the board, with the pharmaceutical sector emerging as a frontrunner beneficiary. This article explores the growing impact of AI and Machine Learning (ML) within pharmaceutical Regulatory Affairs, particularly in dossier preparation, compilation, documentation, submission, review, and regulatory compliance. By automating time-intensive tasks, these technologies streamline workflows, accelerate result generation, and shorten the product approval timeline.
View Article and Find Full Text PDFApplying fractional calculus to malware spread: A fractal-based approach to threat analysis.
PLoS One
January 2025
IT4Innovations, VSB - Technical University of Ostrava, Ostrava, Czech Republic.
Malware is a common word in modern era. Everyone using computer is aware of it. Some users have to face the problem known as Cyber crimes.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!