Article
Computer Science, Hardware & Architecture
Joseph R. Rose, Matthew Swann, Konstantinos P. Grammatikakis, Ioannis Koufos, Gueltoum Bendiab, Stavros Shiaeles, Nicholas Kolokotronis
Summary: The widespread use of IoT devices brings many benefits to society, but also poses cybersecurity risks. This paper explores the potential of using network profiling, machine learning, and game theory to secure IoT against cyber attacks, proposing an anomaly-based intrusion detection solution.
JOURNAL OF SYSTEMS ARCHITECTURE
(2022)
Article
Computer Science, Information Systems
Omid Akbarzadeh, Mehrshid Baradaran, Mohammad R. Khosravi
Summary: The paper aims to design and develop an innovative solution in the Smart Building context to enhance guests' hospitality during COVID-19 and future pandemics. The solution supports features like online appointments, smart navigation, and queue management, addressing issues in smart building and creating a unique platform integrating multiple IoT technologies.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Multidisciplinary Sciences
Yasir Ali, Habib Ullah Khan
Summary: The supply chain management of COVID-19 vaccine is a complex task, and IoT technology is a suitable solution. This study proposes a decision making model to select the right IoT platform for the logistics and transportation process of COVID-19 vaccine. The model is validated and tested through surveys and shows high accuracy and reliability.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Hardware & Architecture
Mahender Kumar, Satish Chand
Summary: This paper introduces a privacy-preserving medical data sharing system, MedHypChain, based on Hyperledger Fabric, aiming to achieve patient-centered interoperability in healthcare, ensuring confidentiality, anonymity, traceability, and unforgeability of data. Through comparisons with other blockchain-based healthcare systems, it is found that this proposed scheme has lower computation and communication costs while achieving all security features.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Xuran Li, Bishenghui Tao, Hong-Ning Dai, Muhammad Imran, Dehuan Wan, Dengwang Li
Summary: The outbreak of the COVID-19 pandemic has deeply impacted the lifestyle of the general public and the healthcare system, leading to the proposal of using the Internet of Medical Things (IoMT) to address the challenges. However, privacy and security concerns hinder the wide adoption of IoMT. We propose a framework of blockchain-enabled IoMT to tackle these issues and explore the opportunities and potential in fighting against the COVID-19 pandemic.
PERVASIVE AND MOBILE COMPUTING
(2021)
Article
Computer Science, Information Systems
Amir Vafid Hanafi, Ali Ghaffari, Hesam Rezaei, Aida Valipour, Bahman Arasteh
Summary: This study proposes a new intrusion detection system model for IoT networks using an improved Binary Golden Jackal Optimization algorithm (IBGJO) and Long Short-Term Memory (LSTM) network. The proposed model achieves an accuracy rate of 98.21% on the NSL-KDD and CICIDS2017 datasets. The results show that the improved GJO algorithm effectively selects relevant features from IDS data and the LSTM accurately classifies the samples. Additionally, the proposed model significantly outperforms Support Vector Machine, K-Nearest Neighbors, and Naive Bayes.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Yuheng Gu, Yu Yang, Yu Yan, Fang Shen, Minna Gao
Summary: This paper proposes a new multi-module intrusion detection system, which effectively deals with the high dimensionality and imbalance of IoT data and improves the detection rate of unknown attacks and the misclassification of rare classes of attack traffic.
COMPUTER COMMUNICATIONS
(2023)
Review
Green & Sustainable Science & Technology
Atefeh Hemmati, Amir Masoud Rahmani
Summary: The medical industry has embraced technology, particularly in the form of the Internet of Medical Things (IoMT), to improve accuracy and efficiency, especially during the COVID-19 pandemic. This paper evaluates recent studies in the IoMT domain using the Systematic Literature Review (SLR) methodology and focuses on factors such as delay, performance, accuracy, security, and cost.
Article
Multidisciplinary Sciences
V. S. Devi Priya, S. Sibi Chakkaravarthy
Summary: Discovering malicious packets in normal network activity can be challenging and time-consuming. The use of IDS or machine and device log analysis can aid in this task. A comprehensive deployment of research honeypot detectors has been employed to analyze and evaluate hackers' behavior. This paper presents a robust outline of containerized honeypot deployment, which offers portability, durability, and simplicity.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Muhammad Hassan Nasir, Junaid Arshad, Muhammad Mubashir Khan
Summary: The increase in cyber attacks on the Internet of Things (IoT) is primarily due to the widespread adoption of IoT in various infrastructures and the security vulnerabilities within IoT endpoints. Botnets have emerged as a major threat, assembling compromised devices to launch cyber attacks. This paper presents efforts to develop an intrusion detection system within IoT devices for enhanced security. The system uses a signature-based detection scheme and has been evaluated for effectiveness in detecting anomalous traffic in resource-constrained IoT networks.
COMPUTERS & SECURITY
(2023)
Review
Computer Science, Artificial Intelligence
Ayoub Si-Ahmed, Mohammed Ali Al-Garadi, Narhimene Boustia
Summary: The Internet of Medical Things (IoMT) has revolutionized the healthcare industry by enabling physiological data collection using sensors and transmitting them for analysis. It offers benefits like early disease detection and automatic medication, but also presents security risks like patient privacy violations. Therefore, adopting robust security measures is crucial to ensure data integrity and confidentiality.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Information Systems
Akbar Telikani, Amir H. Gandomi
Summary: This study proposes a cost-sensitive stacked auto-encoder for addressing the class imbalance problem in IDS. The method can better learn the distinctions between minority and majority classes, improve the performance of IDS, and show better detection of low-frequency attacks.
INTERNET OF THINGS
(2021)
Review
Computer Science, Information Systems
Arash Heidari, Mohammad Ali Jabraeil Jamali
Summary: The security of IoT involves not only network and data security but also human health and life attacks. The integration of Intrusion Detection System (IDS) with IoT systems is important for protecting system security.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Toaha Raza Khan, Malik Muhammad Saad, Muhammad Ashar Tariq, Junaid Akram, Dongkyun Kim
Summary: The Internet of things (IoT) application in e-health plays a vital role in managing health emergencies and disease control, requiring monitoring of the population's compliance in disease-prone areas. Challenges include issues such as information transmission delays and network congestion.
INFORMATION FUSION
(2021)
Article
Computer Science, Information Systems
Yu Yang, Yuheng Gu, Yu Yan
Summary: This paper proposes a geometric synthetic minority oversampling technique based on the optimized kernel density estimation algorithm to generate diverse rare-class attack data. A multi-module intrusion detection system is constructed to improve the detection performance for unknown attacks and rare classes of attack traffic.
