• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• Convergence Security Journal
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• v.17 no.5
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• pp.93-99
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• 2017

Recently IoT(Internet of Things) service industry has grown very rapidly. In this paper, we investigated the changes in IoT service industry as well as new direction of human life in future global society. Under these changing market conditions, competition has been also changed into global and ecological competition. But compared to the platform initiatives and ecological strategies of global companies, Korean companies' vision of building ecosystems is still unclear. In addition, there is a need of internetworking between mobile and IoT services. IoT security Protocol has weakness of leaking out information from Gateway which connected wire and wireless communication. As such, we investigate the structure of IoT and AI service ecosystem in order to gain strategic implications and insights for the security industry in this paper.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.174-178
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• 2024

IoT is collection of different "things" which are associated with open web. As all the things are connected to the Internet, it offers convenience to end users for accessing the resources from "Any Where, Any Time" throughout the globe. At the same time, open nature of IoT provides a fertile ground to an intruder for launching different security related threats. If we can no apply proper security safeguards to the IoT System, then it will be not useful to society. Authentication, Encryption, Trust Management and Secure Routing are different domains to offer security in IoT system. Among them, Authentication is very much important security service as it validates device identity before granting access to system services/ resources. Existing IoT Authentication algorithms are fail to verify device identity in unambiguous way. They are vulnerable to different security threats such as Key Stolen threat, MITM threat and Location Spoofing threat. So, it is a demand of time to design an efficient and secure Multi-factor IoT algorithm which can offer better security and validate device identity in unambiguous way.

• Journal of Internet of Things and Convergence
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• v.2 no.1
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• pp.17-21
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• 2016

The rapid development of IoT leads new kinds of services which does not existed. And, it requires several changes on existing network. Software Defined Network is one of the future network technology which can deal with problems from these kinds of changes. The strong point of Software Defined Network is flexibility and scalability. However, In some cases, these factors could be the security vulnerabilities. In this paper, we present adaptation of F(I)MEA technique for the security analysis on Software Defined Network Technology for IoT services.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.4
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• pp.667-674
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• 2015

Internet of things (IoT) has been a focus of research and widespread. Security and privacy are the key issues for IoT applications, and still faced with some enormous challenges. In order to facilitate this emerging domain, we analyzed the research progress of IoT, and pay attention to the security. By means of deeply analyzing the security architecture and features, the security requirements are required. And, we surveyed the demands and requirements.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.250-258
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• 2022

The emerging scope of the Internet-of-Things (IoT) has piqued the interest of industry and academia in recent times. Therefore, security becomes the main issue to prevent the possibility of cyberattacks. Jamming attacks are threads that can affect performance and cause significant problems for IoT device. This study explores a smart jamming attack (coalition attack) in which the attackers were previously a part of the legitimate network and are now back to attack it based on the gained knowledge. These attackers regroup into a coalition and begin exchanging information about the legitimate network to launch attacks based on the gained knowledge. Our system enables jammer nodes to select the optimal transmission rates for attacks based on the attack probability table, which contains the most probable link transmission rate between nodes in the legitimate network. The table is updated constantly throughout the life cycle of the coalition. The simulation results show that a coalition of jammers can cause highly successful attacks.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.103-114
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• 2022

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1986-2009
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• 2024

The integration of blockchain technology with the rapid growth of Internet of Things (IoT) devices has enabled secure and decentralised data exchange. However, security vulnerabilities and performance limitations remain significant challenges in IoT blockchain networks. This work proposes a novel approach that combines transaction representation and machine learning techniques to address these challenges. Various clustering techniques, including k-means, DBSCAN, Gaussian Mixture Models (GMM), and Hierarchical clustering, were employed to effectively group unlabelled transaction data based on their intrinsic characteristics. Anomaly transaction prediction models based on classifiers were then developed using the labelled data. Performance metrics such as accuracy, precision, recall, and F1-measure were used to identify the minority class representing specious transactions or security threats. The classifiers were also evaluated on their performance using balanced and unbalanced data. Compared to unbalanced data, balanced data resulted in an overall average improvement of approximately 15.85% in accuracy, 88.76% in precision, 60% in recall, and 74.36% in F1-score. This demonstrates the effectiveness of each classifier as a robust classifier with consistently better predictive performance across various evaluation metrics. Moreover, the k-means and GMM clustering techniques outperformed other techniques in identifying security threats, underscoring the importance of appropriate feature selection and clustering methods. The findings have practical implications for reinforcing security and efficiency in real-world IoT blockchain networks, paving the way for future investigations and advancements.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.955-963
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• 2022

The Internet of Things (IoT), combined with various technologies, is rapidly becoming an integral part of our daily life. While it is rapidly taking root in society, security considerations are relatively insufficient, making it a major target for cyber attacks. Since all devices in the IoT environment are connected to the Internet and are closely used in daily life, the damage caused by cyber attacks is also serious. Therefore, encryption communication using a network security protocol must be considered for a service in a more secure IoT environment. A representative network security protocol includes TLS (Transport Layer Protocol) defined by the IETF. This paper analyzes the performance measurement results for TLS version 1.2 and version 1.3 in an IoT device open platform environment to predict the load of TLS, a representative network security protocol, in IoT devices with limited resource characteristics. In addition, by analyzing the performance of each major cryptographic algorithm in version 1.3, we intend to present a standard for setting appropriate network security protocol properties according to IoT device specifications.

• Convergence Security Journal
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• v.22 no.4
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• pp.99-107
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• 2022

The use of smart home appliances and Internet of Things (IoT) devices is growing, enabling new interactions and automation in the home. This technology relies heavily on mobile services which leaves it vulnerable to the increasing threat of hacking, identity theft, information leakage, serious infringement of personal privacy, abnormal access, and erroneous operation. Confirming or proving such security breaches have occurred is also currently insufficient. Furthermore, due to the restricted nature of IoT devices, such as their specifications and operating environments, it is difficult to provide the same level of internet security as personal computers. Therefore, to increase the security on smart home IoT devices, attention is needed on (1) preventing hacking and user authority theft; (2) disabling abnormal manipulation; and (3) strengthening audit records for device operation. In response to this, we present a plan to build a cloud security authentication platform which features security authentication management functionality between mobile terminals and IoT devices.