• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.537-547
• /
• 2023

As Internet of Things (IoT) technology evolves, IoT devices are being utilized in a variety of fields. However, it has become a new surface of cyber attacks and is affecting industries that did not previously consider cyber breaches. After a intrusion occurs, post-processing and damage spread prevention are important, but it is difficult to respond due to the lackof standards and guidelines. Therefore, in order to respond to such incidents, this paper establishes an incident data collection procedure and presents the data that can be collected to improve the intrusion data acquisition method for general IoT devices. In addition, we proved the efficiency and feasibility of the data collection procedure through experiments.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.8
• /
• pp.73-79
• /
• 2020

Since the start of the 4th industrial revolution, technologies have been developed in the Internet of Things (IoT), artificial intelligence (AI), virtual reality (VR), and 5G. Compared to other technologies IoT is currently being commercialized more than other technologies where the numbers of connected things are increases every year. The IoT has a huge advantage to provide convenience and lots of information to users, but security cannot keep up with the speed of development. IoT services continue to provide services for related devices, but at present, more and more types of new services are being combined with other technologies by utilizing the services of devices. This paper reviews and analyzes research on security issues and services related to the Internet of Things to explore how security trends and service delivery will develop in the future.

• The Journal of Bigdata
• /
• v.8 no.2
• /
• pp.141-148
• /
• 2023

Recent advancements in the integration of satellite technology and the Internet of Things (IoT) have led to the development of a sophisticated network ecosystem, capable of generating and utilizing vast amounts of big data across various sectors. However, this integrated network faces significant security challenges, primarily due to constraints like limited latency, low power requirements, and the incorporation of diverse heterogeneous devices. Addressing these security concerns, this paper explores the construction of a satellite-IoT network through the application of Software Defined Networking (SDN). While SDN offers numerous benefits, it also inherits certain inherent security vulnerabilities. To mitigate these issues, we propose a novel approach that incorporates blockchain technology within the SDN framework. This blockchain-based SDN environment enhances security through a distributed controller system, which also facilitates the authentication of IoT terminals and nodes. Our paper details the implementation plan for this system and discusses its validation through a series of tests. Looking forward, we aim to expand our research to include the convergence of artificial intelligence with satellite-IoT devices, exploring new avenues for leveraging the potential of big data in this context.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.53-58
• /
• 2024

The Internet of Things (IoT) enables the connection of millions of disparate devices to the World Wide Web. To perform the task, a lot of smart gadgets must work together. The gadgets recognize other devices as part of their network service. Keeping participating devices safe is a crucial component of the internet of things. When gadgets communicate with one another, they require a promise of confidence. Trust provides certainty that the gadgets or objects will function as expected. Trust management is more difficult than security management. This review includes a thorough examination of trust management in a variety of situations.

• The Journal of the Convergence on Culture Technology
• /
• v.2 no.4
• /
• pp.77-82
• /
• 2016

IoT technology was selected as one of IT 10 strategic technologies by gartner from 2013 to 2015, and implements advanced smart society while enabling interaction between people and things. Because IoT devices are connected to the Internet, they are involved in issues including exposure of private lives, for example, hacking to result in wireless signal interference, data theft, data modification and forgery and service denial, and critical security issues including threat to national confidential information and facilities. This study aims to suggest a method for examining threats to security through IP exposure of IoT devices and examining related problems to minimize threats to security through IP exposure including exposure of private lives or damages to the national infrastructure system.

• Journal of Internet of Things and Convergence
• /
• v.7 no.3
• /
• pp.1-8
• /
• 2021

With the rapid increase in the use of IoT and mobile devices, cyber criminals targeting IoT devices are also on the rise. Among IoT devices, when using a wireless access point (AP), problems such as packets being exposed to the outside due to their own security vulnerabilities or easily infected with malicious codes such as bots, causing DDoS attack traffic, are being discovered. Therefore, in this study, in order to actively respond to cyber attacks targeting IoT devices that are rapidly increasing in recent years, we proposed a method to collect traces of intrusion incidents artifacts from IoT devices, and to improve the validity of intrusion analysis data. Specifically, we presented a method to acquire and analyze digital forensics artifacts in the compromised system after identifying the causes of vulnerabilities by reproducing the behavior of the sample IoT malware. Accordingly, it is expected that it will be possible to establish a system that can efficiently detect intrusion incidents on targeting large-scale IoT devices.

• International Journal of Computer Science & Network Security
• /
• v.21 no.7
• /
• pp.331-340
• /
• 2021

The Internet of Things (IoT) is a rapidly growing physical network that depends on objects, vehicles, sensors, and smart devices. IoT has recently become an important research topic as it autonomously acquires, integrates, communicates, and shares data directly across each other. The centralized architecture of IoT makes it complex to concurrently access control them and presents a new set of technological limitations when trying to manage them globally. This paper proposes a new decentralized access control architecture to manage IoT devices using blockchain, that proposes a solution to concurrency management problems and enhances resource locking to reduce the transaction conflict and avoids deadlock problems. In addition, the proposed algorithm improves performance using a fully distributed access control system for IoT based on blockchain technology. Finally, a performance comparison is provided between the proposed solution and the existing access management solutions in IoT. Deadlock detection is evaluated with the latency of requesting in order to examine various configurations of our solution for increasing scalability. The main goal of the proposed solution is concurrency problem avoidance in decentralized access control management for IoT devices.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.163-172
• /
• 2022

The interconnection of an enormous number of devices into the Internet at a massive scale is a consequence of the Internet of Things (IoT). As a result, tasks offloading from these IoT devices to remote cloud data centers become expensive and inefficient as their number and amount of its emitted data increase exponentially. It is also a challenge to optimize IoT device energy consumption while meeting its application time deadline and data delivery constraints. Consequently, Fog Computing was proposed to support efficient IoT tasks processing as it has a feature of lower service delay, being adjacent to IoT nodes. However, cloud task offloading is still performed frequently as Fog computing has less resources compared to remote cloud. Thus, optimized schemes are required to correctly characterize and distribute IoT devices tasks offloading in a hybrid IoT, Fog, and cloud paradigm. In this paper, we present a detailed survey and classification of of recently published research articles that address the energy efficiency of task offloading schemes in IoT-Fog-Cloud paradigm. Moreover, we also developed a taxonomy for the classification of these schemes and provided a comparative study of different schemes: by identifying achieved advantage and disadvantage of each scheme, as well its related drawbacks and limitations. Moreover, we also state open research issues in the development of energy efficient, scalable, optimized task offloading schemes for Fog computing.

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

• International Journal of Computer Science & Network Security
• /
• v.22 no.4
• /
• pp.89-100
• /
• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.