• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.5
• /
• pp.1310-1338
• /
• 2023

As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3- layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.11
• /
• pp.5276-5298
• /
• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Journal of Industrial Convergence
• /
• v.18 no.2
• /
• pp.69-75
• /
• 2020

Industrial IoT has much interested in wireless mesh networks (WMNs) due to cost effectiveness and coverage. According to the advance in caching technology, WMNs have been researched to overcome the throughput degradation of multihop environment. However, there is few researches of cache power consumption models for WMNs. In particular, a wired line based cache power consumption model in content-centric networks is not still proper to WMNs. In this paper, we split the amount of cache power from the idle power consumption of CPU, and then the cache hit ratio proportional power consumption model (CHR-model) is proposed. The proposed CHR-model provides more accurate power consumption in WMNs, compared with the conventional cache power efficiency based consumption model (CPE-model). The proposed CHR-model can provide a reference model to improve energy-efficient cache operation for Industrial IoT.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.12
• /
• pp.2450-2460
• /
• 2015

Recently, as interest in IoT (Internet of Things) increase, research and standardization of a new protocol which reflects the characteristics of IoT has progressed. Among them, RPL(IPv6 for Low-Power Lossy Network) is a standardized routing protocol for IoT. RPL utilizes DIO (DODAG Information Object) messages which is flooded from the sink node to the whole network for path establish and maintenance. However, in large scale networks, not only a long time is required to propagate the DIO message to the whole networks but also a bottleneck effect around the sink node is occurred. Multi-sink based approaches which take advantage of reducing routing overhead and bottleneck effect are widely used to solve these problems. In this paper, we define 'unnecessary path update problems' that may arise when applying the RPL protocol to the multi sink based IoT networks and propose two methods namely Routing Metric based Path Update Decision method and Immediate Successor based Path Update Decision method for selective routing update.

• International Journal of Computer Science & Network Security
• /
• v.24 no.4
• /
• pp.170-178
• /
• 2024

Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.

• Journal of Advanced Navigation Technology
• /
• v.26 no.6
• /
• pp.481-486
• /
• 2022

The recent rapid growth of the IoT(Internet of Things) is leading to the spread of low-power wireless technology. A major challenge in designing IoT wireless networks is to achieve coexistence between different wireless technologies that share the 2.4 [GHz] ISM (Industrial Scientific Medical) frequency band. Therefore, there is a need for research on improving the reliability of wireless networks and coexisting operation between wireless networks. In particular, it is necessary to study an interference model and performance for mutual service coexistence in a BLE (Bluetooth Low Energy) wireless network environment, which is expected to be widely used as a connection medium between devices in various industrial fields. In this paper, the co-channel interference model with the IEEE 802.15.4 system is established focusing on the physical layer of the BLE system widely used in residential and industrial wireless applications, and the performance of the BLE wireless communication system is analyzed in the co-channel interference environment. As a result of the analysis, as the distance between the interference source and the BLE system increases in an environment where noise and co-channel interference exist, the amount of co-channel interference decreases and the error rate performance of the BLE system improves.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.168-176
• /
• 2023

The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous security challenges as sensitive information is prone to be exposed to malicious users. In this paper, IoT based-security issues ontology is proposed to collect, examine, analyze, prepare, acquire and preserve evidence of IoT security issues challenges. Ontology development has consists three main steps, 1) domain, purpose and scope setting, 2) important terms acquisition, classes and class hierarchy conceptualization and 3) instances creation. Ontology congruent to this paper is method that will help to better understanding and defining terms of IoT based-security issue ontology. Our proposed IoT based-security issue ontology resulting from the protégé has a total of 44 classes and 43 subclasses.

• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.9-17
• /
• 2023

Recently, IoT technology has been widely used in many industries. Also research on integrating IoT technology with IoT sensors is actively underway. One of the important challenges in IoT is to support low-latency communication. With the development of communication networks and protocols, a variety of protocols are being used, and their performance is improving. In this paper, we compare the performance and analyze the characteristics of some of the major communication protocols in IoT application, namely MQTT, HTTP, and HTTPS. IoT sensors acquired data by connecting an Arduino equipped with ESP8266 and a temperature and humidity sensor (DHT11). The server measured the performance by building servers for each protocol using AWS EC2. We analyzed the packets transmitted between the Arduino and the server during the data transmission. We measured the amount of data and transfer time. The measurement results showed that MQTT had the lowest data transmission time and data amount among the three protocols.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.1
• /
• pp.17-26
• /
• 2016

IoT means things space networks that form the intelligent relationship such as sensing, networking, information processing about human being, things and service without explicit mutual cooperation of human being. Lately many IoT groups such as AllSeen Alliance, OIC launched a platform for IoT. Self-adaptive is aimed at implementation without the need for decisions of human being during the operation, so that the machine can respond to changes in its own determination. There is a need to apply the concept of self-adaptive to existing IoT and IoT platform. So In this paper, We look for trends of existing IoT, IoT platform and comparisons by applying a self-adaptive concept to IoT, IoT platform. In addition as an example of this paper, we suggest lacking self-adaptive elements to OIC.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.459-469
• /
• 2023

The number of IoT devices is explosively increasing due to the development of embedded equipment and computer networks. As a result, cyber threats to IoT are increasing, and currently, malicious codes are being distributed and infected to IoT devices and exploited for DDoS. Currently, IoT devices that are the target of such an attack have various installation environments and have limited resources. In addition, IoT devices have a characteristic that once set up, the owner does not care about management. Because of this, IoT devices are becoming a blind spot for management that is easily infected with malicious codes. Because of these difficulties, the threat of malicious codes always exists in IoT devices, and when they are infected, responses are not properly made. In this paper, we will design an malware detection system for IoT in consideration of the characteristics of the IoT environment and present detection rules suitable for use in the system. Using this system, it will be possible to construct an IoT malware detection system inexpensively and efficiently without changing the structure of IoT devices that are already installed and exposed to cyber threats.