• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.367-373
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• 2022

VANET (Vehicular Ad hoc NETwork) is one of the special cases of the ad hoc networks in which car nodes communicate with each other and/or with RSUs (Road Side Unit) in order for the drivers to receive nearby road traffic information as well as for the passengers to retrieve nearby gas price or hotel information. In case of constructing VANET over CCN, users do not need to specify a destination server address rather to input a key word such as nearby congestion in order to gather surrounding traffic congestion information. Furthermore, each car node caches its retrieved data for forwarding other nodes when requested. In addition, the data transmission is inherently multicast, which implies fast data propagation to the participating car nodes. This paper measures and evaluates the data transmission performance of the VCCN (VANET over CCN) in which nodes are equipped with diverse wireless communication channels. The simulation result indicates that 802.11a shows the best performance of the data transmission against other wireless channels. Moreover, it indicates that VCCN improves overall data transmission and provides benefit to the nodes that request the same traffic information by exploiting inherent multicast communication.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.725-730
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• 2022

Named Data Networking (NDN) is a representative technology of ICN that realizes the future Internet architecture. NDN searches for data by its content and not by its host IP address. The consumer generates an interest packet and sends it to the NDN network. The NDN network uses three tables such as CS, FIB, and PIT and forwards the received interest packet to the next hop. The producer transmits the data packet to the consumer through a name-based forwarding scheme. In this paper, we design and implement an ndnSIM-based NDN network and perform performance evaluation. We analyze the ndnSIM structure and develop a 6-node congested NDN network and a 9-node grid NDN network using ndnSIM. In the simulation, the performance of latency and throughput of the interest packet rate are measured. We analyze the effect of congestion on the latency and throughput of the NDN network. This approach will help researchers in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.1-7
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• 2022

As the number of IoT devices increases, power management of the cluster head, which acts as a gateway between the cluster and sink nodes in the IoT network, becomes crucial. Particularly when the cluster head is a mobile wireless terminal, the power consumption of the IoT network must be minimized over its lifetime. In addition, the delay of information transmission in the IoT network is one of the primary metrics for rapid information collecting in the IoT network. In this paper, we propose a low-power buffer management algorithm that takes into account the information transmission delay in an IoT network. By forwarding or skipping received packets utilizing deep Q learning employed in deep reinforcement learning methods, the suggested method is able to reduce power consumption while decreasing transmission delay level. The proposed approach is demonstrated to reduce power consumption and to improve delay relative to the existing buffer management technique used as a comparison in slotted ALOHA protocol.

• KNOM Review
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• v.23 no.2
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• pp.1-10
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• 2020

Network Function Virtualization (NFV) is a key technology of 5G networks that has the advantage of enabling building and operating networks flexibly. However, NFV can complicate network management because it creates numerous virtual resources that should be managed. In NFV environments, service function chaining (SFC) composed of virtual network functions (VNFs) is widely used to apply a series of network functions to traffic. Therefore, it is required to dynamically allocate the right amount of computing resources or instances to SFC for meeting service requirements. In this paper, we propose Deep Q-Networks (DQN)-based auto-scaling to operate the appropriate number of VNF instances in SFC. The proposed approach not only resizes the number of VNF instances in SFC composed of multi-tier architecture but also selects a tier to be scaled in response to dynamic traffic forwarding through SFC.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.113-120
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• 2022

In this paper, we analyze the feasibility of the IP spoofing attack exploiting null security algorithms in 5G networks based on 3GPP standard specifications. According to 3GPP standard specifications, the initial Registration Request message is not protected by encryption and integrity. The IP spoofing attack exploits the vulnerability that allows a malicious gNB (next generation Node B) to modify the contents of the initial Registration Request message of a victim UE (User Equipment) before forwarding it to AMF (Access and Mobility Management Function). If the attack succeeds, the victim UE is disconnected from the 5G network and a malicious UE gets Internet services, while the 5G operator will charge the victim UE. In this paper, we analyze the feasibility of the IP spoofing attack by analyzing whether each signaling message composing the attack conforms to the 3GPP Rel-17 standard specifications. As a result of the analysis, it is determined that the IP spoofing attack is not feasible in the 5G system implemented according to the 3GPP Rel-17 standard specifications.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.109-117
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• 2009

In this paper, we propose an efficient service discovery scheme that combines peer-to-peer caching advertisement and node ID-based selective forwarding service requests. P2P caching advertisement quickly spreads available service information and reduces average response hop count since service information store in neighbor node cache. In addition, node ID-based service requests can minimize network transmission delay and can reduce network load since do not broadcast to all neighbor node. Proposed scheme does not require a central lookup server or registry and not rely on flooding that create a number of transmission messages. Simulation results show that proposed scheme improved network loads and response times since reduce a lot of messages and reduce average response hop counts using adaptive selective nodes among neighbor nodes compared to traditional flooding-based protocol.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.91-96
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• 2009

In this paper, interoperability in heterogeneous wireless mesh network, and mesh nodes for providing efficient IP mobility technique offers multi-hop ARP. Heterogeneous wireless mesh networks to MANETs based on a wireless mesh network backbone and non-MANET architecture is based on a client wireless mesh network and the two mobile networks, combined with a hybrid wireless mesh network are separate. In two different hybrid wireless mesh network routing protocols used to connect the two protocols in the protocol conversion at the gateway to parallel processing problems seriously overload occurs. All of the network reliability and stability are factors that reduce. Therefore, for efficient integration with L3 routing protocols, design techniques to build ARP multi-hop go through the experiment to increase the number of mesh nodes, the packet forwarding rate and an increased hop number of the node was to ensure reliability and stability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.171-178
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• 2023

In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1087-1098
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• 2023

The rapid advancement of artificial intelligence (AI) technology has led to its proactive utilization across various fields. However, this widespread adoption of AI-based systems has raised concerns about the increasing threat of attacks on these systems. In particular, deep neural networks, commonly used in deep learning, have been found vulnerable to adversarial attacks that intentionally manipulate input data to induce model errors. In this study, we propose a method to protect image classification models from visually imperceptible One-Pixel attacks, where only a single pixel is altered in an image. The proposed defense technique utilizes an autoencoder model to remove potential threat elements from input images before forwarding them to the classification model. Experimental results, using the CIFAR-10 dataset, demonstrate that the autoencoder-based defense approach significantly improves the robustness of pretrained image classification models against One-Pixel attacks, with an average defense rate enhancement of 81.2%, all without the need for modifications to the existing models.