• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4080-4097
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• 2020

In recent years, convolutional neural network (CNN) has become the primary method for face detection. But its shortcomings are obvious, such as expensive calculation, heavy model, etc. This makes CNN difficult to use on the mobile devices which have limited computing and storage capabilities. Therefore, the design of lightweight CNN for face detection is becoming more and more important with the popularity of smartphones and mobile Internet. Based on the CPU real-time face detector FaceBoxes, we propose a multi-task lightweight face detector, which has low computing cost and higher detection precision. First, to improve the detection capability, the squeeze and excitation modules are used to extract attention between channels. Then, the textual and semantic information are extracted by shallow networks and deep networks respectively to get rich features. Finally, the landmark detection module is used to improve the detection performance for small faces and provide landmark data for face alignment. Experiments on AFW, FDDB, PASCAL, and WIDER FACE datasets show that our algorithm has achieved significant improvement in the mean average precision. Especially, on the WIDER FACE hard validation set, our algorithm outperforms the mean average precision of FaceBoxes by 7.2%. For VGA-resolution images, the running speed of our algorithm can reach 23FPS on a CPU device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.914-934
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• 2016

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way. This paper improves the outstanding Certified Reputation (CR) model and proposes a Lightweight Cross-domain Trust (LCT) model for the mobile distributed environment in a fully distributed way. The trust certifications, in which the trust ratings contain various trust aspects with different interest preference weights, are collected and provided by the trustees. Furthermore, three factors are comprehensively considered to ease the issue of collusion attacks and make the trust certifications more accurate. Finally, a cross-domain scenario is deployed and implemented, and the comprehensive experiments and analysis are conducted. The results demonstrate that our LCT model obviously outperforms the Bayesian Network (BN) model and the CR model in our cross-domain scenario, and significantly improves the successful interaction rates of the honest entities without increasing the risks of interacting with the malicious entities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4006-4024
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• 2017

Internet of Things (IoT) will transform our daily life by making different aspects of life smart like smart home, smart workplace, smart health and smart city etc. IoT is based on network of physical objects equipped with sensors and actuators that can gather and share data with other objects or humans. Secure communication is required for successful working of IoT. In this paper, a total of 13 lightweight cryptographic algorithms are evaluated based on their implementation results on 8-bit, 16-bit, and 32-bit microcontrollers and their appropriateness is examined for resource-constrained scenarios like IoT. These algorithms are analysed by dissecting them into their logical and structural elements. This paper tries to investigate the relationships between the structural elements of an algorithm and its performance. Association rule mining is used to find association patterns among the constituent elements of the selected ciphers and their performance. Interesting results are found on the type of element used to improve the cipher in terms of code size, RAM requirement and execution time. This paper will serve as a guideline for cryptographic designers to design improved ciphers for resource constrained environments like IoT.

• Advances in nano research
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• v.13 no.5
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• pp.499-512
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• 2022

This study investigates the efficiency of ensemble machine learning for predicting the lightweight-aggregate concrete (LWC) characteristics. A stacking ensemble (STEN) approach was proposed to estimate the dry density (DD) and 28 days compressive strength (Fc-28) of LWC using two meta-models called random forest regressor (RFR) and extra tree regressor (ETR), and two novel ensemble models called STEN-RFR and STEN-ETR, were constructed. Four standalone machine learning models including artificial neural network, gradient boosting regression, K neighbor regression, and support vector regression were used to compare the performance of the proposed models. For this purpose, a sum of 140 LWC mixtures with 21 influencing parameters for producing LWC with a density less than 1000 kg/m³, were used. Based on the experimental results with multiple performance criteria, it can be concluded that the proposed STEN-ETR model can be used to estimate the DD and Fc-28 of LWC. Moreover, the STEN-ETR approach was found to be a significant technique in prediction DD and Fc-28 of LWC with minimal prediction error. In the validation phase, the accuracy of the proposed STEN-ETR model in predicting DD and Fc-28 was found to be 96.79% and 81.50%, respectively. In addition, the significance of cement, water-cement ratio, silica fume, and aggregate with expanded glass variables is efficient in modeling DD and Fc-28 of LWC.

• The KIPS Transactions:PartC
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• v.10C no.2
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• pp.199-208
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• 2003

LDAP (Lightweight Directory Access Protocol) Directory Service provides information for locating resources like files and devices over the network such as Internet or Intranet. Since LDAP is widely accepted as one of the standard directory service structure for the Internet, it is desirable that a group of LDAP servers works transparently and continuously even if the related network partitions temporally, through maintaining replicated directory information among those LDAP servers. In this paper, we describe the design and implementation of a robust LDAP sewer, which runs as a process group in JACE group communication system, and the associated LDAP service provider which enables Java applications to use the developed LDAP directory service.

• Journal of KIISE:Information Networking
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• v.34 no.3
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• pp.175-185
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• 2007

In IEEE 802.15.4 (Low-Rate Wireless Personal Area Network) specification, a successful reception and validation of a data or MAC command frame can be confirmed with an acknowledgment. However, the specification does not support security for acknowledgment frame; the lack of a MAC covering acknowledgments allows an adversary to forge an acknowledgment for any frame. This paper proposes an identity authentication mechanism at the link layer for acknowledgment frame in IEEE 802.15.4 network. With the proposed mechanism there is only three bits for authentication, which can greatly reduce overhead of device. The encrypted bit stream for identity authentication will be transmitted to device by coordinator within association process. Statistical method and simulation results prove that our mechanism is successful in handling MAC layer attack.

• Journal of IKEEE
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• v.27 no.4
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• pp.531-536
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• 2023

This paper proposes a sliding window method with frame feature insertion for immediate attack detection on in-vehicle networks. This method guarantees real-time attack detection by labeling based on the attack status of the current frame. Experiments show that the proposed method improves detection performance by giving more weight to the current frame in CNN computation. The proposed model was designed based on a lightweight LeNet-5 architecture and it achieves 100% detection for DoS attacks. Additionally, by comparing the complexity with conventional models, the proposed model has been proven to be more suitable for resource-constrained devices like ECUs.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.683-688
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• 2011

The wireless sensor network (WSN) is well known for an enabling technology for the ubiquitous environment such as real-time surveillance system, habitat monitoring, home automation and healthcare applications. However, the WSN featuring wireless communication through air, a resource constraints device and irregular network topology, is threatened by malicious nodes such as eavesdropping, forgery, illegal modification or denial of services. For this reason, security in the WSN is key factor for utilizing the sensor network into the commercial way. There is a series of symmetric cryptography proposed by laboratory or industry for a long time. Among of them, recently proposed HUMMINGBIRD algorithm, motivated by the design of the well-known Enigma machine, is much more suitable to resource constrained devices, including smart card, sensor node and RFID tags in terms of computational complexity and block size. It also provides resistance to the most common attacks such as linear and differential cryptanalysis. In this paper, we implements ultra-lightweight cryptography, HUMMINGBIRD algorithm into the resource constrained device, sensor node as a perfectly customized design of sensor node.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.91-98
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• 2020

The mobile agent, which handles a given task while migrating between the sensor nodes, moves including the execution commands and task processing results. This increases the size of the mobile agent, causing the network to load, leading to the migration time delay and the loss of migration reliability. This paper presents the method of lightening the mobile agent using distributed object technology and the algorithm for exploring and providing the optimal migration path that is actively performed in the event of network traffic, and it proposes a method to ensure the reliability of the mobile agent migration by applying them. In addition, through the comparative analysis experiments based on agent size and network traffic for the migration time of mobile agent equipped with active rules in sensor network-based mobile agent middleware environment, applying the proposed methods proves to ensure the autonomy and migration reliability of the mobile agent.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.465-476
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• 2005

The wireless sensor network consists of a number of sensor nodes which have physical constraints. Each sensor node senses surrounding environments and sends the sensed information to Sink. In order to alleviate the inherent vulnerability in security of the wireless sensor nodes with the hardware constraints, the lightweight security protocol is needed and a variety of research is ongoing. In this paper, we propose a non-hierarchical sensor network and a security protocol that is suitable for monitoring man-made objects such as bridges. This paper, furthermore, explores a two-layer authentication, key distribution scheme which distributes the key and location of a sensor node in advance, and an effective security routing protocol which can take advantage of the Sleep and Awake state. This also results in the increased data transfer rate by increasing the number of alternative routing paths and the reduced energy consumption rate.