• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1247-1260
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• 2021

For more efficient energy management of nodes in wireless sensor networks, research has been conducted on mobile sink nodes that deliver data from sensor nodes to server recently. UAV (Unmanned Aerial vehicle) is used as a representative mobile sink node. Also, most studies on UAV propose algorithms for calculating optimal paths and have produced rapid advances in the IoD (Internet of Drones) environment. At the same time, some papers proposed mutual authentication and secure key exchange considering nature of the IoD, which requires efficient creation of multiple nodes and session keys in security perspective. However, most papers that proposed secure communication in mobile sink nodes did not protect end-to-end data privacy. Therefore, in this paper, we propose integrated security model that authentication between mobile sink nodes and sensor nodes to securely relay sensor data to base stations. Also, we show informal security analysis that our scheme is secure from various known attacks. Finally, we compare communication overhead with other key exchange schemes previously proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Smart Media Journal
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• v.11 no.11
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• pp.75-83
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• 2022

NIST in the United States has developed SCAP, a protocol that enables automated inspection and management of security vulnerability using existing standards such as CVE and CPE. SCAP operates by creating a checklist using the XCCDF and OVAL languages and running the prepared checklist with the SCAP tool such as the SCAP Workbench made by OpenSCAP to return the check result. SCAP checklist files for various operating systems are shared through the NCP community, and the checklist files include ID, title, description, and inspection method for each item. However, since the inspection items are simply listed in the order in which they are written, so it is necessary to classify and manage the items by type so that the security manager can systematically manage them using the SCAP checklist file. In this study, we propose a method of extracting the description of each inspection item from the SCAP checklist file written in OVAL language, classifying the categories through a machine learning model, and outputting the SCAP check results for each classified item.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.2
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• pp.81-88
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• 2016

Machine-to-Machine (M2M) communication provides each component (machine) with access to Internet, evolving into the IoT technology. IoT is a trend where numbers of devices provide the communication service, using the Internet protocol. As spreading the concept of IoT(Internet of Things), various objects become home information sources. According to the wide spread of various devices, it is difficult to access data on the devices with unified manners. Under this environment, security is a critical element to create various types of application and service. In this paper propose the inter-device authentication and Centralized Remote Security Provisioning framework in Open M2M environment. The results of previous studies in this task is carried out by protecting it with the latest information on M2M / IoT and designed to provide the ultimate goal of future M2M / IoT optimized platform that can be integrated M2M / IoT service security and security model presents the information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.505-507
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• 2021

In a Wireless Sensor Network (WSN), the wireless data transmission environment plays an important role in system performance. In the proposed mobility model moving distance of sensor nodes has a great influences on communication performance. Transmission/receiving distance (d), path loss (L), sensitivity, Bit Error Rate (BER), Signal-to-Noise Ratio (SNR) are considerations when designing a wireless communication system. MANET is a form of network in which only wireless terminals communicate with each other independently and move without any assistance of an existing infrastructure network. This paper is research on the optimized power usage method which is study on the effect of the moving distance of mobile nodes on the overall energy efficiency of the system in WSN. The purpose of this study is to extend the life of the entire network by proposing the mobile distance of sensor nodes within the communication available range.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.131-135
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• 2024

In the MQTT protocol, if the retained flag of a message published by a publisher is set, the message is stored in the broker as a retained message. When a new subscriber performs a subscribe, the broker immediately sends the retained message. This allows the new subscriber to perform updates on the current state via the retained message without waiting for new messages from the publisher. However, sending retained messages can become a traffic overhead if new messages are frequently published by the publisher. This situation could be considered an overhead when new subscribers frequently subscribe. Therefore, in this paper, we propose a retained message delivery scheme by considering the characteristics of the published messages. We model the delivery and waiting actions to new subscribers from the perspective of the broker using reinforcement learning, and determine the optimal policy through Q learning algorithm. Through performance analysis, we confirm that the proposed method shows improved performance compared to existing methods.

• Journal of Periodontal and Implant Science
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• v.54 no.1
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• pp.25-36
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• 2024

Purpose: Mucogingival defects (MGDs), such as dental root recessions, decreased vestibular depth, and absence of keratinized tissues, are commonly seen in dental clinics. MGDs may result in functional, aesthetic, and hygienic concerns. In these situations, autogenous soft tissue grafts are considered the gold-standard treatment. This study compares the healing process of free gingival grafts (FGGs) to bacterial cellulose matrix (BCM) and human acellular dermal matrix (ADM) seeded with fibroblasts from culture supplemented with platelet-rich plasma in a rat model. Methods: Surgical defects were made in rats, which received the following treatments in a randomized manner: group I, negative control (defect creation only); group II, positive control (FGG); group III, BCM; group IV, BCM + fibroblasts; group V, ADM; and group VI, ADM + fibroblasts. Clinical, histological, and immunological analyses were performed 15 days after grafting. Clinical examinations recorded epithelium regularity and the presence of ulcers, erythema, and/or edema. Results: The histological analysis revealed the degree of reepithelization, width, regularity, and presence of keratin. The Fisher exact statistical test was applied to the results (P<0.05). No groups showed ulcers except for group I. All groups had regular epithelium without erythema and without edema. Histologically, all groups exhibited regular epithelium with keratinization, and myofibroblasts were present in the connective tissue. The groups that received engineered grafts showed similar clinical and histological results to the FGG group. Conclusions: Within the limitations of this study, it was concluded that BCM and ADM can be used as cell scaffolds, with ADM yielding the best results. This study supports the use of this technical protocol in humans.

• Anatomy and Cell Biology
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• v.56 no.1
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• pp.86-93
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• 2023

Age at death estimation has always been a crucial yet challenging part of identification process in forensic field. The use of human skeletons have long been explored using the principle of macro and micro-architecture change in correlation with increasing age. The clavicle is recommended as the best candidate for accurate age estimation because of its accessibility, time to maturation and minimal effect from weight. Our study applies pre-trained convolutional neural network in order to achieve the most accurate and cost effective age estimation model using clavicular bone. The total of 988 clavicles of Thai population with known age and sex were radiographed using Kodak 9000 Extra-oral Imaging System. The radiographs then went through preprocessing protocol which include region of interest selection and quality assessment. Additional samples were generated using generative adversarial network. The total clavicular images used in this study were 3,999 which were then separated into training and test set, and the test set were subsequently categorized into 7 age groups. GoogLeNet was modified at two layers and fine tuned the parameters. The highest validation accuracy was 89.02% but the test set achieved only 30% accuracy. Our results show that the use of medial clavicular radiographs has a potential in the field of age at death estimation, thus, further study is recommended.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.159-169
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• 2024

Purpose: The aim of this study was to evaluate the influence of different cone-beam computed tomography (CBCT) acquisition protocols on reducing the effective radiation dose while maintaining image quality. Materials and Methods: The effective dose emitted by a CBCT device was calculated using thermoluminescent dosimeters placed in a Rando Alderson phantom. Image quality was assessed by 3 experienced evaluators. The relationship between image quality and confidence was evaluated using the Fisher exact test, and the agreement among raters was assessed using the kappa test. Multiple linear regression analysis was performed to investigate whether the technical parameters could predict the effective dose. P-values<0.05 were considered to indicate statistical significance. Results: The optimized protocol (3 mA, 99 kVp, and 450 projection images) demonstrated good image quality and a lower effective dose for radiation-sensitive organs. Image quality and confidence had consistent values for all structures (P<0.05). Multiple linear regression analysis resulted in a statistically significant model. The milliamperage (b=0.504; t=3.406; P=0.027), kilovoltage peak (b=0.589; t=3.979; P=0.016) and number of projection images (b=0.557; t=3.762; P=0.020) were predictors of the effective dose. Conclusion: Optimized CBCT acquisition protocols can significantly reduce the effective radiation dose while maintaining acceptable image quality by adjusting the milliamperage and projection images.