• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.4
• /
• pp.9-21
• /
• 2004

In this paper, we proposed the image hiding method which decreases calculation amount by encrypt partial data using discrete wavelet transform and linear scale quantization which were adopted as the main technique for frequency transform in JPEG2000 standard. Also we used the chaotic system which has smaller calculation amount than other encryption algorithms and then dramatically decreased calculation amount. This method operates encryption process between quantization and entropy coding for preserving compression ratio of images and uses the subband selection method and the random changing method using the chaotic system. For ciphering the quantization index we use a novel image encryption algerian of cyclically shifted in the right or left direction and encrypts two quantization assignment method (Top-down/Reflection code), made change of data less. Also, suggested encryption method to JPEG2000 progressive transmission. The experiments have been performed with the proposed methods implemented in software for about 500 images. consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. It has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.

• Fire Science and Engineering
• /
• v.25 no.6
• /
• pp.32-38
• /
• 2011

As the using rate of an explosive gas has been increased in the industrial site, the regional residents adjacent to the site as well as the site workers have frequently fallen into a dangerous situation. Damage caused by accident in the process using hydrogen gas is not confined only to the relevant process, but also is linked to a large scale of fire or explosion and it bring about heavy casualties. Therefore, personnel in charge should investigate the kinds and causes of the accident, forecast the scale of damage and also, shall establish and manage safety countermeasures. We, in Anti-Calamity Research Center, forecasted the scope of danger if break out a fire or/and explosion in hydrogen gas facilities of MLCC firing process. We selected piping leak accident, which is the most frequent accident case based on an actual analysis of accident data occurred. We select and apply piping leak accident which is the most frequent case based on an actual accident data as a model of damage forecasting scenario caused by accident. A jet fire breaks out if hydrogen gas leaks through pipe size of 10 mm ${\Phi}$ under pressure of 120 bar, and in case of $4kw/m^2$ of radiation level, the radiation heat can produce an effect on up to distance of maximum 12.45 meter. Herein, we are going to recommend safety security and countermeasures for improvement through forecasting of accident damages.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5B
• /
• pp.385-394
• /
• 2012

The tactical mobile communication network, which comprises a part of the next-generation Tactical Information and Communication Network (TICN), provides means of communication and control for Tactical Multi-Functional Terminals (TMFT) belonging to a Mobile Subscriber Access Point (MSAP). The next-generation of MSAP is capable of constructing a backbone network via LCTR and HCTR directional antennas. At the same time, WMN modules are used to create and manage a wireless mesh backbone. When directional antennas are used in mobile environments, seamless services cannot be efficiently supported as the movement of the node prevents the angle of the antenna to constantly match. Therefore, data communication through the wireless mesh networks is required to provide direct communication between mobile MSAPs. Accordingly, mutual authentication and data encryption mechanisms are required to provide reliable data transmission in this environment. To provide efficient mutual authentication between MSAP devices, the process of verifying a certificate of the other MSAP device through its own authentication server is required. This paper proposes mutual authentication mechanisms where the MSAP requiring authentication and the MSAP that permits it initiates low-cost and efficient authentication in a distributed way. More specifically, we propose a method of applying EAP-ELS (Extensible Authentication Protocol-Transport Layer Security) in the next-generation TICN.

• Journal of KIISE:Information Networking
• /
• v.33 no.1
• /
• pp.38-48
• /
• 2006

For extending of hot-spot of WLAN, (2) proposes internetworking scheme between wireless LAN (WLAN) and mobile ad-hoc network (MANET), which employ the same layer-2 protocol with different mode. Compared to internetworking schemes between UMTS (Universal Mobile Telecommunications Systems) and WLAN (3-4), the scheme from (2) has relatively low overhead and latencies because WLAN and MANET are physically and logically similar to each other. However, the mode switching algorithm proposed in r2] for internetworking between WLAN and MANET only considers signal strength and determines handoff, and mobile nodes following a zigzag course in pollution area may perform handoff at short intervals. Furthermore, (2) employs mobile IPv6 (MIPv6) at base, which brings still high delay on handoff and overhead due to signal message exchange. In this paper, we present optimized internetworking scheme between WLAN and MANET, modified from (2). To settle ping-pong handoff from (2), we propose adaptive mode switching algorithm. HMIPv6 is employed for IP connectivity and mobility service in WLAN, which solves some shortcomings, such as high handoff overhead and vulnerable security. For routing in MANET, OLSR is employed, which is a proactive Protocol and has optimally reduced signal broadcasting overhead. OLSR operates with current P protocol compatibly with no change or modification. The proposed internetworking scheme based on adaptive mode switching algorithm shows better performance than scheme from (2).

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.87-101
• /
• 2022

Cyber-attacks occur in the blink of an eye in cyberspace, and the damage is increasing all over the world. Therefore, it is necessary to develop a cyber common operational picture that can grasp the various assets belonging to the 3rd layer of cyberspace from various perspectives. By applying the method for grasping battlefield information used by the military, it is possible to achieve optimal cyberspace situational awareness. Therefore, in this study, the visualization screens necessary for the cyber common operational picture are identified and the criteria (response speed, user interface, object symbol, object size) are investigated. After that, the framework is designed by applying the identified and investigated items, and the visualization screens are implemented accordingly. Finally, among the criteria investigated by the visualization screen, an experiment is conducted on the response speed that cannot be recognized by a photograph. As a result, all the implemented visualization screens met the standard for response speed. Such research helps commanders and security officers to build a cyber common operational picture to prepare for cyber-attacks.

• Journal of Convergence for Information Technology
• /
• v.11 no.5
• /
• pp.30-37
• /
• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.1-15
• /
• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.1307-1307
• /
• 2024

Recent research on heavy equipment has been conducted for the purposes of enhanced safety, productivity improvement, and carbon neutrality at construction sites. A sensor-based approach is being explored to monitor the location and movements of heavy equipment in real time. However, it poses significant challenges in terms of time and cost as multiple sensors should be installed on numerous heavy equipment at construction sites. In addition, there is a limitation in identifying the collaboration or interference between two or more heavy equipment. In light of this, a vision-based deep learning approach is being actively conducted to effectively respond to various working conditions and dynamic environments. To enhance the performance of a vision-based activity recognition model, it is essential to secure a sufficient amount of training datasets (i.e., video datasets collected from actual construction sites). However, due to safety and security issues at construction sites, there are limitations in adequately collecting training dataset under various situations and environmental conditions. In addition, the videos feature a sequence of multiple activities of heavy equipment, making it challenging to clearly distinguish the boundaries between preceding and subsequent activities. To address these challenges, this study proposed a domain adaptation in vision-based transfer learning for automated excavator activity recognition utilizing 3D ResNet (residual deep neural network). Particularly, this study aimed to identify the optimal depth of 3D ResNet (i.e., the number of layers of the feature extractor) suitable for domain adaptation via fine-tuning process. To achieve this, this study sought to evaluate the activity recognition performance of five 3D ResNet models with 18, 34, 50, 101, and 152 layers, which used two consecutive videos with multiple activities (5 mins, 33 secs and 10 mins, 6 secs) collected from actual construction sites. First, pretrained weights from large-scale datasets (i.e., Kinetic-700 and Moment in Time (MiT)) in other domains (e.g., humans, animals, natural phenomena) were utilized. Second, five 3D ResNet models were fine-tuned using a customized dataset (14,185 clips, 60,606 secs). As an evaluation index for activity recognition model, the F1 score showed 0.881, 0.689, 0.74, 0.684, and 0.569 for the five 3D ResNet models, with the 18-layer model performing the best. This result indicated that the activity recognition models with fewer layers could be advantageous in deriving the optimal weights for the target domain (i.e., excavator activities) when fine-tuning with a limited dataset. Consequently, this study identified the optimal depth of 3D ResNet that can maintain a reliable performance in dynamic and complex construction sites, even with a limited dataset. The proposed approach is expected to contribute to the development of decision-support systems capable of systematically managing enhanced safety, productivity improvement, and carbon neutrality in the construction industry.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.6C
• /
• pp.648-658
• /
• 2003

As the usage of image/video contents increase, a security problem for the payed image data or the ones requiring confidentiality is raised. This paper proposed an image encryption methodology to hide the image information. The target data of it is the result from quantization in wavelet domain. This method encrypts only part of the image data rather than the whole data of the original image, in which three types of data selection methodologies were involved. First, by using the fact that the wavelet transform decomposes the original image into frequency sub-bands, only some of the frequency sub-bands were included in encryption to make the resulting image unrecognizable. In the data to represent each pixel, only MSBs were taken for encryption. Finally, pixels to be encrypted in a specific sub-band were selected randomly by using LFSR(Linear Feedback Shift Register). Part of the key for encryption was used for the seed value of LFSR and in selecting the parallel output bits of the LFSR for random selection so that the strength of encryption algorithm increased. The experiments have been performed with the proposed methods implemented in software for about 500 images, from which the result showed that only about 1/1000 amount of data to the original image can obtain the encryption effect not to recognize the original image. Consequently, we are sure that the proposed are efficient image encryption methods to acquire the high encryption effect with small amount of encryption. Also, in this paper, several encryption scheme according to the selection of the sub-bands and the number of bits from LFSR outputs for pixel selection have been proposed, and it has been shown that there exits a relation of trade-off between the execution time and the effect of the encryption. It means that the proposed methods can be selectively used according to the application areas. Also, because the proposed methods are performed in the application layer, they are expected to be a good solution for the end-to-end security problem, which is appearing as one of the important problems in the networks with both wired and wireless sections.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.1
• /
• pp.123-136
• /
• 2004

In this paper, complexity and regularity of polynomial multiplication over $GF({2^n})$ are defined by using Hamming weight of rows and columns of the matrix ever GF(2) which represents polynomial multiplication. It is shown experimentally that in order to construct the block cipher robust against differential cryptanalysis, polynomial multiplication of substitution layer and the permutation layer should have high complexity and high regularity. With result of the experiment, a way of constituting S box and G function is suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with a nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over $GF({2^8})$ which has neither a fixed pout, whose input and output are the same except 0 and 1, nor an opposite fixed number, whose output is one`s complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes linear transform with 4 S-box outputs using the matrix of 4${\times}$4 over $GF({2^8})$. The components in the matrix of linear transformation have high complexity and high regularity. Furthermore, G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, and there can be no weak input where a fixed point an opposite fixed point, and output can be two`s complement of input. The primitive polynomials of nonlinear function affine transform and linear transformation are different each other. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.