• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.11
• /
• pp.469-478
• /
• 2019

Car-sharing services have been settled on as a new type of public transportation owing to their enhanced convenience, expanded awareness of practical consumption patterns, the inspiration for environmental conscientiousness, and the diffusion of smart phones following the economic crisis. With development of the market, many people have started using such services. However, security is still an issue. Damage is expected since IDs and passwords are required for log-in when renting and controlling the vehicles. The protocol suggested in this study uses bio-information, providing an optimized service, and convenient (but strong) authentication with various service-provider clouds registering car big data about users through brokers. If using the techniques suggested here, it is feasible to reduce the exposure of the bio-information, and to receive service from multiple service-provider clouds through one particular broker. In addition, the proposed protocol reduces public key operations and session key storage by 20% on mobile devices, compared to existing car-sharing platforms, and because it provides convenient, but strong, authentication (and therefore constitutes a secure channel), it is possible to proceed with secure communications. It is anticipated that the techniques suggested in this study will enhance secure communications and user convenience in the future car-sharing-service cloud environment.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.4
• /
• pp.41-49
• /
• 2010

This paper proposes a new high speed SHA-1 architecture using multiple unfolding and pre-computation techniques. We unfolds iterative hash operations to 2 continuos hash stage and reschedules computation timing. Then, the part of critical path is computed at the previous hash operation round and the rest is performed in the present round. These techniques reduce 3 additions to 2 additions on the critical path. It makes the maximum clock frequency of 118 MHz which provides throughput rate of 5.9 Gbps. The proposed architecture shows 26% higher throughput with a 32% smaller hardware size compared to other counterparts. This paper also introduces a analytical model of multiple SHA-1 architecture at the system level that maps a large input data on SHA-1 block in parallel. The model gives us the required number of SHA-1 blocks for a large multimedia data processing that it helps to make decision hardware configuration. The hs fospeed SHA-1 is useful to generate a condensed message and may strengthen the security of mobile communication and internet service.

• 재활복지
• /
• v.21 no.3
• /
• pp.129-146
• /
• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of Internet Computing and Services
• /
• v.23 no.6
• /
• pp.1-13
• /
• 2022

As the information and communication environment develops, the environment of military facilities is also development remarkably. In proportion to this, cyber threats are also increasing, and in particular, APT attacks, which are difficult to prevent with existing signature-based cyber defense systems, are frequently targeting military and national infrastructure. It is important to identify attack groups for appropriate response, but it is very difficult to identify them due to the nature of cyber attacks conducted in secret using methods such as anti-forensics. In the past, after an attack was detected, a security expert had to perform high-level analysis for a long time based on the large amount of evidence collected to get a clue about the attack group. To solve this problem, in this paper, we proposed an automation technique that can classify an attack group within a short time after detection. In case of APT attacks, compared to general cyber attacks, the number of attacks is small, there is not much known data, and it is designed to bypass signature-based cyber defense techniques. As an attack model, we used MITRE ATT&CK® which modeled many parts of cyber attacks. We design an impact score considering the versatility of the attack techniques and proposed a group similarity score based on this. Experimental results show that the proposed method classified the attack group with a 72.62% probability based on Top-5 accuracy.

• Smart Media Journal
• /
• v.12 no.9
• /
• pp.9-18
• /
• 2023

Black box cryptography is a cryptographic scheme based on a hardware encryption device, operating under the assumption that the device and the user can be trusted. However, with the increasing use of cryptographic algorithms on unreliable open platforms, the threats to black box cryptography systems have become even more significant. As a consequence, white box cryptography have been proposed to securely operate cryptographic algorithms on open platforms by hiding encryption keys during the encryption process, making it difficult for attackers to extract the keys. However, unlike traditional cryptography, white box-based encryption lacks established specifications, making challenging verify its structural security. To promote the safer utilization of white box cryptography, CHES organizes The WhibOx Contest periodically, which conducts safety analyses of various white box cryptographic techniques. Among these, the Differential Computation Analysis (DCA) attack proposed by Bos in 2016 is widely utilized in safety analyses and represents a powerful attack technique against robust white box block ciphers. Therefore, this paper analyzes the research trends in white box block ciphers and provides a summary of DCA attacks and relevant countermeasures. adhering to the format of a research paper.

• Smart Media Journal
• /
• v.13 no.4
• /
• pp.33-48
• /
• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.5
• /
• pp.219-227
• /
• 2024

The rapidly changing security environment and technological innovations of the 21st century present new challenges to military organizations. Particularly, as the MZ generation, comprised of Millennials (born 1981-1996) and Generation Z (born 1997-2012), emerges as the primary workforce in the military, traditional military personnel management methods are being called into question. The MZ generation, as digital natives, are technologically proficient, prioritize personal growth and quality of life, and prefer horizontal communication and participation. The purpose of this study is to reestablish talent acquisition and retention strategies for military organizations, considering the characteristics and demands of the MZ generation. To this end, we analyzed advanced talent management techniques from the corporate sector and explored ways to apply them to the unique context of military organizations. Additionally, by examining the current status and challenges of the Korean military, we attempted a balanced approach that considers both global trends and Korea's specific circumstances. The research results suggest various strategies including career development programs, cultural innovation, improvement of reward systems, participatory decision-making, enhancement of digital competencies, and creation of flexible work environments. These strategies are expected to improve the efficiency and competitiveness of military organizations while simultaneously enhancing job satisfaction and organizational commitment among MZ generation service members.

• The KIPS Transactions:PartC
• /
• v.10C no.2
• /
• pp.125-132
• /
• 2003

In the paper, we can select the best safeguard as proposed the definite and systematical method and procedure on risk mitigation of risk management for information system. The practical risk mitigation methodology has a good fulfillment procedure and a definition to fulfill procedure on each phase. So, it is easy to fulfill and can apply to any risk management methodology. The practical risk mitigation is composed of 6 phases, which are the existing safeguard assessment, safeguard means selection, safeguard technique selection, risk admission assessment, cost-effective analysis and safeguard embodiment. The practical risk mitigation's advantages are as follow. Efficient selection of safeguards to apply to risk's features with safeguard's means and techniques before embodying safeguards. Prevention of redundant works and security budgets waste as re-using the existing excellent safeguards through the existing safeguard assessment. Reflection of organization's CEO opinions to require special safeguards for the most important information system.

• The KIPS Transactions:PartC
• /
• v.10C no.5
• /
• pp.585-594
• /
• 2003

Java card is one of promising smart card platform with java technology. Java card defines necessary packages and classes for Embedded device that have small memory such as smart card Jana card is compatible with EMV that is Industry specification standard and ISO-7816 that is international standard. However, Java card is not offers user authentication protocol. In this paper, We design and implement an user authentication protocol applicable wireless devices based on Java Card using standard 3GPP Specification (SMS), Java Card Specification (APDU), Cryptography and so on. Our Java Card user authentication techniques can possibly be applied to the area of M-Commerce, Wireless Security, E-Payment System, Mobile Internet, Global Position Service, Ubiquitous Computing and so on.

• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.31-43
• /
• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.