• 한국정보통신설비학회:학술대회논문집
• /
• 2009.08a
• /
• pp.387-390
• /
• 2009

Wireless Sensor Network (WSN) can easily compromised from attackers because it has the limited resource and deployed in exposed environments. When the sensitive packets are occurred such as enemy's movement or fire alarm, attackers can selectively drop them using a compromised node. It brings the isolation between the basestation and the sensor fields. To detect selective forwarding attack, Xiao, Yu and Gao proposed checkpoint-based multi-hop acknowledgement scheme (CHEMAS). The check-point nodes are used to detect the area which generating selective forwarding attacks. However, CHEMAS has static probability of selecting check-point nodes. It cannot achieve the flexibility to coordinate between the detection ability and the energy consumption. In this paper, we propose the control method for the number fo check-point nodes. Through the control method, we can achieve the flexibility which can provide the sufficient detection ability while conserving the energy consumption.

• International Journal of Internet, Broadcasting and Communication
• /
• v.14 no.3
• /
• pp.8-16
• /
• 2022

In this paper, we propose a method of reconstructing the file system to obtain digital forensics information from the APFS file system when meta information that can know the structure of the file system is deleted due to partial damage to the disk. This method is to reconstruct the tree structure of the file system by only retrieving the B-tree node where file/directory information is stored. This method is not a method of constructing nodes based on structural information such as Container Superblock (NXSB) and Volume Checkpoint Superblock (APSB), and B-tree root and leaf node information. The entire disk cluster is traversed to find scattered B-tree leaf nodes and to gather all the information in the file system to build information. It is a method of reconstructing a tree structure of a file/directory based on refined essential data by removing duplicate data. We demonstrate that the proposed method is valid through the results of applying the proposed method by generating numbers of user files and directories.

• Journal of the Korea Society for Simulation
• /
• v.19 no.2
• /
• pp.73-80
• /
• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.2
• /
• pp.15-25
• /
• 2017

A System can be more Dependable from some types of Threats if the Dependability Level Against the Threat on the System is Increased. However, The Dependability-performance Tradeoff should be Considered because the Increased Dependability may Degrade the Performance of the System. Therefore, it is Efficient to Temporally Increase the Dependability Level to High only when an Threat is Predicted on the System in a Short time while Maintaining the Level in Low or mid in Normal Situations. In this Paper, we Present a Threat Prevention Strategy for a Networked Node by Dynamically Changing the Dependability Level According to the Threat Situation on its Logically/physically Neighboring Nodes. As case Studies, we Employ our Strategy to an Internet Server Against TCP SYN Flood Attacks and to a Checkpoint and Rollback System Against Transient Faults. Our Performance Analysis Shows that our Strategy can Effectively Relieve the Damage of the Failure without Serious Performance Degradation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.88-88
• /
• 2000

As more and more critical commercial applications move on the Internet, providing highly available servers becomes increasingly important. One of the advantages of a clustered system is that it has hardware and software redundancy. High availability can be provided by detecting node or daemon failure and reconfiguring the system appropriately so that the workload can be taken over bi the remaining nodes in the cluster. This paper presents how to provide the guaranteeing high availability of clustering web server. The load balancer becomes a single failure point of the whole system. In order to prevent the failure of the load balancer, we setup a backup server using heartbeat, fake, mon, and checkpointing fault-tolerance method. For high availability of file servers in the cluster, we setup coda file system. Coda is a advanced network fault-tolerance distributed file system.

• The KIPS Transactions:PartA
• /
• v.13A no.7 s.104
• /
• pp.607-614
• /
• 2006

The checkpointing schemes should reduce the process delay through managing the checkpoints of each node to fit the network load to enhance the performance of the process running on the cluster system that write the checkpoints into its global stable storage. For this reason, a cluster system with single IO space on a distributed RAID chooses a suitable checkpointng scheme to get the maximum IO performance and the best rollback recovery efficiency. In this paper, we improved the striped checkpointing scheme with dynamic stripe group size by adapting to the network bandwidth variation at the point of checkpointing. To analyze the performance of the multi striped checkpointing scheme, we applied Linpack HPC benchmark with MPI on our own cluster system with maximum 512 virtual nodes. The benchmark results showed that the multistriped checkpointing scheme has better performance than the striped checkpointing scheme on the checkpoint writing efficiency and rollback recovery at heavy system load.

• The KIPS Transactions:PartA
• /
• v.10A no.2
• /
• pp.123-130
• /
• 2003

This paper presents a new striped checkpointing scheme for serverless cluster computers, where the local disks are attached to the cluster nodes collectively form a distributed RAID with a single I/O space. Striping enables parallel I/O on the distributed disks and staggering avoids network bottleneck in the distributed RAID. We demonstrate how to reduce the checkpointing overhead and increase the availability by striping and staggering dynamically for communication intensive applications. Linpack HPC Benchamark and MPI programs are applied to these checkpointing schemes for performance evaluation on the 16-nodes cluster system. Benchmark results prove the benefits of the striped checkpointing scheme compare to the existing schemes, and these results are useful to design the efficient checkpointing scheme for fast rollback recovery from any single node failure in a cluster system.

• Journal of Gastric Cancer
• /
• v.23 no.3
• /
• pp.410-427
• /
• 2023

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI. The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers. Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI. Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.