• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.9
• /
• pp.3751-3770
• /
• 2015

Many sorts of image processing software facilitate image editing and also generate a great number of doctored images. Forensic technology emerges to detect the unintentional or malicious image operations. Most of forensic methods focus on the detection of single operations. However, a series of operations may be used to sequentially manipulate an image, which makes the operation detection problem complex. Forensic investigators always want to know as much exhaustive information about a suspicious image's entire processing history as possible. The detection of the operation chain, consisting of a series of operations, is a significant and challenging problem in the research field of forensics. In this paper, based on the histogram distribution uniformity of a manipulated image, we propose an operation chain detection scheme to identify histogram equalization (HE) followed by the dither-like operation (DLO). Two histogram features and a local spatial feature are utilized to further determine which DLO may have been applied. Both theoretical analysis and experimental results verify the effectiveness of our proposed scheme for both global and local scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5112-5128
• /
• 2016

Tracking human body is an important problem in computer vision field. Tracking failures caused by occlusion can lead to wrong rectification of the target position. In this paper, a robust human tracking algorithm is proposed to address the problem of occlusion, rotation and improve the tracking accuracy. It is based on Tracking-Learning-Detection framework. The key auxiliary information is used in the framework which motivated by the fact that a tracking target is usually embedded in the context that provides useful information. First, face localization method is utilized to find key face location information. Second, the relative position relationship is established between the auxiliary information and the target location. With the relevant model, the key face information will get the current target position when a target has disappeared. Thus, the target can be stably tracked even when it is partially or fully occluded. Experiments are conducted in various challenging videos. In conjunction with online update, the results demonstrate that the proposed method outperforms the traditional TLD algorithm, and it has a relatively better tracking performance than other state-of-the-art methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.3
• /
• pp.814-836
• /
• 2021

Wildlife ecologists and biologists recapture deer to collect tracking data from deer collars or wait for a drop-off of a deer collar construction that is automatically detached and disconnected. The research teams need to manage a base camp with medical trailers, helicopters, and airplanes to capture deer or wait for several months until the deer collar drops off of the deer's neck. We propose an intelligent robust base-station research with a low-cost and time saving method to obtain recording sensor data from their collars to a listener node, and readings are obtained without opening the weatherproof deer collar. We successfully designed the and implemented a robust base station system for automatically collecting data of the collars and listener motes in harsh wilderness environments. Intelligent solutions were also analyzed for improved data collections and pattern predictions with drone-based detection and tracking algorithms.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.1
• /
• pp.140-147
• /
• 2024

In Current artificial structures, we must periodically make their safety inspections. In this process, we should consider the safety of workers and the accuracy of safety checks and also consider time and cost savings for safety inspections. Additionally, in the fields of architecture and civil engineering, we are unavoidable the use of foreign commercialized BIM model tools. To address these challenges, we propose mapping crack areas and BIM 3D design drawings based on augmented reality (AR) for the safety inspection of Huge Bridges. For this purpose, we define indexing of 2D/3D drawing models, create the tabulation of all 2D/3D drawings into a database, analyze QR codes, and finally integrate with augmented reality devices. we may expect our method to improve the efficiency of safety inspections on bridge sites. Moreover, we will enable the domestics of our pure technology.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.15-22
• /
• 2022

The Tactile Internet technology is considered as the evolution of the internet of things. It will enable real time applications in all fields like remote surgery. It requires extra low latency which must not exceed 1ms, high availability, reliability and strong security system. Since it appearance in 2014, tremendous efforts have been made to ensure authentication between sensors, actuators and servers to secure many applications such as remote surgery. This human to machine relationship is very critical due to its dependence of the human live, the communication between the surgeon who performs the remote surgery and the robot arms, as a tactile internet actor, should be fully and end to end protected during the surgery. Thus, a secure mutual user authentication framework has to be implemented in order to ensure security without influencing latency. The existing methods of authentication require server to stock and exchange data between the tactile internet entities, which does not only make the proposed systems vulnerables to the SPOF (Single Point of Failure), but also impact negatively on the latency time. To address these issues, we propose a lightweight authentication protocol for remote surgery in a Tactile Internet environment, which is composed of a decentralized blockchain and physically unclonable functions. Finally, performances evaluation illustrate that our proposed solution ensures security, latency and reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2014-2034
• /
• 2015

This paper focuses on solving co-channel interference (CCI) issues arising in the open subscriber group (OSG) mode of heterogeneous networks (HetNets). Considering a general framework consisting of arbitrary number of picocells within a macro cell, where the inter-user interference (IUI) is the main CCI to macro user equipments (UEs), while the the inter-cell interference (ICI) is the major CCI to pico UEs. In this paper, three IA based transceiver design schemes are proposed. For macro cell, we uniformly use block diagonalization (BD) scheme to eliminate the IUI. And for picocells, three IA schemes are proposed to mitigate the ICI. The first scheme, named as zero forcing IA (ZF-IA) scheme, aligns the inter picocell interference onto an arbitrary sub-space of the cross-tier interference using ZF scheme. Considering the channel state information (CSI) of the desired channel of pico UEs, the second scheme, named as optimal desired sub-channel selected IA (ODC-IA) scheme, aligns the inter picocell interference onto a certain sub-space of the cross-tier interference, which guarantees the largest channel gain of the desired signal of pico UEs. The third IA scheme, named as maximum cross-tier interference selected IA (MI-IA) scheme, is designed for the system with less receive antennas. The inter picocell interference is aligned onto the space of the strongest cross-tier interference and only the interference on this space is nullified. The complexity analysis and simulations show that the proposed transceiver design schemes outperform the existing IA schemes in the OSG mode of HetNets, and the MI-IA scheme reduces the requirement of the receive antennas number with lower complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.3
• /
• pp.1063-1082
• /
• 2018

The concept of SDN (Software Defined Networking) endows the network with programmability and significantly improves the flexibility and extensibility of networks. Currently a plenty of research works on introducing SDN into wireless networks. Most of them focus on the innovation of the SDN based architectures but few consider how to realize the global perception of the network through the controller. In order to address this problem, a software defined carrier grade Wi-Fi framework called SWAN, is proposed firstly. Then based on the proposed SWAN architecture, a blueprint of introducing the traditional NSA (Network Situation Awareness) into SWAN is proposed and described in detail. Through perceiving various network data by a decentralized architecture and making comprehension and prediction on the perceived data, the proposed blueprint endows the controllers with the capability to aware of the current network situation and predict the near future situation. Meanwhile, the extensibility of the proposed blueprint makes it a universal solution for software defined wireless networks SDWNs rather than just for one case. Then we further research one typical use case of proposed NSA blueprint: network performance awareness (NPA). The subsequent comparison with other methods and result analysis not only well prove the effectiveness of proposed NPA but further provide a strong proof of the feasibility of proposed NSA blueprint.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.3
• /
• pp.1098-1112
• /
• 2018

Achievable sum rate and energy efficiency (EE) are investigated for the massive multiple-input multiple-output (Massive MIMO) downlink with channel aging in the time varying Ricean fading channel. Specifically, the expression of the achievable sum rate of the system for the maximum ratio transmission (MRT) precoder with aged channel state information (CSI) in the time varying Ricean fading channel is first presented. Based on the expression, the effect of both channel aging and the Ricean factor on the power scaling law are studied. It is found that the transmit power of base station (BS) is scaled down by $1/{\sqrt{M}}$(where M is the number of the BS antennas) when the Ricean factor K is equal to zero (i.e., time varying Rayleigh fading channel), indicating that aged CSI does not affect the power scaling law. However, the transmit power of the BS is scaled down by 1/M for the time varying Ricean fading channel (where $K{\neq}0$) indicating that the Ricean factor affects the power scaling law and sum rate, and channel aging only leads to a reduction of the sum rate. Second, the EE of the system is analyzed based on the general power consumption model. Both the theoretical analysis and the simulations show that the channel aging could degrade the sum rate and the EE of the system, and it does not affect the power scaling law.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.3917-3941
• /
• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• International journal of advanced smart convergence
• /
• v.10 no.3
• /
• pp.89-96
• /
• 2021

In various areas of the 4th industry, a big issue is software quality enhancement for stability and reliability of the smart software systems. After revising software promotion law at 2020, we must clearly define requirements and separate design parts and implementation parts of an all public software development contracts. In this study, we need to validate whether the final implementation of software is followed by the original design or not. To do this, we consider the design restoration through software visualization based on reverse engineering. Therefore we propose an UML design extraction and visualization method based on reverse engineering. Based on this, we may validate whether it is implemented according to the original design, and how much visualizes and includes the code the internal complexity for improvement of software quality.