• Journal of Distribution Science
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• v.17 no.3
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• pp.57-67
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• 2019

Purpose - This study aims to examine the impact of work values on entrepreneurial attitudes, and test the moderating effect of entrepreneurial opportunity identification on the above mentioned relationship as well. Research design, data, and methodology - A questionnaire survey was conducted to 258 employees who comes from 8 different types of the enterprises in northwestern of China, and the corresponding research model was verified. Results - The results show that "comfort and security" (one dimension of work values) has a significant negative impact on entrepreneurial attitudes. Another two dimensions of work values, such as "competence and growth" and "status and independence" have a significant positive impact on entrepreneurial attitudes. In addition, entrepreneurial opportunity identification has a significant moderating effect on the relations between work values and entrepreneurial attitudes. Specifically, only the entrepreneurship opportunity identification positively moderates the relationship between status & independence and entrepreneurial attitudes. Conclusions - This research further enriches the relevant theories of organizational behavior and entrepreneurships. This study also has guiding significance and value for management practice, especially for this research results implies, that is, individual's ability to entrepreneurial opportunity identification (e.g., identify feasible distribution channel for potential new venture) is important in entrepreneurship.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.201-208
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• 2011

The aim of this paper is to develop a framework of weather information services which is for processing contents and providing proper contents to new-media such as outdoor electronic display, DID (digital information display), and terrestrial multi-channel broadcasting, etc. By introducing the analysis of media use and perception science of human intelligence, the contents producing method to improve recognizing rate for weather information is provide and the layered framework of weather information services for new-media is designed. It integrates many different services to the framework. It can prevent duplicate investment for services and serve a major momentum to technical progress.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.11-25
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• 2018

While being believed that decrypting any RSA ciphertext is as hard as factorizing the RSA modulus, it was also shown that, if additional information is available, breaking the RSA cryptosystem may be much easier than factoring. For example, Coppersmith showed that, given the 1/2 fraction of the least or the most significant bits of one of two RSA primes, one can factorize the RSA modulus very efficiently, using the lattice-based technique. More recently, introducing the so called cold boot attack, Halderman et al. showed that one can recover cryptographic keys from a decayed DRAM image. And, following up this result, Heninger and Shacham presented a polynomial-time attack which, given 0.27-fraction of the RSA private key of the form (p, q, d, $d_p$, $d_q$), can recover the whole key, provided that the given bits are uniformly distributed. And, based on the work of Heninger and Shacham, this paper presents a different approach for recovering RSA private key bits from decayed key information, under the assumption that some random portion of the private key bits is known. More precisely, we present the algorithm of recovering RSA private key bits from erased key material and elaborate the formula of describing the number of partially-recovered RSA private key candidates in terms of the given erasure rate. Then, the result is justified by some extensive experiments.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.7-12
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• 2014

Quantum cryptography is one of the most feasible fields using quantum mechanics. Therefore, quantum cryptography has consistently been researched, and a variety of cryptographic exchange method has been developed, such as BB84, etc. This paper explains a basic concept of quantum communications and quantum key distribution systems using quantum mechanics. Also, it introduces a reason of the development of quantum cryptography and attack scenarios which threaten the security of QKD. Finally, the experiment of this paper simulates quantum key attack by estimating qubit phases through a modeled quantum channel, and discusses needs of post-processing methods for overcoming eavesdropping.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5819-5840
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• 2018

Considering the topology of hierarchical tree structure, each cluster in WSNs is faced with various attacks launched by malicious nodes, which include network eavesdropping, channel interference and data tampering. The existing intrusion detection algorithm does not take into consideration the resource constraints of cluster heads and sensor nodes. Due to application requirements, sensor nodes in WSNs are deployed with approximately uncorrelated security weights. In our study, a novel and versatile intrusion detection system (IDS) for the optimal defense strategy is primarily introduced. Given the flexibility that wireless communication provides, it is unreasonable to expect malicious nodes will demonstrate a fixed behavior over time. Instead, malicious nodes can dynamically update the attack strategy in response to the IDS in each game stage. Thus, a multi-stage intrusion detection game (MIDG) based on Bayesian rules is proposed. In order to formulate the solution of MIDG, an in-depth analysis on the Bayesian equilibrium is performed iteratively. Depending on the MIDG theoretical analysis, the optimal behaviors of rational attackers and defenders are derived and calculated accurately. The numerical experimental results validate the effectiveness and robustness of the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4573-4594
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• 2020

Announcement protocol in Internet of Vehicles (IoV) is an intelligent application to enhance public safety, alleviate traffic jams and improve transportation quality. It requires communication between vehicles, roadside units and pedestrian to disseminate safety-related messages. However, as vehicles connected to internet, it makes them accessible globally to a potential adversary. Safety-related application requires a message to be reliable, however it may intrude the privacy of a vehicle. Contrarily, if some misbehaviour emerges, the malicious vehicles must be able to traceable and revoke from the network. This is a contradiction between privacy and accountability since the privacy of a user should be preserved. For a secure communication among intelligent entities, we propose a novel announcement protocol in IoV using group signature. To the best of our knowledge, our work is the first comprehensive construction of an announcement protocol in IoV that deploys group signature. We show that our protocol efficiently solves these conflicting security requirements of message reliability, privacy and accountability using 5G communication channel. The performance analysis and simulation results signify our work achieves performance efficiency in IoV communication.

• Journal of Distribution Science
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• v.20 no.7
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• pp.107-117
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• 2022

Purpose: The scope of forensic investigations serves to identify malicious activities, including leakage of crucial corporate information. The investigations also identify security lapses in available networks. The purpose of the present study is to explore how to block distribution channels to protect illegal leakage in supply chain through digital forensic method. Research design, data and methodology: The present study conducted the qualitative textual analysis and its data collection process entails five steps: identifying and collecting data, determining coding categories, coding the content, checking validity and reliability, and analyzing and presenting the results. This methodology is a significant research method due to its high quality of previous resources. Results: Applying previous literature analysis to the results of this study, the author figured out that there are four solutions as an evidences to block distribution channels, preventing illegal leakage regarding company information. The following subtitles show clear solutions: (1) Communicate with Stakeholders, (2) Preventing and addressing illegal leakage, (3) Victims of Data Breach, (4) Focusing Solely on Technical Teams. Conclusion: There are difficult scenarios that continue to introduce difficult questions surrounding engagement with digital evidence. Consequently, it is important to enhance data handling to provide answers for organizations that suffer due to illegal leakages of sensitive information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.759-764
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• 2021

Because sensitive and private information should be exchanged between electric vehicles and a V2G service provider, reliable communication channel is essential to operate Vehicle-to-Grid (V2G) system which considers battery of electric vehicles as a factor of smart grid. The block chain is a platform for cryptocurrency transaction and fully distributed database system running by only equivalent node in the network without help of any central management or 3^rd party. In this paper, the structure and operation method of the blockchain are investigated, and the application of the blockchain for the V2G system was also explained and analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1671-1686
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• 2022

Face manipulation tools represented by Deepfake have threatened the security of people's biological identity information. Particularly, manipulation tools with deep learning technology have brought great challenges to Deepfake detection. There are many solutions for Deepfake detection based on traditional machine learning and advanced deep learning. However, those solutions of detectors almost have problems of poor performance when evaluated on different quality datasets. In this paper, for the sake of making high-quality Deepfake datasets, we provide a preprocessing method based on the image pixel matrix feature to eliminate similar images and the residual channel attention network (RCAN) to resize the scale of images. Significantly, we also describe a Deepfake detector named Cascaded-Hop which is based on the PixelHop++ system and the successive subspace learning (SSL) model. By feeding the preprocessed datasets, Cascaded-Hop achieves a good classification result on different manipulation types and multiple quality datasets. According to the experiment on FaceForensics++ and Celeb-DF, the AUC (area under curve) results of our proposed methods are comparable to the state-of-the-art models.