• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.357-364
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• 2019

As industrial information disclosure by insider's rate is around 80%, most of relevant researches explain briefly its causes are discontent of salary or human resources system. This paper scrapes texts on Jobplanet, an anonymous company review website and analyzes discontent keyword by 7 related area and their contexts to find out more details on brief causes referred above. After drawing LGG (Local Grammar Graph) by each areas with related dictionary list, this paper shows an example of concordance as a proof and several ways for human resources leakage prevention. Finally, text analysis results are compared with previous researches based on survey with limited questions and answers. This study is meaningful to expand the scope of employee discontent analysis with company review text and provide more specific, granular and honest discontent vocabularies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.43-51
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• 2010

It is meaningful to investigate data in unallocated space because we can investigate the deleted data. Consecutively complete file recovery using the File Carving is possible in unallocated area, but noncontiguous or incomplete data recovery is impossible. Typically, the analysis of the data fragments are needed because they should contain large amounts of information. Microsoft Word, Excel, PowerPoint and PDF document file's text are stored using compression or specific document format. If the part of aforementioned document file was stored in unallocated data fragment, text extraction is possible using specific document format. In this paper, we suggest the method of extracting a particular document file text in unallocated data fragment.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.61-68
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• 2022

The present study was based on developing an AI based model to facilitate the academic registration needs of blind students. The model was developed to enable blind students to submit academic service requests and tasks with ease. The findings from previous studies formed the basis of the study where functionality gaps from the literary research identified by blind students were utilized when the system was devised. Primary simulation data were composed based on several thousand cases. As such, the current study develops a model based on archival insight. Given that the model is theoretical, it was partially applied to help determine how efficient the associated AI tools are and determine how effective they are in real-world settings by incorporating them into the portal that institutions currently use. In this paper, we argue that voice-activated personal assistant (VAPA), text mining, bag of words, and case-based reasoning (CBR) perform better together, compared with other classifiers for analyzing and classifying the text in academic request submission through the VAPA.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.223-231
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• 2022

The application of computer software into the linguistic analysis of texts proves useful to arrive at concise and authentic results from large data texts. Based on this assumption, this paper employs a Computer-Aided Text Analysis (CATA) and a Critical Discourse Analysis (CDA) to explore the manipulative strategies of positive/negative presentation in Orwell's Animal Farm. More specifically, the paper attempts to explore the extent to which CATA software represented by the three variables of Frequency Distribution Analysis (FDA), Content Analysis (CA), and Key Word in Context (KWIC) incorporate with CDA decipher the manipulative purposes beyond positive presentation of selfness and negative presentation of otherness in the selected corpus. The analysis covers some CDA strategies, including justification, false statistics, and competency, for positive self-presentation; and accusation, criticism, and the use of ambiguous words for negative other-presentation. With the application of CATA, some words will be analyzed by showing their frequency distribution analysis as well as their contextual environment in the selected text to expose the extent to which they are employed as strategies of positive/negative presentation in the text under investigation. Findings show that CATA software contributes significantly to the linguistic analysis of large data texts. The paper recommends the use and application of the different CATA software in the stylistic and corpus linguistics studies.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.87-96
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• 2022

This paper employs a computer-aided text analysis (CATA) and a Critical Discourse Analysis (CDA) to explore the strategies of recruitment and intellectual polarization in ISIS (Islamic State in Iraq and Syria) media. The paper's main objective is to shed light on the efficacy of employing computer software in the linguistic analysis of texts, and the extent to which CATA software contribute to deciphering hidden meanings of texts as well as to arrive at concise and authentic results from these texts. More specifically, this paper attempts to demonstrate the contribution of CATA software represented in the two variables of Frequency Distribution Analysis (FDA) and Content Analysis (CA) in decoding the strategies of recruitment and intellectual polarization in one of ISIS 's digital publication: Rumiyah (a digital magazine published by ISIS). The analytical focus is on three strategies of recruitment and intellectual polarization: (i) lexicalization, (ii) intertextual religionisation, and (iii) justification. Two main findings are revealed in this study. First, the application of CATA software into the linguistic investigation of texts contributes effectively to the understanding of the thematic and ideological messages pertaining to the analyzed text. Second, the computational analysis guarantees concise, credible, authentic and ample results than is the case if the analysis is conducted without the work of computer software. The paper, therefore, recommends the integration of CATA software into the linguistic analysis of the various types of texts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4184-4202
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• 2021

Text steganography combined with natural language generation has become increasingly popular. The existing methods usually embed secret information in the generated word by controlling the sampling in the process of text generation. A candidate pool will be constructed by greedy strategy, and only the words with high probability will be encoded, which damages the statistical law of the texts and seriously affects the security of steganography. In order to reduce the influence of the candidate pool on the statistical imperceptibility of steganography, we propose a steganography method based on a new sampling strategy. Instead of just consisting of words with high probability, we select words with relatively small difference from the actual sample of the language model to build a candidate pool, thus keeping consistency with the probability distribution of the language model. What's more, we encode the candidate words according to their probability similarity with the target word, which can further maintain the probability distribution. Experimental results show that the proposed method can outperform the state-of-the-art steganographic methods in terms of security performance.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.163-167
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• 2022

The article explores linguo-stylistic influence markers in essayistic texts. The novelty of this investigation is provided by its perspective. Essayism is looked at as a style of thinking and writing and studied as a holistic philosophical and cultural phenomenon, as a revalent form of comprehension of reality that features non-lasting author's judgements and enhancement of the author's voice in the text. Based on the texts by V. Rosanov, G.K. Chesterton, and D. Dontsov, the remarkable English, Russian, and Ukrainian essay-writers of the first party of the 20th century, the article tracks the typical ontological-and-existentialist correlation at the content, stylistic, and semantic levels. It is observed in terms of the ideas presented in the texts of these publicists and the lexicostylistic markers of the influence on the reader that enable these ideas to implement. The explored poetic syntax, key lexemes, dialogueness, intonational melodics, specific language, free associations, aphoristic nature, verbalization of emotions and feeling in the psycholinguistic form of their expression, stress, heroic elevation, metaphors and evaluative linguistic units in the ontological-and-existentialist aspects contribute to extremely delicate and demanding nature of the essayistic style. They create a "lacework" of unpredictable properties, intellectual illumination, unexpected similarity, metaphorical freshness, sudden discoveries, unmotivated unities.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.48-54
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• 2023

Nowadays, a blind man finds it very difficult to cross the roads. They should be very vigilant with every step they take. To resolve this problem, Convolutional Neural Networks(CNN) is a best method to analyse the data and automate the model without intervention of human being. In this work, a traffic signal recognition system is designed using CNN for the visually impaired. To provide a safe walking environment, a voice message is given according to light state and timer state at that instance. The developed model consists of two phases, in the first phase the CNN model is trained to classify different images captured from traffic signals. Common Objects in Context (COCO) labelled dataset is used, which includes images of different classes like traffic lights, bicycles, cars etc. The traffic light object will be detected using this labelled dataset with help of object detection model. The CNN model detects the color of the traffic light and timer displayed on the traffic image. In the second phase, from the detected color of the light and timer value a text message is generated and sent to the text-to-speech conversion model to make voice guidance for the blind person. The developed traffic light recognition model recognizes traffic light color and countdown timer displayed on the signal for safe signal crossing. The countdown timer displayed on the signal was not considered in existing models which is very useful. The proposed model has given accurate results in different scenarios when compared to other models.

• Journal of Information Technology Services
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• v.23 no.2
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• pp.13-29
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• 2024

Recently, with the rapid spread of mobile terminals such as smartphones and tablet PCs, social demand for mobile information security is increasing as new security issues that are difficult to predict as well as service evolution and lifestyle changes are raised. Smart terminals include smartphones, smart pads, chromebooks, laptops, etc. that provide various functions such as phone calls, text messages, Internet browsing, social media apps, games, and education. Along with the explosive spread of these smart terminals, they are naturally being used in our daily life and educational environment. In the mobile environment, behind the convenience of portability, there are more various security threats and vulnerabilities than in the general PC environment, and threats such as device loss, information leakage, and malicious codes exist, so it is necessary to take fundamental security measures at a higher level. In this study, we suggest ways to improve security by identifying trends in mobile smart information security and effectively responding to security threats to the mobile environment. In addition, it presents implications for various measures for effective class utilization along with correct security management methods and security measures related to the supply of smart devices that the Office of Education is promoting for schools at each level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.734-750
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• 2012

CAPTCHAs are automated tests that are there to avoid misuse of computing and information resources by bots. Typical text-based CAPTCHAs are proven to be vulnerable against malicious automated programs. In this paper, we present an image-based CAPTCHA scheme using easily identifiable human appearance characteristics that overcomes the weaknesses of current text-based schemes. We propose and evaluate two applications for our scheme involving 25 participants. Both applications use same characteristics but different classes against those characteristics. Application 1 is optimized for security while application 2 is optimized for usability. Experimental evaluation shows promising results having 83% human success rate with Application 2 as compared to 62% with Application 1.