• Analytical Science and Technology
• /
• v.34 no.6
• /
• pp.251-258
• /
• 2021

Knives are most frequently used as weapons in violent crimes. Criminals leave behind knife sheaths made of paper and tape at crime scenes. It is difficult to develop fingerprints using tape attached to a porous surface, resulting in the need to explore effective techniques for identifying fingerprints as well as the distribution of fingerprints on each surface, when evidence such as paper knife sheaths are found. In this study, 50 knife sheaths were prepared. The cyanoacrylate fuming (CA fuming) method was applied to develop fingerprints on the non-adhesive side of the tape, and a dual-purpose 1,2-indanedione/Zn (1,2-IND/Zn) reagent was used to separate tape from paper while simultaneously developing fingerprints on the paper. The fingerprints on the adhesive side of the tape were developed using Wet Powder Black^®. Using the R statistical analysis program (The R Foundation for Statistical Computing), we used a heat map to indicate the location of fingerprints developed from each surface. More fingerprints were detected at the ends than in the center of the adhesive side of the tape, and although the non-adhesive sides of tape and paper did not present clear distribution patterns, many fingerprints were developed that had sufficient clarity for personal identification. The results of this study may be applicable for processing evidence when paper sheaths are found at crime scenes.

• Phonetics and Speech Sciences
• /
• v.14 no.3
• /
• pp.103-112
• /
• 2022

Due to the popularization of smartphones, most of the recorded speech files submitted as evidence of recent crimes are produced by smartphones, and the integrity (forgery) of the submitted speech files based on smartphones is emerging as a major issue in the investigation and trial process. Samsung smartphones with the highest domestic market share are distributed with built-in speech recording applications that can record calls and voice, and can edit recorded speech. Unlike editing through third-party speech (audio) applications, editing by their own builtin speech applications has a high similarity to the original file in metadata structures and attributes, so more precise analysis techniques need to prove integrity. In this study, we constructed a speech file metadata database for speech files (original files) recorded by 34 Samsung smartphones and edited speech files edited by their built-in speech recording applications. We analyzed by comparing the metadata structures and attributes of the original files to their edited ones. As a result, we found significant metadata differences between the original speech files and the edited ones.

• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.4
• /
• pp.431-453
• /
• 2022

Hate is a collective expression of exclusivity toward others and it is fostered and reproduced through false public perception. This study aims to explore the objects and issues of hate discussed in our society using text mining techniques. To this end, we collected 17,867 news data published from 1990 to 2020 and constructed a co-word network and cluster analysis. In order to derive an explicit co-word network highly related to hate, we carried out sentence split and extracted a total of 52,520 sentences containing the words 'hate', 'prejudice' and 'discrimination' in the preprocessing phase. As a result of analyzing the frequency of words in the collected news data, the subjects that appeared most frequently in relation to hate in our society were women, race, and sexual minorities, and the related issues were related laws and crimes. As a result of cluster analysis based on the co-word network, we found a total of six hate-related clusters. The largest cluster was 'genderphobic', accounting for 41.4% of the total, followed by 'sexual minority hatred' at 28.7%, 'racial hatred' at 15.1%, 'selective hatred' at 8.5%, 'political hatred' accounted for 5.7% and 'environmental hatred' accounted for 0.3%. In the discussion, we comprehensively extracted all specific hate target names from the collected news data, which were not specifically revealed as a result of the cluster analysis.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.4
• /
• pp.49-57
• /
• 2022

The government is making great efforts to prevent crimes such as missing children by using public CCTVs. However, there is a shortage of operating manpower, weakening of concentration due to long-term concentration, and difficulty in tracking. In addition, applying real-time object search, re-identification, and tracking through a deep learning algorithm showed a phenomenon of increased parameters and insufficient memory for speed reduction due to complex network analysis. In this paper, we designed the network to improve speed and save memory through the application of Yolo v4, which can recognize real-time objects, and the application of Batch and TensorRT technology. In this thesis, based on the research on these advanced algorithms, OSNet re-ranking and K-reciprocal nearest neighbor for re-identification, Jaccard distance dissimilarity measurement algorithm for correlation, etc. are developed and used in the solution of CCTV national safety identification and tracking system. As a result, we propose a solution that can track objects by recognizing and re-identification objects in real-time within situation of a Korean public multi-CCTV environment through a set of algorithm combinations.

• Korean Journal of Culture and Social Issue
• /
• v.27 no.3
• /
• pp.237-258
• /
• 2021

The purpose of this research was to empirically explore the association between exposure to news of the nth Room Case, indirect trauma, and beliefs about the world among adults in their 20s. A total of 228 adults in their 20s participated in an online survey designed to study the association above. Analysis using SPSS 25.0 showed that participants who were exposed to more related news immediately after the nth Room case was revealed experienced a higher level of indirect trauma. Furthermore, indirect trauma fully mediated the relationship between exposure to the news of the nth Room Case and beliefs about the world. This study empirically demonstrated the impact of news exposure on beliefs about the world through indirect trauma, suggesting that, like disasters, sex crimes can cause indirect trauma to third parties through the news. However, this study was limited to adults in their 20s, and most of the participants were women; therefore, future studies using samples representing demographically more diverse groups are needed. Future research could also examine the possibility of emotional contagion mediating or moderating the relationship between news exposure and indirect trauma.

• Korean Journal of Forensic Psychology
• /
• v.12 no.2
• /
• pp.199-221
• /
• 2021

The purpose of this study is to examine some factors affecting the decision-making process of white-collar crime. In a between-subject experiment, 102 adult white-collar workers were randomly assigned to a financial pressure condition or tit for tat strategy condition. Participants went through a decision-making process in a modified iterated prisoner's dilemma for a white-collar crime scenario to earn points. The obtained score indicated the risk of committing a crime. The lower the score, the higher was the risk of participating in a crime. The results showed that participants who received only tit for tat strategy information without financial pressure instructions showed the lowest risk of participating in a crime, and those who received only financial pressure without the strategic information had the highest risk of participating in a crime. In addition, those who received the financial pressure instructions were more likely to participate in a crime than those who did not receive financial pressure instructions regardless of the provision of strategic information. The results of this study propose the need for measures to legally relieve financial pressure, the need for education on white-collar crimes for office workers, and the need for a decision-making structure within the enterprise that is not dogmatic but cooperative and mutually verifiable.

• Korean Journal of Forensic Psychology
• /
• v.11 no.1
• /
• pp.37-61
• /
• 2020

Lee, Khogali, Despodova, and Penrod (2019) demonstrated that American participants whose races are different from a defendant and a victim rendered more punitive judgments against the defendant in a same-race crime (e.g., White observer-Black defendant-Black victim) compared to a cross-race crime (e.g., White observer-Black defendant-Hispanic victim). The aim of the current study was to test the replicability of their findings in a different country-South Korea. Study 1a failed to replicate the race-combination effect in South Korea with three new moderators-case strength, defendant's use of violence, and race salience. Study 1b was conducted with the same design of Study 1a in the United States to examine whether the failure of the replication in Study 1a was due to cultural differences between South Korea and the United States. However, Study 1b also failed to replicate the race-combination effect. Study 2 conducted a meta-analytic review of the data from Lee et al.'s (2019) study, along with the data from Study 1a and 1b and revealed that the race-salience manipulation in Study 1a and 1b might have caused the null results. We conclude that when people' races are different from both a defendant and a victim, they are likely to render more punitive judgments against the defendant in a same-race crime than a cross-race crime. However, the race-combination effect is only sustained when race-relevant issues are not salient in the crime.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.4
• /
• pp.189-198
• /
• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.9
• /
• pp.289-296
• /
• 2017

Anger cause heart disease and domestic violence and recently there have been an increasing number of media reports of crimes committed because of their inability to control their anger. Anger has been reported to cause massive financial losses due to heart disease and domestic violence. Therefore, since anger raises serious social problems and social costs, it is necessary to take active intervention methods to alleviate inappropriate anger coping. A variety of methods such as cognitive and emotional approach, psycho-mechanical approach, psycho-educational approach, relaxation therapy, cognitive behavior-art therapy, and stress immunization are being explored and utilized for presenting effective anger-coping intervention alternatives. In this manner, information and communication technology is likely to be used as an effective means for this, and various researches are being conducted. The purpose of this study is to develop an anger coping service technology using ICT (Information & Communication Technology) technology as an effort to improve anger coping ability. In other words, the goal is to develop a technology that delays anger and evokes the surroundings by providing location-based services to recognize anger situations and facilitate anger. This research is about the technology which intervene directly the anger situation to resolve it using location information and introduce the base technology to realize it.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.471-485
• /
• 2023

Recently, due to the nature of blockchain that guarantees users' anonymity, more and more cases are being exploited for crimes such as illegal transactions. However, cryptocurrency is protected in cryptocurrency wallets, making it difficult to recover criminal funds. Therefore, this study acquires artifacts from the data and memory area of a local PC based on user behavior from four browser extension wallets (Metamask, Binance, Phantom, and Kaikas) to track and retrieve cryptocurrencies used in crime, and analyzes how to use them from a digital forensics perspective. As a result of the analysis, the type of wallet and cryptocurrency used by the suspect was confirmed through the API name obtained from the browser's cache data, and the URL and wallet address used for the remittance transaction were obtained. We also identified Client IDs that could identify devices used in cookie data, and confirmed that mnemonic code could be obtained from memory. Additionally, we propose an algorithm to measure the persistence of obtainable mnemonic code and automate acquisition.