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In the past, phishing techniques were a common means of attack carried out by individuals or small groups via spam mail on a randomly selected target. However, in recent years, phishing techniques have been adopted by advanced persistent threat (APT) groups to attack organizations such as the Sony Pictures Enterprise and Korea Hydro & Nuclear Power. As such, our study aims to analyze the past campaigns conducted by the APT groups. We aim to propose a countermeasure that corresponds to the phishing campaign by collecting datasets pertaining to the phishing techniques. Based on our past study, we collected private and public data from 16 different cases that utilize a phishing attack. Our research adopted MITRE’s ATT&CK framework and tactic, techniques, and procedures (TTPs) to extract and examine the various campaigns. The framework proposed in this study makes considerable contributions to both the private and public sectors, as the framework aids the organizations in counteracting the malicious threats performed by the APT groups.

Despite the extensive ramifications of illegal online gambling (IOG) services, actions taken by government authorities have had little effect in halting these operations. In order to reduce the prevalence of IOG, the ability to detect malicious uniform resource locators (URLs) is crucial. Text mining and binary classification have been widely adopted to detect and prevent spam short message services (SMSs), but government authorities and various task forces that monitor and regulate gambling also rely on the analysis of malicious URLs. This study proposes a novel system to analyse the characteristics of spam URLs, offering a method that can assist government agencies combatting mobile IOG sites.

With the development of IoT devices, wearable devices are being used to record various types of information. Wearable IoT devices are attached to the user and can collect and transmit user data at all times along with a smartphone. In particular, sensitive information such as location information has an essential value in terms of privacy, and therefore some IoT devices implement data protection by introducing methods such as masking. However, masking can only protect privacy to a certain extent in logs having large numbers of recorded data. However, the effectiveness may decrease if we are linked with other information collected from within the device. Herein, a scenario-based case study on deanonymizing anonymized location information based on logs stored in wearable devices is described. As a result, we combined contextual and direct evidence from the collected information. It was possible to obtain the result in which the user could effectively identify the actual location. Through this study, not only can a deanonymized user location be identified but we can also confirm that cross-validation is possible even when dealing with modified GPS coordinates.

The smart factory environment has been transformed into an Industrial Internet of Things (IIoT) environment, which is an interconnected and open approach. This has made smart manufacturing plants vulnerable to cyberattacks that can directly lead to physical damage. Most cyberattacks targeting smart factories are carried out using malware. Thus, a solution that efficiently detects malware by monitoring and analyzing network traffic for malware attacks in smart factory IIoT environments is critical. However, achieving accurate real-time malware detection in such environments is difficult. To solve this problem, this study proposes an edge computing-based malware detection system that efficiently detects various cyberattacks (malware) by distributing vast amounts of smart factory IIoT traffic information to edge servers for deep learning processing. The proposed malware detection system consists of three layers (edge device, edge, and cloud layers) and utilizes four meaningful functions (model training and testing, model deployment, model inference, and training data transmission) for edge-based deep learning. In experiments conducted on the Malimg dataset, the proposed malware detection system incorporating a convolutional neural network with image visualization technology achieved an overall classification accuracy of 98.93%, precision of 98.93%, recall of 98.93%, and F1-score of 98.92%.

Originating from the desire to improve sustainability, producing fuels and chemicals from the conversion of biomass and waste plastic has become an important research topic in the twenty-first century. Although biomass is natural and plastic synthetic, the chemical nature of the two are not as distinct as they first appear. They share substantial structural similarities in terms of their polymeric nature and the types of bonds linking their monomeric units, resulting in close relationships between the two materials and their conversions. Previously, their transformations were mostly studied and reviewed separately in the literature. Here, we summarize the catalytic conversion of biomass and waste plastics, with a focus on bond activation chemistry and catalyst design. By tracking the historical and more recent developments, it becomes clear that biomass and plastic have not only evolved their unique conversion pathways but have also started to cross paths with each other, with each influencing the landscape of the other. As a result, this Review on the catalytic conversion of biomass and waste plastic in a unified angle offers improved insights into existing technologies, and more importantly, may enable new opportunities for future advances.

Distant organ crosstalk during AKI, first studied mechanistically in the lung (1), is now known to play an important role in disease outcomes. The relationship between intestinal microbiota and AKI has also been explored, resulting in exciting findings that are promising for future human therapeutics. In search of ways to reduce kidney T cells by using “cleaner,” germfree (GF) mice, it was unexpectedly found that GF mice not only retained their kidney immune cells, but also had a higher number of natural killer T (NKT) cells and reduced IL-4 levels compared with normal wild-type (WT) mice. Moreover, GF mice subjected to kidney ischemia-reperfusion (IR) injury had increased CD8 T-cell trafficking and inflammatory cytokine mediators compared with normal WT mice (2). Induction of ischemic AKI in GF mice led to a worse course of AKI, in terms of both structure and function. Conventionalizing GF mice with normal mouse stool led to normalizing T-cell and NKT populations, and relative protection from AKI, compared with GF mice (2). It was subsequently observed that early exposure to gut microbiota during development was associated with long-term changes in NKT-cell function in nonrenal tissues, and NKT cells in GF mice had a less mature phenotype with diminished activation capacity upon antigen encounter (3,4). To elucidate whether the effects were bidirectional and AKI led to changes in the gut microbiome, gut microbiota was evaluated in C57BL/6 WT mice after ischemic or nephrotoxic (cisplatin; CP) injury. DNA was isolated from the fecal pellets ( n =4–5 per group) at baseline (D0) and at 3 days (D3) post-IR. The V3–V5 region of the 16S ribosomal RNA gene was amplified using the 357F/926R primer set and sequenced using the Roche/454 platform. IR and CP modified the relative abundance of specific bacterial species belonging to the phyla Actinobacteria, Bacteroidetes, Firmicutes, …

Since the GDPR was implemented in 2018, organizations that collect data from the EU residents are required to receive the user’s consent. Organizational measures to ensure that the organizations are compliant to the recently enacted GDPR are still abstract and ambiguous. Moreover, data subjects and controllers have demanded the practice of obtaining consent from organizations. By observing the case law and guidelines related to the GDPR provisions, we deduced four consent conditions. Then, we examined how online service provider’s websites are making efforts to implement the GDPR framework. For this, we identified key characteristics of these websites, such as the existence of consent buttons. In order to help the data subjects obtain consent, we proposed an automatic tool that can check the consent conditions by checking the websites. Our study examined 10,000 websites for 26 days using the Python libraries with the tool automatically crawling the website information and analyzes the HTML structure according to the specified conditions. In addition, this tool crawls the privacy policy of each website. Moreover, it automatically determines whether it meets the four consent conditions by calculating it according to the formula defined in the consent condition. To evaluate the tool’s accuracy, the researchers manually analyzed 500 websites and compared the manual analysis with the results of the tool’s automatic analysis. We found that this tool differentiates itself through qualitative comparisons with other GDPR meters.

The development of information and communication technologies extended the application of digitalized industrial control systems (ICSs) to critical infrastructure. With this circumstance, emerging sophisticated cyberattacks by adversaries, including nation-backed terrorists, target ICSs due to their strategic value that critical infrastructure can cause severe consequences to equipment, people, and the environment due to the cyberattacks on ICSs. Therefore, critical infrastructure owners should provide high assurance to those involved, such as neighboring residents and governments, that the facility is adequately protected against cyberattacks. The risk assessment that identifies, estimates, and prioritizes risks is vital to provide high assurance. This study proposes a framework for evaluating risks by quantifying the likelihood of cyber exploitation and the consequences of cyberattacks. The quantification of the likelihood of cyber exploitation is inspired by research on Bayesian attack graphs (BAGs), allowing probability evaluation that considers the causal relationship between ICSs and multistage attacks. For the cyberattack consequences quantification, we propose a methodology to evaluate how far an impact will spread and thus how many functions will be influenced when an ICS is exploited. The methodology is conducted by ICS experts identifying and listing functional dependencies and essential function goals among ICSs that they are already familiar with and do not require in-depth cybersecurity knowledge. Through experiments, we demonstrated how to apply our framework to assess the risks of the plant protection system, which is a safety-grade digital system used in nuclear power plants. The result shows that risk can be multidimensionally assessed than previous literature, such as discovering that components that were not considered important have high risk due to their functional connectivity.

본 연구는 학업성적과 자존감이 우울감과 행복감에 미치는 영향을 밝히는데 있다. 이를 위하여 한국복지패널 7차와 10차 자료에서 초등학생 444명과 고등학생 492명을 대상으로 구조방정식 모형을 통해 분석하였다. 본 연구에서 분석한 결과 외생변수인 부모지원은 두 집단 모두 학업성적에 직접효과가 있는 것으로 나타났으나, 자존감의 경우 고등학생 집단에는 직접효과가 있는 것으로 나타났으나, 초등학생 집단에는 직접효과가 없는 것으로 나타났다. 또한 학교환경은 학업성적 및 자존감에 두 집단 모두 직접 효과가 있는 것으로 나타났으며, 학업성적은 두 집단 모두 우울감과 행복감에 직접효과는 없는 것으로 나타났으나, 자존감은 두 집단 모두 우울감과 행복감에 직접효과가 있는 것으로 나타났다. 본 연구 결과에서 나타난 두드러진 특성은 자존감의 효과라 판단된다. 학업성적이 우울감과 행복감에 영향을 미치지 못하는 반면, 자존감의 효과는 상대적으로 크기 때문이다. 특히 초등학생 및 고등학생 집단 간 직접적인 영향뿐만 아니라 매개효과가 모두 자존감과 관련되어 있는 것으로 나타났다.

The direct hydroconversion of triglycerides into biojet fuel (i.e., cascade reactions including hydrogenation, deoxygenation, and hydrocracking) is challenging, even though it is beneficial in terms of process intensification. This is because the minute amount of CO produced during deoxygenation can poison the metal component of various metal–acid bifunctional catalysts, causing undesired overcracking and rapid catalyst deactivation through coke formation. To overcome this problem, we synthesized a CO-tolerant catalyst by supporting bimetallic PtRe on ultra-stable Y (USY) zeolite as acidic support. Compared to conventional catalyst (e.g., Pt/USY), PtRe/USY showed markedly enhanced tolerance to CO because it had weakened interaction with CO and also could rapidly convert the chemisorbed CO into less harmful methane and H2O through methanation. Consequently, overcracking and catalyst deactivation were greatly suppressed during the direct triglyceride hydroconversion. It is remarkable that PtRe/USY is intrinsically a much poorer hydrocracking catalyst than Pt/USY under pure H2 atmosphere because of its high hydrogenolysis activity. However, H2O and CO produced in situ during the deoxygenation of triglycerides selectively poisoned the active sites for undesired hydrogenolysis, thereby making PtRe/USY a highly stable and selective catalyst for producing biojet fuel. Under the optimum condition, 41 wt% of biojet fuel with respect to palm oil could be produced through direct hydroconversion, which satisfied all the required fuel specifications.

Protein synthesis is important for maintaining cellular homeostasis under various stress responses. In this study, we screened an anticancer drug library to select compounds with translational repression functions. AZD8055, an ATP-competitive mechanistic target of rapamycin complex 1/2 (mTORC1/2) inhibitor, was selected as a translational suppressor. AZD8055 inhibited protein synthesis in mouse embryonic fibroblasts and hepatocellular carcinoma HepG2 cells. Extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK) were activated during the early phase of mTORC1/2 inhibition by AZD8055 treatment. Combined treatment of AZD8055 with the MAPK kinase1/2 (MEK1/2) inhibitor refametinib or the p38 inhibitor SB203580 markedly decreased translation in HepG2 cells. Thus, the inhibition of ERK1/2 or p38 may enhance the efficacy of AZD8055-mediated inhibition of protein synthesis. In addition, AZD8055 down-regulated the phosphorylation of eukaryotic initiation factor 4E-binding protein 1 (4E-BP1), and AZD8055-induced phosphorylation of ERK1/2 and p38 had no effect on phosphorylation status of 4E-BP1. Interestingly, AZD8055 modulated the 4E-BP1 mRNA pool by up-regulating ERK1/2 and p38 pathways. Together, these results suggest that AZD8055-induced activation of MAPKs interferes with inhibition of protein synthesis at an early stage of mTORC1/2 inhibition, and that it may contribute to the development of resistance to mTORC1/2 inhibitors.