As the world enters a fourth Industrial Revolution, organizations worldwide face challenges in dealing with important assets such as industrial technology. Leaking these assets can not only damage organizations economically but also negatively affect customer relationships and brand image. This has led to an increased awareness of industrial security in both the business and academic spheres and a focus on identifying and implementing countermeasures against security incidents, as future computing environments will continuously face security threats. This study first examines the literature on industrial security and its current status in South Korea, which is considered an active industrial security research environment. Subsequently, meta-analyses are conducted on South Korea and abroad to compare their status and research trends in the industrial security field. The results confirm that South Korea has more actively conducted relevant studies compared to international research. This study contributes to the current literature by not only increasing the awareness of industrial security but also encouraging future studies in the field to facilitate a safe and sustainable computing environment.

https://www.mdpi.com/2071-1050/12/22/9526/pdf

A Meta-Analysis of Industrial Security Research for Sustainable Organizational Growth

Managing digital marketing

Given the importance of technologies to organizations, technology leakages can cause considerable financial losses and threaten the survival of firms. Although organizations use technology protection diagnostic models to prevent such leakages, most diagnostic models focus on cybersecurity, and the evaluation system is complex, making it difficult for SMEs to use it. This makes them unsuitable for the general technology protection diagnosis of companies. Hence, this study proposes a diagnostic model that assesses these technology protection capabilities of organizations from personnel and administrative perspectives. Drawing upon the individual elements of the 7S model—shared values, strategy, structure, systems, staff, style, and skills—our model analyzes the influence of the elements on the technology protection capabilities of organizations. To determine this influence, the study conducts a questionnaire survey among 435 employees from large, larger medium-sized, and small and medium enterprises. Using the partial least squares and the artificial neural network methods, the study determines the ranking of the relative importance of the 7s elements. The results show that the shared values element most significantly influences these capabilities. The remaining elements influence the technology protection capabilities in the following order from the greatest to the least effect: staff, strategy, structure, systems, style, and skills. These findings highlight the significance of developing an awareness of the necessity of technology protection among all the members of an organization.

7S Model for Technology Protection of Organizations

In today's data communication environment, network and system security is vital. Hackers and intruders can gain unauthorized access to networks and online services, resulting in some successful attempts to knock down networks and web services. With the progress of security systems, new threats and countermeasures to these assaults emerge. Intrusion Detection Systems are one of these choices (IDS). An Intrusion Detection System's primary goal is to protect resources from attacks. It analyses and anticipates user behavior before determining if it is an assault or a common occurrence. We use Rough Set Theory (RST) and Gradient Boosting to identify network breaches (using the boost library). When packets are intercepted from the network, RST is used to pre-process the data and reduce the dimensions. A gradient boosting model will be used to learn and evaluate the features chosen by RST. RST-Gradient boost model provides the greatest results and accuracy when compared to other scale-down strategies like regular scaler.

Prevention of Data Breach by Machine Learning Techniques

The internal resource allocation approach is proposed for the information security of smart cities using the evolutionary game model. Focusing on the information resource allocation of smart cities, the relationship among information security factors is first analyzed, then the directed connection graph and adjacency matrix are constructed to obtain its directed hierarchical structure diagram by calculating the reachable matrix, thereby developing an explanatory structure model for information security resources in smart cities. Furthermore, an evolutionary game model is established, and the replicator dynamics are used to adjust the model. Finally, three types of typical problems are investigated through simulation experiments to verify and explain the structural model.

Internal Resource Allocation to Information Security of Smart Cities Using Evolutionary Game Model

This research establishes a security evaluation model from the insider leakage perspective and suggests an objective evaluation measurement. Organizational security risks are fused and compounded both inside and outside the organization. Although multiple security controls are implemented to minimize an organization’s security risk, effective security control requires management to preemptively check the organization’s security level. Existing criteria for evaluating security level are limited to external security risks and have improper limit points for dealing with security risks that are fused and compounded within an organization. The focus of this study is the prevention of technical information leakage. Furthermore, we propose a method for measuring the level at which the objectivity of certain items is secured. We compiled 26 detailed evaluation items, considering the security requirements to prevent technical information leakage. We not only performed suitability, reliability, and factor analyses and statistical validation, but also established a method to measure the security level. This measurement method ensures the effectiveness and objectivity of the evaluation of security level, mitigating the risks of security incidents caused by insiders. The results serve as a reference for organizations when designing security evaluation criteria and automated tools based on our evaluation model for future research.

https://www.mdpi.com/2071-1050/12/24/10639/pdf

The Development of a Security Evaluation Model Focused on Information Leakage Protection for Sustainable Growth

With the continuously increasing number of data leakage security incidents caused by organization insiders, current security activities cannot predict a data leakage. Because such security incidents are extremely harmful and difficult to detect, predicting security incidents would be the most effective preventative method. However, current insider security controls and systems detect and identify unusual behaviors to prevent security incidents but produce many false-positives. To solve these problems, the present study collects and analyzes data leaks by insiders in advance, analyzes information leaks that can predict security incidents, and evaluates risk based on behavior. To this end, data leakage behaviors by insiders are analyzed through an analysis of previous studies and the implementation of an in-depth interview method. Statistical verification of the analyzed data leakage behavior is performed to determine the validity and derive the levels of leakage risk for each behavior. In addition, by applying the N-gram analysis method to derive a data leakage scenario, the levels of risk are clarified to reduce false-positives and over detection (i.e., the limitations of existing data leakage prevention systems) and make preemptive security activities possible.

Research on Behavior-Based Data Leakage Incidents for the Sustainable Growth of an Organization

Most of security countermeasures have been implemented to cope with continuous increase leakage of technology, but almost security countermeasures are focused on securing the boundary between inside and outside. This is effective for detecting and responding to attacks from the outside, but it is vulnerable to internal security incidents. In order to prevent internal leakage effectively, this study identifies activities corresponding to technology leakage activities and designes technology leakage activity detection items. As a design method, we analyzed the existing technology leakage detection methods based on the previous research and analyzed the technology leakage cases from the viewpoint of technology leakage activities. Through the statistical analysis, the items of detection of the technology leakage outcomes were verified to be appropriate, valid and reliable. Based on the results of this study, it is expected that it will be a basis for designing the technology leaking scenarios based on future research and leaking experiences.

https://koreascience.kr:443/article/JAKO201924156251258.pdf

Jawon Kim

Papers

The Development of a Security Evaluation Model Focused on Information Leakage Protection for Sustainable Growth

Research on Behavior-Based Data Leakage Incidents for the Sustainable Growth of an Organization

An Exploratory Study for Clustering of Technology Leakage Activities