• 정보보호학회논문지
• /
• 제5권1호
• /
• pp.51-64
• /
• 1995

분산 환경을 고려한 보안 데이터베이스 모델에 효율적인 접근 제어와 자료가 가지는 가치의 중요도에 따라 정보의 흐름을 제어하기 위한 다단계 기법을 도입하는 연구들이 진행되어 왔다. 기존의 기법들은 문제점을 내포한 상태에서 연구가 이루어졌다. 문제점은 첫째, 다단계로 보호되는 전역적인 자료에 대한 관리가 거의 불가능하다는 점이다. 둘째, 부분과 전역의 자료에 대한 과도한 접근 취소로 실제 사용자의 접근 허용여부와 접근을 원하는 자료의 상관 관계를 분리하기가 어려워 진다. 기존의 기법이 가진 문제점으로 인해 성능의 하락과 사용에 있어 유연성을 제공할 수 없다. 본 논문에서는 분산 환경에서 자료에 대한 보호를 쉽게 얻을 수 있고 전역적인 자료의 효율적인 관리와 사용자가 접근하고자 하는 자료에 대한 접근 취소가 일어나지 않는 스키마를 이용한 다단계 보안 데이터베이스 모델을 제안했다.

• International Journal of Computer Science & Network Security
• /
• 제22권2호
• /
• pp.167-174
• /
• 2022

Vehicular Ad hoc Networks are considered as special kind of Mobile Ad Hoc Networks. VANETs are a new emerging recently developed, advanced technology that allows a wide set of applications related to providing more safety on roads, more convenience for passengers, self-driven vehicles, and intelligent transportation systems (ITS). Delay Tolerant Networks (DTN) are networks that allow communication in the event of connection problems, such as delays, intermittent connections, high error rates, and so on. Moreover, these are used in areas that may not have end-to-end connectivity. The expansion from DTN to VANET resulted in Vehicle Delay Tolerant Networks (VDTN). In this approach, a vehicle stores and carries a message in its buffer, and when the opportunity arises, it forwards the message to another node. Carry-store-forward mechanisms, packets in VDTNs can be delivered to the destination without clear connection between the transmitter and the receiver. The primary goals of routing protocols in VDTNs is to maximize the probability of delivery ratio to the destination node, while minimizing the total end-to-end delay. DTNs are used in a variety of operating environments, including those that are subject to failures and interruptions, and those with high delay, such as vehicle ad hoc networks (VANETs). This paper discusses DTN routing protocols belonging to unicast delay tolerant position based. The comparison was implemented using the NS2 simulator. Simulation of the three DTN routing protocols GeOpps, GeoSpray, and MaxProp is recorded, and the results are presented.

• International Journal of Computer Science & Network Security
• /
• 제21권11호
• /
• pp.189-192
• /
• 2021

The article is devoted to the issue of the content of legal instruments in terms of tourism business, namely the problems of legal regulation of insurance in tourism. The analysis of the state of development of the problem in question shows that the issue of legal regulation of the insurance contract in general and the contract in tourism services, in general, is insufficiently studied. The article is devoted to topical issues of legal regulation of insurance in the field of tourism, the search for effective mechanisms to increase the liability of both underwriters and insurers. Therefore, insurance can be considered as one of the methods of preventing unfortunate consequences during the implementation of tourism activities. The author's vision of the content of the package of measures that can positively influence not only the development of the tourist industry in general but primarily to help identify those legal segments that need improvement in the future has been stated.

• International Journal of Computer Science & Network Security
• /
• 제22권9호
• /
• pp.343-347
• /
• 2022

To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

• International Journal of Computer Science & Network Security
• /
• 제22권8호
• /
• pp.81-86
• /
• 2022

Digital technologies in the regional sector of public administration are the basis for its reform and a potential example for the whole country on how to use the benefits of the "digital" world. The synergistic potential of social, mobile, "cloud" technologies, as well as data analysis technologies and the "Internet of Things" can collectively lead to transformational changes in public administration and in general, that is, make the use of digital technologies for the economic development of the region in the system of digitalization of public administration effective, reactive and valuable. Thus, the purpose of the study is to identify modern prospects and realities of the development of digital technologies for the economic development of the region in the system of digitalization of public administration. As a result of the study, the main mechanisms and systems of digital technologies for the economic development of the region in the system of digitalization of public administration were analyzed.

• International Journal of Computer Science & Network Security
• /
• 제22권3호
• /
• pp.61-66
• /
• 2022

Object classification is one of the main fields in neural networks and has attracted the interest of many researchers. Although there have been vast advancements in this area, still there are many challenges that are faced even in the current era due to its inefficiency in handling large data, linguistic and dimensional complexities. Powerful hardware and software approaches in Neural Networks such as Deep Neural Networks present efficient mechanisms and contribute a lot to the field of object recognition as well as to handle time series classification. Due to the high rate of accuracy in terms of prediction rate, a neural network is often preferred in applications that require identification, segmentation, and detection based on features. Neural networks self-learning ability has revolutionized computing power and has its application in numerous fields such as powering unmanned self-driving vehicles, speech recognition, etc. In this paper, the experiment is conducted to implement a neural approach to identify numbers in different formats without human intervention. Measures are taken to improve the efficiency of the machines to classify and identify numbers. Experimental results show the importance of having training sets to achieve better recognition accuracy.

• International Journal of Computer Science & Network Security
• /
• 제23권2호
• /
• pp.47-54
• /
• 2023

This article reviews recent advances and perspectives in neuroscience related to consciousness, cognition, and neural networks in the brain. The neural mechanisms underlying cognitive processes, such as perception, attention, memory, and decision-making, are explored. The article also examines how these processes give rise to our experience of consciousness. The implications of these findings for our understanding of the brain and its functions are presented, as well as potential applications of this knowledge in fields such as medicine, psychology, and artificial intelligence. Additionally, the article explores the concept of a quantum viewpoint concerning consciousness, cognition, and creativity and how incorporating DNA as a key element could reconcile classical and quantum perspectives on human behaviour, consciousness, and cognition, as explained by genomic psychological theory. Furthermore, the article explains how the human brain processes external stimuli through the sensory nervous system and how it can be simulated using an artificial neural network (ANN) consisting of one input layer, multiple hidden layers, and an output layer. The law of learning is also discussed, explaining how ANNs work and how the modification of weight values affects the output and input values. The article concludes with a discussion of future research directions in this field, highlighting the potential for further discoveries and advancements in our understanding of the brain and its functions.

• International Journal of Computer Science & Network Security
• /
• 제23권9호
• /
• pp.166-176
• /
• 2023

A scenario known as conflict in face recognition may arise as a result of some disparity-related issues (such as expression, distortion, occlusion and others) leading to a compromise of someone's identity or contradiction of the intended message. However, addressing this requires the determination and application of appropriate procedures among the various conflict theories both in terms of concepts as well as resolution strategies. Theories such as Marxist, Game theory (Prisoner's dilemma, Penny matching, Chicken problem), Lanchester theory and Information theory were analyzed in relation to facial images conflict and these were made possible by trying to provide answers to selected questions as far as resolving facial conflict is concerned. It has been observed that the scenarios presented in the Marxist theory agree with the form of resolution expected in the analysis of conflict and its related issues as they relate to face recognition. The study observed that the issue of conflict in facial images can better be analyzed using the concept introduced by the Marxist theory in relation to the Information theory. This is as a result of its resolution strategy which tends to seek a form of balance as result as opposed to the win or lose case scenarios applied in other concepts. This was also consolidated by making reference to the main mechanisms and result scenario applicable in Information theory.

• International Journal of Computer Science & Network Security
• /
• 제23권8호
• /
• pp.49-62
• /
• 2023

There has been a rapid increase in the creation and alteration of new malware samples which is a huge financial risk for many organizations. There is a huge demand for improvement in classification and detection mechanisms available today, as some of the old strategies like classification using mac learning algorithms were proved to be useful but cannot perform well in the scalable auto feature extraction scenario. To overcome this there must be a mechanism to automatically analyze malware based on the automatic feature extraction process. For this purpose, the dynamic analysis of real malware executable files has been done to extract useful features like API call sequence and opcode sequence. The use of different hashing techniques has been analyzed to further generate images and convert them into image representable form which will allow us to use more advanced classification approaches to classify huge amounts of images using deep learning approaches. The use of deep learning algorithms like convolutional neural networks enables the classification of malware by converting it into images. These images when fed into the CNN after being converted into the grayscale image will perform comparatively well in case of dynamic changes in malware code as image samples will be changed by few pixels when classified based on a greyscale image. In this work, we used VGG-16 architecture of CNN for experimentation.

• International Journal of Computer Science & Network Security
• /
• 제23권8호
• /
• pp.204-209
• /
• 2023

Dynamic Bandwidth Allocation (DBA) methods in telecommunication network & systems have emerged with mechanisms for sharing limited resources in a rapidly growing number of users in today's access networks. Since the DBA research trends are incredibly fast-changing literature where almost every day new areas and terms continue to emerge. Co - citation analysis offers a significant support to researchers to distinguish intellectual bases and potentially leading edges of a specific field. We present the visualization based analysis for DBA algorithms in telecommunication field using mainstream co-citation analysis tool-CiteSpace and web of science (WoS) analysis. Research records for the period of decade (2009-2018) for this analysis are sought from WoS. The visualization results identify the most influential DBA algorithms research studies, journals, major countries, institutions, and researchers, and indicate the intellectual bases and focus entirely on DBA algorithms in the literature, offering guidance to interested researchers on more study of DBA algorithms.