• Title/Summary/Keyword: Personal Network Exposure

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Research on Military SNS Protection Profile for National defense (국방정보보호를 위한 군(軍) SNS 보호프로파일(PP) 개발에 관한 연구)

  • Yu, DeokHoon;Kim, SeungJoo
    • Journal of Internet Computing and Services
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    • v.14 no.1
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    • pp.41-52
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    • 2013
  • Social Network Service(SNS) have become very popular during the past few years. Also SNS, an current communication platform, greatly contributes to transmit the information rapidly and strengthen a sense of community and fellowship in military service. however it has vulnerable factors. For example, invasion of privacy, exposure of personal information and military data. In this particular case, it is a deathblow to the military service. Military Social Network Service require to protect the military security threats and disclosure of defense secrets. For such reasons we need the secure SNS that protects from any attacks or vulnerable factors. We present classification of functional type and analysis the SNS architecture. The goal of this work is propose military SNS security functional requirements for practical use safely.

A Design of KDPC(Key Distributed Protocol based on Cluster) using ECDH Algorithm on USN Environment (USN 환경에서 ECDH 알고리즘을 이용한 KDPC(Key Distribution Protocol based on Cluster) 설계)

  • Jeong, Eun-Hee;Lee, Byung-Kwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.856-858
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    • 2013
  • The data which is sensed on USN(Ubiquitous Sensor Network) environment is concerned with personal privacy and the secret information of business, but it has more vulnerable characteristics, in contrast to common networks. In other words, USN has the vulnerabilities which is easily exposed to the attacks such as the eavesdropping of sensor information, the distribution of abnormal packets, the reuse of message, an forgery attack, and denial of service attacks. Therefore, the key is necessarily required for secure communication between sensor nodes. This paper proposes a KDPC(Key Distribution Protocol based on Cluster) using ECDH algorithm by considering the characteristics of sensor network. As a result, the KDPC can provide the safe USN environment by detecting the forgery data and preventing the exposure of sensing data.

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Study of effectiveness for the network separation policy of financial companies (금융회사 망분리 정책의 효과성 연구)

  • Cho, Byeong-Joo;Yun, Jang-Ho;Lee, Kyeong-Ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.1
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    • pp.181-195
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    • 2015
  • Financial industries have operated internal and external network with an unified system for continual business process of customers and other organizations in the past. The financial supervising authority requires more technical and managerial protecting policy to financial industries related to the exposure as danger of external attacks or information leakage. Financial industries performed network separation into internal business and external internet networks for protecting IT assets from malware infection accessing internet or hacking attacks and prohibiting leakage of customers' personal and financial information following financial supervising authority and redefine security policy to fit on network separated-condition. In this study, effectiveness for network separation policy was examined on malware inflow and verified that malware inflow in all routes can be blocked by the policy with analyzing operration data of a financial company, estimating network separation. Result of this study proves that malware infection route by portable storages was not completely blocked even on adapting network-separated condition. As a solution for this, efficient security policy would be suggested in this paper as controlling portable storages for maximizing effectiveness of network separation.

Changes in the marketing direction and form of exhibitions using social media

  • Im-yeoreum Kim;Gi-Hwan Ryu
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.2
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    • pp.268-272
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    • 2023
  • With the development of SNS, companies and individuals are actively marketing through social media to develop their own products. It is also important to post posts promoting on simple SNS or to show a lot of exposure using algorithms, but customers upload reviews or proof shots of the product on their own, naturally increasing the exposure of the product and increasing the purchasing power of potential customers. As the number of products that users want to purchase through SNS is increasing, they want to access and purchase not only tangible products such as goods and food, but also intangible services through SNS. In this paper, we would like to study exhibitions that have both tangible and intangible characteristics. SNS accounts that mainly introduce these products by searching for reviews have been created while spending leisure time such as exhibitions and fairs, reducing the hassle of searching for personal interests on search engines, and providing prices and reviews from the exhibition's schedule, lowering entry barriers and increasing purchasing power. Using this point, many exhibitions not only display works, but also open various experience centers, and create a photo zone or a unique exhibition hall atmosphere to attract many customers. In this study, we study the impact of SNS on the leisure culture of exhibition. The marketing direction in the situation where SNS marketing is becoming the mainstream is presented, and the change in the form of exhibition is described and presented as an academic approach.

Spam Image Detection Model based on Deep Learning for Improving Spam Filter

  • Seong-Guk Nam;Dong-Gun Lee;Yeong-Seok Seo
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.289-301
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    • 2023
  • Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

Analysis of the Vulnerability of the IoT by the Scenario (시나리오 분석을 통한 사물인터넷(IoT)의 취약성 분석)

  • Hong, Sunghyuck;Sin, Hyeon-Jun
    • Journal of the Korea Convergence Society
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    • v.8 no.9
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    • pp.1-7
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    • 2017
  • As the network environment develops and speeds up, a lot of smart devices is developed, and a high-speed smart society can be realized while allowing people to interact with objects. As the number of things Internet has surged, a wide range of new security risks and problems have emerged for devices, platforms and operating systems, communications, and connected systems. Due to the physical characteristics of IoT devices, they are smaller in size than conventional systems, and operate with low power, low cost, and relatively low specifications. Therefore, it is difficult to apply the existing security solution used in the existing system. In addition, IoT devices are connected to the network at all times, it is important to ensure that personal privacy exposure, such as eavesdropping, data tampering, privacy breach, information leakage, unauthorized access, Significant security issues can arise, including confidentiality and threats to facilities. In this paper, we investigate cases of security threats and cases of network of IoT, analyze vulnerabilities, and suggest ways to minimize property damage by Internet of things.

De-Identified Face Image Generation within Face Verification for Privacy Protection (프라이버시 보호를 위한 얼굴 인증이 가능한 비식별화 얼굴 이미지 생성 연구)

  • Jung-jae Lee;Hyun-sik Na;To-min Ok;Dae-seon Choi
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.201-210
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    • 2023
  • Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

Factors Influencing the Adoption of Location-Based Smartphone Applications: An Application of the Privacy Calculus Model (스마트폰 위치기반 어플리케이션의 이용의도에 영향을 미치는 요인: 프라이버시 계산 모형의 적용)

  • Cha, Hoon S.
    • Asia pacific journal of information systems
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    • v.22 no.4
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    • pp.7-29
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    • 2012
  • Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

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Perceptional Change of a New Product, DMB Phone

  • Kim, Ju-Young;Ko, Deok-Im
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.3
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    • pp.59-88
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    • 2008
  • Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

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