Data visualization has become a useful tool to effectively communicate information and is widely used not only by experts but also at a general level. However, it is dangerous that it is as efficient as it is to transmit false information. All data visualizations have hidden intent with powerful messages by editor. Building a system that grasps these intentions helps to understand the thoughts of groups and individuals. Most of the existing research focuses on effective data visualization methods and methods of expression. The more various visualization methods, the more likely the data will be distorted. In this paper, we present an analysis of deceptive data visualization in a goal-oriented environment. Based on the vulnerability of human cognitive processing, we classify the attack types and identify what tricks occur in the context of data visualization. This study suggests the first step in studying the case of aggressive visualization and opens the way for further research.
Smartphones have all the recent technology integration and NFC (Near Field Communication) Technology is one of them and become an essential these days. Despite using smartphones with NFC technology widely, not many security vulnerabilities have been discovered. This paper attempts to identify characteristics and various services in NFC technology, and to present a wide range of security vulnerabilities, prevention, and policies especially in NFC Contactless technology. We describe a security vulnerability and an possible threat based on human vulnerability and traditional malware distribution technic using Peer-to-Peer network on NFC-Enabled smartphones. The vulnerability is as follows: An attacker creates a NFC tag for distributing his or her malicious code to unspecified individuals and apply to hidden spot near by NFC reader in public transport like subway system. The tag will direct smartphone users to a certain website and automatically downloads malicious codes into their smartphones. The infected devices actually help to spread malicious code using P2P mode and finally as traditional DDoS attack, a certain target will be attacked by them at scheduled time.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2018.10a
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pp.152-155
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2018
Over the past years, Link Flooding Attacks (LFAs) have been introduced as new network threats. LFAs are indirect DDoS attacks that selectively flood intermediate core links, while legacy DDoS attacks directly targets end points. Flooding bandwidth in the core links results in that a wide target area is affected by the attack. In the traditional network, mitigating LFAs is a challenge since an attacker can easily construct a link map that contains entire network topology via traceroute. Security researchers have proposed many solutions, however, they focused on reactive countermeasures that respond to LFAs when attacks occurred. We argue that this reactive approach is limited in that core links are already exposed to an attacker. In this paper, we present SDHoneyNet that prelocates vulnerable links by computing static and dynamic property on Software-defined Networks (SDN). SDHoneyNet deploys Honey Topology, which is obfuscated topology, on the nearby links. Using this approach, core links can be hidden from attacker's sight, which leads to effectively building proactive method for mitigating LFAs.
Journal of the Institute of Convergence Signal Processing
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v.10
no.4
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pp.214-219
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2009
This paper proposes a watermarking algorithm considering the frequency characteristics of Haegeum sounds for copyright protection of digital Haegeum sound contents. The harmonics of Haegeum sounds commonly have large magnitude values in 1500Hz~2000Hz and 2800Hz~3500Hz so that those bands are selected to embed a watermark. The proposed method computes the FFT (fast Fourier transform) of the original sound signal and embeds the watermark bits generated by PN (pseudo noise) sequence into the harmonics in the selected bands. Furthermore, the proposed method is robust to lowpass filter, bandpass filter, cropping, noise addition, MP3 compression attacks and the maximum BER (bit error rate) is 1.41% after lowpass filter attack. To measure the quality of the watermarked sound, subjective listening test, MUSHRA (multiple stimuli with hidden reference and anchor), was conducted. The mean value of MUSHRA listening test is bigger than 98 and 96.67 for every Haegeum sounds and Korean classical music with Haeguem, respectively.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.14
no.2
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pp.109-114
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2021
As various users increase in a network environment, it is difficult to protect sensitive and confidential information transmitted and received from attackers. Concealing bitwise secret data in an image using the LSB technique can be very vulnerable to attack. To solve this problem, a hybrid method that combines encryption and information hiding is used. Therefore, an effective method for users to securely protect secret messages and implement secret communication is required. A new approach is needed to improve security and imperceptibility to ensure image quality. In this paper, I propose an LSB steganography technique that hides Hangul messages in a cover image based on MSB and LSB. At this time, after separating Hangul into chosung, jungsung and jongsung, the secret message is applied with Exclusive-OR or Exclusive-NOR operation depending on the selected MSB. In addition, the calculated secret data is hidden in the LSB n bits of the cover image converted by Fibonacci technique. PSNR was used to confirm the effectiveness of the applied results. It was confirmed 41.517(dB) which is suitable as an acceptable result.
Journal of the Korea Institute of Information Security & Cryptology
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v.33
no.4
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pp.621-631
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2023
Adversarial training improves the robustness of deep neural networks for adversarial examples. However, the previous adversarial training method focuses only on the adversarial loss function, ignoring that even a small perturbation of the input layer causes a significant change in the hidden layer features. Consequently, the accuracy of a defended model is reduced for various untrained situations such as clean samples or other attack techniques. Therefore, an architectural perspective is necessary to improve feature representation power to solve this problem. In this paper, we apply an attention module that generates an attention map of an input image to a general model and performs PGD adversarial training upon the augmented model. In our experiments on the CIFAR-10 dataset, the attention augmented model showed higher accuracy than the general model regardless of the network structure. In particular, the robust accuracy of our approach was consistently higher for various attacks such as PGD, FGSM, and BIM and more powerful adversaries. By visualizing the attention map, we further confirmed that the attention module extracts features of the correct class even for adversarial examples.
Recently, for the advancement of embedded technology about mobile device, a new kind of service, mash-up is appeared. It is service or application combining multimedia content making tool or device and web-GIS(geographic information system) service in the mobile environment. This service can be ease to use for casual user and can apply in various ways. So, It is served in web 2.0 environment actively. But, in the mashup service, because generated multimedia contents linked with web map are new type of multimedia contents which include user's migration routes in the space such as GPS coordinates. Thus, there are no protection ways for intellectual property created by GIS web-map service users and user's privacy. In this paper, we proposed a location and user information hiding scheme for GIS web-map service. This scheme embeds location and user information into a picture that is taken by camera module on the mobile phone. It is not only protecting way for user's privacy but is also tracing way against illegal photographer who is peeping person through hidden camera. And than, we also realized proposed scheme on the mobile smart phone. For minimizing margin of error about location coordinate value against contents manipulating attacks, GPS information is embedded into chrominance signal of contents considering weight of each digit about binary type of GPS coordinate value. And for tracing illegal photographer, user information such as serial number of mobile phone, phone number and photographing date is embedded into frequency spectrum of contents luminance signal. In the experimental results, we confirmed that the error of extracted information against various image processing attacks is within reliable tolerance. And after file format translation attack, we extracted embedded information from the attacked contents without no damage. Using similarity between extracted one and original templete, we also extracted whole information from damaged chrominance signal of contents by various image processing attacks.
This study was conducted focusing on the role of auteurism animation. The purpose of auteurism animation is to criticize irregularities of a society in witty and fierce way through satires from the sharp perspectives of a animator that is not bound by tastes of people or the interests or standpoints of specific groups, and thus to induce positive changes in a society as a purifier. In the context, this study investigated satires shown in by Jan Svankmajer and by Norman Mclaren among the animators who utilize animation as a tool to produce social meaning. As a result, the following characteristics and meanings were found. First, Dimensions of Dialogue is an animation that satires absurdity and irregularities of a human society in symbolic and exceptional way through directing by segmentations of images and omnibus structures. The satire carries the lesson of improvement in the hidden part of cynical attack to history, society, and human beings. It also maximizes absolute reality and engagement of images of Jan Svankmajer through unique and grotesque images of the animator such as alienated world, confusing shapes, and amusement of irregularities. Second, the movie, is an exemplary animation that applied core concept of animation through pixilation techniques based on an event story structure by causal relationship. It satires the changing process of a good man to violent madness through confrontation and conflicts for material desires, with exaggerated slipstick movements and humors as a black comedy. The satire methods of both animation works are delivered through unique image styles and symbolic wordage of the animators who triggered ironical laughter in attacking humanism and moral insensitivity that might be felt seriously otherwise. That is, the animators try to show the positive will for changing the society to a sound one through the form of negativity in terms of moral perspective in animation rather than destruction against the target. As such, the satires in both works worked as an auteurism allegory that maximizes social functions and artistic influence of animation.
It can be assumed that the reasons why the animation characters, 'Olaf (in Frozen Kingdom)' and 'Minions (in Super Bad)', etc., which were very successful in the merchandising market while having won the popularity better than the main characters are very popular even though such characters appeared only by playing a funny role while assisting the adventures of the main characters are not only because of their cute appearances but also because such characters have their own core features in their inner world as the transitional object-characters. Simply expressing, a 'Transitional Object' as a concept suggested by a child psychologist, 'Donald Winnicott', means a lovey doll or an imaginary friend which temporarily replaces an infant's mother during the procedure when the infant is mentally separated from its mother. However, in case that the theory of transitional objects was applied directly to many narrative content characters for doing a study, there must have been done some studies in advance for establishing some new criteria and indexes related to the transitional object-characters of such narrative contents. Accordingly, while thinking that the 'emotional relationship' between a growth-subject and a growth mediator must be dealt with as the most important content in order to define a transitional object-character in a narration clearly, this researcher established some emotional index for judging the propensities of a transitional object-character on the basis of such way of thinking. The index is composed of 4 kinds of emotional roles (quasi-family member, growth mediator, lovey doll, an imaginary friend), 6 kinds of emotional supports (hugging, protecting, accepting, giving the initiative, improving the relationship and mutual supervising) and 4 kinds of emotional impressions (impression by contacting, impression to protect and impression accepting an attack). In case that some main characters of a family feature animation, 'Inside Out', are analyzed while the index mentioned above is applied, it was found that 'Bing Bong' and 'Sadness' have a high propensity as a transitional object-character. Especially, it could be inversely inferred in which ways some good transitional object-characters can help the narrations on growth of a family feature animation by taking a look at the character, 'Sadness' that has the highest propensity as a transitional object-character. The transitional object-character, 'Sadness' assists the narration on growth internally and externally by helping the internal maturity of a growth-subject in a way of projecting the tasks for the internal maturity of a growth-subject while helping the growth-subject to be successfully externally in a way of providing the growth-subject with some kinds of facilitating emotion. As the results from this Study, since such kinds of emotional experiences provided by such transitional object-characters are displaced to not only the relevant growth-subjects but also the audience who are emphasized with such growth-subjects as they are, such transitional object-characters play a role of hidden benefactors who induce some immersion into the narrations and provide child and adult audience with various layers of emotional satisfaction.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (
) were the topic modeling results for each research topic (
) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.
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