• Title/Summary/Keyword: Fake information

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A Study on the Effect of the Document Summarization Technique on the Fake News Detection Model (문서 요약 기법이 가짜 뉴스 탐지 모형에 미치는 영향에 관한 연구)

  • Shim, Jae-Seung;Won, Ha-Ram;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.201-220
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    • 2019
  • Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

Behavior based Routing Misbehavior Detection in Wireless Sensor Networks

  • Terence, Sebastian;Purushothaman, Geethanjali
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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    • pp.5354-5369
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    • 2019
  • Sensor networks are deployed in unheeded environment to monitor the situation. In view of the unheeded environment and by the nature of their communication channel sensor nodes are vulnerable to various attacks most commonly malicious packet dropping attacks namely blackhole, grayhole attack and sinkhole attack. In each of these attacks, the attackers capture the sensor nodes to inject fake details, to deceive other sensor nodes and to interrupt the network traffic by packet dropping. In all such attacks, the compromised node advertises itself with fake routing facts to draw its neighbor traffic and to plunge the data packets. False routing advertisement play vital role in deceiving genuine node in network. In this paper, behavior based routing misbehavior detection (BRMD) is designed in wireless sensor networks to detect false advertiser node in the network. Herein the sensor nodes are monitored by its neighbor. The node which attracts more neighbor traffic by fake routing advertisement and involves the malicious activities such as packet dropping, selective packet dropping and tampering data are detected by its various behaviors and isolated from the network. To estimate the effectiveness of the proposed technique, Network Simulator 2.34 is used. In addition packet delivery ratio, throughput and end-to-end delay of BRMD are compared with other existing routing protocols and as a consequence it is shown that BRMD performs better. The outcome also demonstrates that BRMD yields lesser false positive (less than 6%) and false negative (less than 4%) encountered in various attack detection.

Fake GPS Detection for the Online Game Service on Server-Side (모의 위치 서비스를 이용한 온라인 게임 악용 탐지 방안)

  • Han, Jaehyeok;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.5
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    • pp.1069-1076
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    • 2017
  • Recently $Pok\acute{e}mon$ GO implements an online game with location-based real time augmented reality on mobile. The correct play of this game should be based on collecting the $Pok\acute{e}mon$ that appears as the user moves around by foot, but as the popularity increases, it appears an abuse to play easily. Many people have used an application that provides a mock location service such as Fake GPS, and these applications can be judged to be cheating in online games because they can play games in the house without moving. Detection of such cheating from a client point of view (mobile device) can consume a large amount of resources, which can reduce the speed of the game. It is difficult for developers to apply detection methods that negatively affect game usage and user's satisfaction. Therefore, in this paper, we propose a method to detect users abusing mock location service in online game by route analysis using GPS location record from the server point of view.

A New Sender-Side Public-Key Deniable Encryption Scheme with Fast Decryption

  • Barakat, Tamer Mohamed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3231-3249
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    • 2014
  • Deniable encryption, introduced in 1997 by Canetti, Dwork, Naor, and Ostrovsky, guarantees that the sender or the receiver of a secret message is able to "fake" the message encrypted in a specific ciphertext in the presence of a coercing adversary, without the adversary detecting that he was not given the real message. Sender - side deniable encryption scheme is considered to be one of the classification of deniable encryption technique which defined as resilient against coercing the sender. M. H. Ibrahim presented a sender - side deniable encryption scheme which based on public key and uncertainty of Jacobi Symbol [6]. This scheme has several problems; (1) it can't be able to derive the fake message $M_f$ that belongs to a valid message set, (2) it is not secure against Quadratic Residue Problem (QRP), and (3) the decryption process is very slow because it is based dramatically on square root computation until reach the message as a Quadratic Non Residue (QNR). The first problem is solved by J. Howlader and S. Basu's scheme [7]; they presented a sender side encryption scheme that allows the sender to present a fake message $M_f$ from a valid message set, but it still suffers from the last two mentioned problems. In this paper we present a new sender-side deniable public-key encryption scheme with fast decryption by which the sender is able to lie about the encrypted message to a coercer and hence escape coercion. While the receiver is able to decrypt for the true message, the sender has the ability to open a fake message of his choice to the coercer which, when verified, gives the same ciphertext as the true message. Compared with both Ibrahim's scheme and J. Howlader and S. Basu's scheme, our scheme enjoys nice two features which solved the mentioned problems: (1) It is semantically secure against Quadratic Residue Problem; (2) It is as fast, in the decryption process, as other schemes. Finally, applying the proposed deniable encryption, we originally give a coercion resistant internet voting model without physical assumptions.

Fake Discrimination using Time Information in CNN-based Signature Recognition (CNN 기반 서명인식에서 시간정보를 이용한 위조판별)

  • Choi, Seouing-Ho;Jung, Sung Hoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.07a
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    • pp.293-294
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    • 2017
  • 본 논문에서는 CNN 기반 서명인식에서 시간정보를 이용하여 위조서명을 보다 정확하게 판별하는 방법을 제안한다. 시간정보를 이용하는 첫 번째 방법은 서명하는 전체 시간을 동일한 개수의 등 간격으로 나누어 각각의 이미지를 얻고 이를 합성하여 이용하는 방법이다. 두 번째 방법은 동일한 개수의 등 간격으로 나누어진 각각의 이미지를 CNN-LSTM 으로 판별하는 방법이다. 동일한 개수의 등 간격으로 나누어진 이미지들에는 서명의 속도에 따른 모양의 차이가 발생하기 때문에 비록 최종 서명의 모양이 원본과 매우 유사하다고 하더라도 속도가 다른 경우 위조임을 판별할 수 있다. 두 명의 서명에 대하여 실험을 한 결과 최종 서명이 매우 유사하더라도 속도가 다른 경우 위조로 판별할 수 있음을 보였다. 다만 이미지 합성 과정에 만들어진 새로운 정보로 인하여 진짜 서명을 가짜로 판별할 수 있는 가능성도 늘어날 수 있음을 확인하였다.

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Toward Trustworthy Social Network Services: A Robust Design of Recommender Systems

  • Noh, Giseop;Oh, Hayoung;Lee, Kyu-haeng;Kim, Chong-kwon
    • Journal of Communications and Networks
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    • v.17 no.2
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    • pp.145-156
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    • 2015
  • In recent years, electronic commerce and online social networks (OSNs) have experienced fast growth, and as a result, recommendation systems (RSs) have become extremely common. Accuracy and robustness are important performance indexes that characterize customized information or suggestions provided by RSs. However, nefarious users may be present, and they can distort information within the RSs by creating fake identities (Sybils). Although prior research has attempted to mitigate the negative impact of Sybils, the presence of these fake identities remains an unsolved problem. In this paper, we introduce a new weighted link analysis and influence level for RSs resistant to Sybil attacks. Our approach is validated through simulations of a broad range of attacks, and it is found to outperform other state-of-the-art recommendation methods in terms of both accuracy and robustness.

Research of method prevent to illegal use of Credit Card (신용카드 부정사용 거래 예방을 위한 대처 방안 연구)

  • Pu, Chang Hee;Jun, Moon Seog
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.3
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    • pp.147-156
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    • 2012
  • Most people in our society use credit card instead of cash or check, so credit card is very important economic method. Credit card supposed to be safe, but hackers hack credit card for illegal deal. Also hackers make fake credit card and issue fake credit card to other people. In this thesis it will study and analyze damage case for safe credit card deal. It will use safe credit card system to insert variety of information and data of using pattern in artificial intelligence network, so print out the possibility of risk and monitor the risk of credit card user's deal pattern, so if one of user's pattern is different than normal pattern, it will pop up message in consultant's screen. This thesis will study and suggest way of prevent from illegal deal and user friendly credit card checking system.

Current Issues with the Big Data Utilization from a Humanities Perspective (인문학적 관점으로 본 빅데이터 활용을 위한 당면 문제)

  • Park, Eun-ha;Jeon, Jin-woo
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.125-134
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    • 2022
  • This study aims to critically discuss the problems that need to be solved from a humanities perspective in order to utilize big data. It identifies and discusses three research problems that may arise from collecting, processing, and using big data. First, it looks at the fake information circulating with regard to problems with the data itself, specifically looking at article-type advertisements and fake news related to politics. Second, discrimination by the algorithm was cited as a problem with big data processing and its results. This discrimination was seen while searching for engineers on the portal site. Finally, problems related to the invasion of personal related information were seen in three categories: the right to privacy, the right to self-determination of information, and the right to be forgotten. This study is meaningful in that it points out the problems facing in the aspect of big data utilization from the humanities perspective in the era of big data and discusses possible problems in the collection, processing, and use of big data, respectively.

Multi-modal Authentication Using Score Fusion of ECG and Fingerprints

  • Kwon, Young-Bin;Kim, Jason
    • Journal of information and communication convergence engineering
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    • v.18 no.2
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    • pp.132-146
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    • 2020
  • Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

Harmful Disinformation in Southeast Asia: "Negative Campaigning", "Information Operations" and "Racist Propaganda" - Three Forms of Manipulative Political Communication in Malaysia, Myanmar, and Thailand

  • Radue, Melanie
    • Journal of Contemporary Eastern Asia
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    • v.18 no.2
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    • pp.68-89
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    • 2019
  • When comparing media freedom in Malaysia, Myanmar, and Thailand, so-called "fake news" appears as threats to a deliberative (online) public sphere in these three diverse contexts. However, "racist propaganda", "information operations" and "negative campaigning" might be more accurate terms that explain these forms of systematic manipulative political communication. The three cases show forms of disinformation in under-researched contexts and thereby expand the often Western focused discourses on hate speech and fake news. Additionally, the analysis shows that harmful disinformation disseminated online originates from differing contextual trajectories and is not an "online phenomenon". Drawing on an analysis of connotative context factors, this explorative comparative study enables an understanding of different forms of harmful disinformation in Malaysia, Myanmar, and Thailand. The connotative context factors were inductively inferred from 32 expert interviews providing explanations for the formation of political communication (control) mechanisms.