Quoc Nguyen

The Graduate University for Advanced Studies, SOKENDAI | SOKENDAI · Department of Informatics

Adversarial attacks reveal serious flaws in deep learning models. More dangerously, these attacks preserve the original meaning and escape human recognition. Existing methods for detecting these attacks need to be trained using original/adversarial data. In this paper, we propose detection without training by voting on hard labels from predictions...

Machine-translated text plays an important role in modern life by smoothing communication from various communities using different languages. However, unnatural translation may lead to misunderstanding, a detector is thus needed to avoid the unfortunate mistakes. While a previous method measured the naturalness of continuous words using a N-gram la...

An adversarial attack generates harmful text that fools a target model. More dangerously, this text is unrecognizable by humans. Existing work detects adversarial text and corrects a target’s prediction by identifying perturbed words and changing them into their synonyms, but many benign words are also changed. In this paper, we directly detect adv...

There are two cases describing how a classifier processes input text, namely, misclassification and correct classification. In terms of misclassified texts, a classifier handles the texts with both incorrect predictions and adversarial texts, which are generated to fool the classifier, which is called a victim. Both types are misunderstood by the v...

Homograph attack is a way that attackers deceive victims about which website domain name they are communicating with by exploiting the fact that many characters look alike. The attack becomes serious and is raising broad attention when recently many brand domains have been attacked such as Apple Inc., Adobe Inc., Lloyds Bank, etc. We first design a...

Homograph attack is a way that attackers deceive victims about which website domain name they are communicating with by exploiting the fact that many characters look alike. The attack becomes serious and is raising broad attention when recently many brand domains have been attacked such as Apple Inc., Adobe Inc., Lloyds Bank, etc. We first design a...

Attackers create adversarial text to deceive both human perception and the current AI systems to perform malicious purposes such as spam product reviews and fake political posts. We investigate the difference between the adversarial and the original text to prevent the risk. We prove that the text written by a human is more coherent and fluent. Mor...

Machine-translated text plays a crucial role in the communication of people using different languages. However, adversaries can use such text for malicious purposes such as plagiarism and fake review. The existing methods detected a machine-translated text only using the text's intrinsic content, but they are unsuitable for classifying the machine-...

Visual homograph attack is a way that the attackers deceive victims about what domain they are communicating with by exploiting the fact that many characters look alike. The attack is growing into a serious problem and raising broad attention in reality when recently many brand domains have been attacked such as apple.com (Apple Inc.), adobe.com (A...

Gait anonymization for protecting a person’s identity against gait recognition while maintaining naturalness is a new research direction. It can be used to protect the identity of people in videos to be posted on social networks, in police videos that require redaction, and in videos obtained from surveillance systems. We have developed a spatio-te...

Machine-translated text plays an important role in modern life by smoothing communication from various communities using different languages. However, unnatural translation may lead to misunderstanding, a detector is thus needed to avoid the unfortunate mistakes. While a previous method measured the naturalness of continuous words using a N-gram la...

Homograph attack is a way that attackers deceive victims about which domain they are communicating with by exploiting the fact that many characters look alike. The attack becomes serious and is raising broad attention when recently many brand domains have been attacked such as Apple Inc., Adobe Inc., Lloyds Bank, etc. We first design a survey of hu...

We have developed a method for extracting the coherence features from a paragraph by matching similar words in its sentences. We conducted an experiment with a parallel German corpus containing 2000 human-created and 2000 machine-translated paragraphs. The result showed that our method achieved the best performance (accuracy = 72.3%, equal error ra...

Discriminating between computer-generated images (CGIs) and photographic images (PIs) is not a new problem in digital image forensics. However, with advances in rendering techniques supported by strong hardware and in generative adversarial networks, CGIs are becoming indistinguishable from PIs in both human and computer perception. This means that...

Making computer-generated (CG) images more difficult to detect is an interesting problem in computer graphics and security. While most approaches focus on the image rendering phase, this paper presents a method based on increasing the naturalness of CG facial images from the perspective of spoofing detectors. The proposed method is implemented usin...

Discriminating between computer-generated images and natural ones is a crucial problem in digital image forensics. Facial images belong to a special case of this problem. Advances in technology have made it possible for computers to generate realistic multimedia contents that are very difficult to distinguish from non-computer generated contents. T...

As of today, millions of people share messages via online social networks, some of which probably contain sensitive information. An adversary can collect these freely available messages and specifically analyze them for privacy leaks, such as the users’ location. Unlike other approaches that try to detect these leaks using complete message streams,...

While online social networking is a popular way for people to share information, it carries the risk of unintentionally disclosing personal information. One way to reduce this risk is to anonymize personal information in messages before they are posted. Furthermore, if personal information is somehow disclosed, the person who disclosed it should be...

Time-related information in message posted on-line is one type of sensitive information targeted by attackers, one reason that sharing information online can be risky. Therefore, time information should be anonym zed before it is posted in online social networks (OSNs). One approach to reducing the risk is to anon Mize the personal information by r...

The application of fingerprinting techniques to relational data cannot protect personal information against a collusion attack, in which the attacker has access to a set of published data. The general fingerprinting techniques such as Li et at.'s, Guo et al.'s, and Schrittwieser et al.'s focus on detecting the traitor, who leaked the data. Among th...

Time-related information in text posted on-line is one type of personal information targeted by attackers, one reason that sharing information online can be risky. Therefore, time information should be anonymized before it is posted on social networking services. One approach to anonymizing information is to replace sensitive phrases with anonymous...

Social networking services (SNSs) support communication among people via the Internet. However, sensitive information about a user can be disclosed by the user's SNS friends. This makes it unsafe for a user to share information with friends in different groups. Moreover, a friend who has disclosed a user's information is difficult to identify. One...

One approach to overcoming the problem of too much information about a user being disclosed on social networking services (by the user or by the user's friends) through natural language texts (blogs, comments, status updates, etc.) is to anonymize the texts. However, determining which information is sensitive and should thus be anonymized is a chal...

Users often share same text information for friends in different level groups on social networking services (SNSs). Moreover, it does not identify a person who has revealed the text. Some approaches overcome this problem by using anonymity text, but most methods for doing this has focused on databases. However, information about a user in SNSs is g...