Kentaro Aburada

An Authentication Method Independent of Tap Operation on the Touchscreen of a Mobile Device

At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are generated by the electrical activity of muscle fibers during contraction, are detected over the skin surface. Muscle movement can be differentiated by analyzing the s-EMG. In this paper, a series of experiments was carried out to investigate the prospect of an authentication method using s-EMGs. Specifically, several gestures of the wrist were introduced, and the s-EMGs generated for each motion pattern were measured. We compared the s-EMG patterns generated by each subject with the patterns generated by other subjects. As a result, it was found that each subject has similar patterns that are different from those of other subjects. Thus, sEMGs can be used to confirm one’s identification for authenticating passwords on touchscreen devices.

Proposal of a Puzzle Authentication Method with Shoulder-surfing Attack Resistance

Recently, mobile terminals such as smartphones have come into widespread use. Most of such mobile terminals store several types of important data, such as personal information. Therefore, in order to prevent data theft, it is necessary to lock and unlock terminals using a personal authentication method such as personal identification numbers (PINs). However, most existing authentication methods have a common problem, referred to as shoulder-surfing in which authentication information is covertly obtained by peeking over the shoulder of a user as he/she completes the authentication sequence. In this paper, we propose a puzzle authentication method that is very simple and sufficiently secure, even when the authentication sequence is being watched. This method uses a grid-based authentication scheme in which a user selects four out of 16 panels, and four out of 16 positions. We also implemented the proposed method on a mobile terminal and evaluated it through experiments and questionnaire surveys.

On applying support vector machines to a user authentication method using surface electromyogram signals

At present, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are detected over the skin surface, are generated by the electrical activity of muscle fibers during contraction. Muscle movement can be differentiated by analyzing the s-EMG. Taking advantage of the characteristics, we proposed a method that uses a list of gestures as a password in the previous study. In this paper, we introduced support vector machines (SVM) for improvement of the method of identifying gestures. A series of experiments was carried out to evaluate the performance of the SVM based method as a gesture classifier and we also discussed its security.

A Study on a User Identification Method Using Dynamic Time Warping to Realize an Authentication System by s-EMG.

At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching.

Evaluation of User Identification Methods for Realizing an Authentication System Using s-EMG

At the present time, mobile devices such as tablet-type PCs and smart phones have widely penetrated into our daily lives. Therefore, an authentication method that prevents shoulder surfing is needed. We are investigating a new user authentication method for mobile devices that uses surface electromyogram (s-EMG) signals, not screen touching. The s-EMG signals, which are detected over the skin surface, are generated by the electrical activity of muscle fibers during contraction. Muscle movement can be differentiated by analyzing the s-EMG. Taking advantage of the caracteristics, we proposed a method that uses a list of gestures as a password in the previous study. In this paper, we employed support vector machines and attempted to improve the gesture recognition method by introducing correlation coefficient and cross-correlation. A series of experiments was carried out in order to evaluate the performance of the method.

A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method

Distributed Denial-of-Service (DDoS) attack detection systems are classified into a signature based approach and an anomaly based approach. However, such methods tend to suffer from low responsiveness. On the other hand, real-time burst detection which is used in data mining offers two advantages over traditional statistical methods. First, it can be used for real-time detection when an event is occurring, and second, it can work with less processing as information about events are compressed, even if a large number of events occur. Here, the authors add the function for attack detection in real-time burst detection technique, and propose a highly responsive DDoS attack detection technique. This paper performs experiments to evaluate its effectiveness, and discusses its detection accuracy and processing performance.

Evaluation of Farmers Market Information System to Connect with Some Social Stakeholders

A large part of the population in Tanzania consists of rural smallholder farmers. Due to lack of market information, farmers sell crops to middlemen at lower prices and hence don’t get enough profits. Previously we developed a WEB and SMS (Short Message Service) based Farmers Market Information System using a Waterfall model which automatically replies to farmers’ requests for market prices of crops through SMS. We then improved the system so that, farmers can access crop buyers’ details and crop demand reports through SMS while crop buyers can access farmers’ details and crop demand reports through SMS or WEB. We also evaluated the effectiveness of the system to crop buyers’ incomes and times for accessing market information after implementing the system in Tanzania in the SWAHILI language. In this paper we further evaluate the system effectiveness. Findings reveal that the system helped farmers to get improved incomes and access market information in shorter times. The system also helped farmers and crop buyers to sell and buy larger quantities of crops respectively. The findings also reveal that young people can learn and use the system more easily than old people. Users can also easily learn and use the system if they can read and write in the SWAHILI language regardless of their education levels.

Evaluation of Index Poisoning Method in Large Scale Winny Network

In recent years, P2P file-sharing networks are used all over the world. This has led to social problems such as the illegal distribution of copyrighted material and the leakage of personal information through computer viruses because P2P does not have a control function for file distribution. To address these issues, a control method called index poisoning has been studied. However, problems such as pollution in the network index and a need to increment control traffic have been reported when index poisoning is applied to a P2P file-sharing network. We propose a method that implements dynamic clustering to limit the range of index poisoning as a solution for these problems that also maintains the effectiveness of the control function. In this study, we implement index poisoning on the large-scale Winny network and evaluate the system performance.

Evaluation of Mouse Operation Authentication Method Having Shoulder Surfing Resistance

Currently, typing character strings on a keyboard is used for personal authentication for PC login and unlocking. Although some graphical and biometric-based methods have been developed, most of them have weak authentication strength or weak shoulder surfing resistance. In this paper, we propose a personal authentication method that the user specifies positions on a N × N matrix using mouse clicks. The user can hide the mouse during authentication easily, so the method has shoulder surfing resistance and can be used in public places. We developed the proposed method (pattern method), and two variations (number and color, and combination method), and performed user testing and shoulder surfing experiment to validate the proposed method. The proposed method was tested by 20 subjects in pattern method, 23 subjects in the number and color, and the combination method. The authentication success rate is 63.1%, 56.3% and 87.5% on each method. The specific rate by shoulder surfing is 1.4% in pattern method.

An Examination of CAPTCHA for Tolerance of Relay Attacks and Automated Attacks

CAPTCHA is a type of challenge response test used to distinguish human users from malicious computer programs such as bots, and is used to protect email, blogs, and other web services from bot attacks. So far, research on enhance of CAPTCHA’s resistance to bot attacks has been proceeded to counter advanced automated attacks method. However, an attack technique known as a relay attack has been devised to circumvent CAPTCHA. In this attack, since human solves CAPTCHA, the existing measures assuming bots have no effect on this attack. We designed a new CAPTCHA scheme for relay attacks tolerance and automated attacks tolerance. In this paper, we tested the robustness of the proposed method against several types of automated attacks. We constructed an experimental environment in which a relay attack can be simulated, and designed a series of experiments to evaluate the performance of the proposed method. As a result, we found that the proposed CAPTCHA scheme offers some of level of resistance to automated attacks and relay attacks.