Ryuya Uda

A method of appliance detection based on features of power waveform

We propose a method to detect the model, location and activity of a conventional home electric appliance. Waveforms of current consumed by appliances vary according to their configurations and activity. We define feature parameters for detecting the status of appliances. A current detector, microcomputer and transmitter are equipped in a power outlet in order to measure consumed current, calculate the feature parameters, and transmit the results to a home server. Feature parameters of appliances in the home are learned and stored in a home server in advance. The home server compares the feature parameters of known appliances with the received feature parameters to detect an appliances model and activity. User could control appliances from out of the house via the Internet.

Proposal of Movie CAPTCHA Method Using Amodal Completion

Web services accounts have recently been automatically acquired in large quantities by bot-programs, which are malicious. Furthermore, the acquired accounts have been used for spamming, which is a problem for service operators or Internet users. Completely Automated Public Turing Tests To Tell Computers and Humans Apart (CAPTCHAs) have generally been adopted for Web Services as a method of preventing Web services accounts from being acquired. These are Turing tests for users of Web services to distinguish between humans and bot-programs. There are several types of methods in CAPTCHAs, but the most typical in this field are text-based. However, these methods can be decoded with a high degree of probability, because of the OCR technology that has evolved. Much research on resolving this problem has been proposed. For example, one method in this research adds distortion to characters to make it difficult to analyze them with OCR. Despite this research, OCR has a higher success rate than humans. Thus, we propose a practical method for CAPTCHA in this paper in which only humans can provide correct answers by applying a modal completion.

Text-Based CAPTCHA Using Phonemic Restoration Effect and Similar Sounds

In Recent years, bot (robot) program has been one of the problems on the web. Some kinds of the bots acquire accounts of web services in order to use the accounts for SPAM mails, phishing, etc. CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is one of the countermeasures for preventing bots from acquiring the accounts. Text-based CAPTCHA is especially implemented on almost all famous web services. However, CAPTCHA faces a problem that evolution of algorithms for analysis of printed characters disarms text-based CAPTCHA. Of course, stronger distortion of characters is the easiest solution of the problem. However, it makes recognition of characters difficult not only for bots but also for human beings. Therefore, in this paper, we propose a new CAPTCHA with higher safety and convenience. Especially, we focus on the human abilities of phonemic restoration and recognition of similar sounds, and adopt the abilities in the propose CAPTCHA. The proposed CAPTCHA makes machinery presumption difficult for bots, while providing easy recognition for human beings.

A low cost privacy protection method for SNS by using Bloom filter

Recently, a number of online services has developed due to the spread of the Internet and smartphones. Especially, the SNS that the place of communication among people is popular and high rate utilization. However, as the services have developed, problems such as flame war or web stalker due to SNS has increased. When the problems have occurred, the private information had been identified from the posted information such as address, employment place, and commute place. In some related works are propose method to prevent leak of personal information for providers and server administrators. But, these methods require high calculation cost. Therefore, we propose a system to lower the calculation cost by using a Bloom filter. In addition, it inhibit the use of a lot of content such as unregistered search service or community.

Personal identification by flick input with acceleration sensor

Flick input is usual input method on touch panels of smartphones. Inputted characters are decided by a touched place on the screen and by a moving direction from the place. There is a research by Terabayashi et al. In which users are identified with characteristics of flick input of them. Kobata et al. Improve the identification method by using 3D acceleration sensor. However, they use the acceleration sensor to acquire posture of users. In this paper, we improve the method by using 3D acceleration sensor to increase accuracy of personal identification.

Privacy Protection on Transfer System of Automated Teller Machine from Brute Force Attack

Currently, an authentication system used in banks is to protect assets of users. However, these systems are weak against the peeping attack. That is high risk. Therefore, we proposed that a user safely enters credentials and information to transfer money after launching Live CD on stand-alone in place without risk of peeping attack such as a home. The entered information is encrypted by common key crypto system and stored in a QR code. If the peeping attack occurred, this information were protected by using the QR code, also can be high-speed processing. However, if QR codes ware obtained by unauthorized users, they can find out privacy information of owner by reading QR code to a ATM. Therefore, we propose that the system is appended function for privacy protection to the previous method.

Effective CAPTCHA with Amodal Completion and Aftereffects

Accounts on web services are always exposed to the menace of attacks. Especially, a large number of accounts can be used for unfair uses such as stealth marketing or SPAM attacks. Needless to say, acquisition of those accounts and attacks are automatically done by software programs called bots. Therefore, a technology called CAPTCHA is usually used in the acquisition of accounts for web services in order to distinguish human beings from bots. The most popular kind of CAPTCHA methods is text-based CAPTCHA in which distorted alphabets and numbers appear with obstacles or noise. However, it is known that all of text-based CAPTCHA algorithms can be analyzed by computers. In addition, too much distortion or noise prevents human beings from alphabets or numbers. There are other kinds of CAPTCHA methods such as image CAPTCHA and audio CAPTCHA. However, they also have problems in use. As a related work, an effective text-based CAPTCHA algorithm was proposed to which amodal completion is applied. The CAPTCHA provides computers a large amount of calculation cost while amodal completion helps human beings to recognize characters momentarily. On the other hand, momentary recognition is uncomfortable for human beings since extreme concentration is required within ten seconds. Therefore, in this paper, we propose an improved algorithm to which amodal completion and aftereffects are applied. The aftereffects extend time for recognition of characters from a moment to several seconds.

Effective CAPTCHA with Amodal Completion and Aftereffects by Complementary Colors and Difference of Luminance

We propose an effective CAPTCHA with amodal completion and aftereffects and improve it by applying complementary colors and difference of luminance. CAPTCHA is a method which distinguishes human beings from artificial intelligence which is usually called bots on Internet. Bots acquire accounts of web services for unfair uses such as stealth marketing or SPAM attacks. That is, CAPTCHA is a countermeasure against those attacks. The most popular kind of CAPTCHA methods is text-based CAPTCHA in which distorted alphabets and numbers appear with obstacles or noise. However, it is known that all of text-based CAPTCHA algorithms can be analyzed by computers. In addition, too much distortion or noise prevents human beings from alphabets or numbers. There are other kinds of CAPTCHA methods such as image CAPTCHA and audio CAPTCHA. However, they also have problems in use. As a related work, an effective text-based CAPTCHA algorithm with amodal completion was proposed. The CAPTCHA provides computers a large amount of calculation cost while amodal completion helps human beings to recognize characters momentarily. On the other hand, extreme concentration is required for momentary recognition. The CAPTCHA is once improved in our laboratory. Aftereffects are additionally combined with the CAPTCHA algorithm. Moreover, in this paper, we add colors to the algorithm with considering combinations of complementary colors and those of luminance. The aftereffects extend time for recognition of characters from a moment to several seconds.

Challenge of Deep Learning against CAPTCHA with Amodal Completion and Aftereffects by Colors

We make experiments of machine learning for our CAPTCHA proposed as an effective CAPTCHA with amodal completion and aftereffects by colors. CAPTCHA is a method that distinguishes human beings from artificial intelligence in order to prohibit malicious programs from acquiring accounts on Internet. The most popular CAPTCHA is text-based CAPTCHA with distorted alphabets and numbers. However, it is known that all of text-based CAPTCHA algorithms can be analyzed by computers. In addition, too much distortion or noise prevents human beings from recognizing alphabets or numbers. As a solution of the problems, an effective text-based CAPTCHA algorithm with amodal completion was proposed by our team. Our CAPTCHA causes computers a large amount of calculation costs while amodal completion helps human beings to recognize characters momentarily. Our CAPTCHA has evolved with aftereffects and combinations of complementary colors. In this paper, we evaluate our CAPTCHA by machine learning since machine learning is faster and more accurate than existing calculations by a computer. We confirm the limitations of machine learning. Especially, we focus on whether a computer can recognize characters without knowledge of amodal completion.

HTK analysis of text-based CAPTCHA using phonemic restoration effect and similar pronunciation with an Asian accent

In Recent years, bot (robot) programs have been a threat on the web. Some kinds of the bots acquire accounts of web services in order to use the accounts for SPAM mails, phishing, etc. CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) is one of the countermeasures for preventing bots from acquiring the accounts. Especially, text-based CAPTCHA is applied to almost all famous web services since it can be implemented easily. However, CAPTCHA faces a problem that evolution of algorithms for analysis of printed characters disarms text-based CAPTCHA. Stronger distortion of characters is an easiest countermeasure of the problem. However, it makes recognition of characters difficult not only for bots but also for human beings. Therefore, in this paper, we propose a new CAPTCHA with resistance to the analysis by computers. We focus on the human abilities of phonemic restoration and recognition of similar pronunciation. Furthermore, we also pay attention to the fact that words with an Asian accent can be heard by English speakers. The proposed CAPTCHA makes machinery presumption difficult for bots, while providing easy recognition for human beings.