A lot of research is being conducted into improving the usability and security of phone-unlocking. There is however a severe lack of scientic data on users’ current unlocking behavior and perceptions. We performed an online survey (n = 260) and a one-month eld study ( n = 52) to gain insights into real world (un)locking behavior of smartphone users. One of the main goals was to nd out how much overhead unlocking and authenticating adds to the overall phone usage and in how many unlock interactions security (i.e. authentication) was perceived as necessary. We also investigated why users do or do not use a lock screen and how they cope with smartphone-related risks, such as shouldersurng or unwanted accesses. Among other results, we found that on average, participants spent around 2.9 % of their smartphone interaction time with authenticating (9 % in the worst case). Participants that used a secure lock screen like PIN or Android unlock patterns considered it unnecessary in 24.1 % of situations. Shoulder surng was perceived to be a relevant risk in only 11 of 3410 sampled situations.

/pdf/it-s-a-hard-lock-life-a-field-study-of-smartphone-un-locking-3a84sozkho.pdf

It's a Hard Lock Life: A Field Study of Smartphone (Un)Locking Behavior and Risk Perception

As more and more Arabic textual information becomes available through the Web in homes and businesses, via Internet and Intranet services, there is an urgent need for technologies and tools to process the relevant information. Named Entity Recognition NER is an Information Extraction task that has become an integral part of many other Natural Language Processing NLP tasks, such as Machine Translation and Information Retrieval. Arabic NER has begun to receive attention in recent years. The characteristics and peculiarities of Arabic, a member of the Semitic languages family, make dealing with NER a challenge. The performance of an Arabic NER component affects the overall performance of the NLP system in a positive manner. This article attempts to describe and detail the recent increase in interest and progress made in Arabic NER research. The importance of the NER task is demonstrated, the main characteristics of the Arabic language are highlighted, and the aspects of standardization in annotating named entities are illustrated. Moreover, the different Arabic linguistic resources are presented and the approaches used in Arabic NER field are explained. The features of common tools used in Arabic NER are described, and standard evaluation metrics are illustrated. In addition, a review of the state of the art of Arabic NER research is discussed. Finally, we present our conclusions. Throughout the presentation, illustrative examples are used for clarification.

/pdf/a-survey-of-arabic-named-entity-recognition-and-3qzyjs2k5b.pdf

A survey of arabic named entity recognition and classification

Understanding the use of Virtual Reality in Marketing: a text mining-based review

In this paper, we present XSide, an authentication mechanism that uses the front and the back of smartphones to enter stroke-based passwords. Users can switch sides during input to minimize the risk of shoulder surfing. We performed a user study (n = 32) to explore how switching sides during authentication affects usability and security of the system. The results indicate that switching the sides increases security while authentication speed stays relatively fast (≤ 4 seconds). The paper furthermore provides insights on accuracy of eyes-free input (as used in XSide) and shows how 3D printed prototype cases can improve the back-of-device interaction experience.

Now you see me, now you don't: protecting smartphone authentication from shoulder surfers

To prevent unauthorized parties from accessing data stored on their smartphones, users have the option of enabling a "lock screen" that requires a secret code (e.g., PIN, drawing a pattern, or biometric) to gain access to their devices. We present a detailed analysis of the smartphone locking mechanisms currently available to billions of smartphone users worldwide. Through a month-long field study, we logged events from a panel of users with instrumented smartphones (N=134). We are able to show how existing lock screen mechanisms provide users with distinct tradeoffs between usability (unlocking speed vs. unlocking frequency) and security. We find that PIN users take longer to enter their codes, but commit fewer errors than pattern users, who unlock more frequently and are very prone to errors. Overall, PIN and pattern users spent the same amount of time unlocking their devices on average. Additionally, unlock performance seemed unaffected for users enabling the stealth mode for patterns. Based on our results, we identify areas where device locking mechanisms can be improved to result in fewer human errors -- increasing usability -- while also maintaining security.

https://dl.acm.org/doi/pdf/10.1145/2858036.2858267

The Anatomy of Smartphone Unlocking: A Field Study of Android Lock Screens

In mobile devices such as smart phones, it is important to provide adequate user authentication. Conventional text-based passwords have significant drawbacks though they are used as the most common authentication method. To address the vulnerabilities of traditional text-based passwords, graphical password schemes have been developed as possible alternative solutions. However, a potential drawback of graphical password schemes is that they are more vulnerable to shoulder-surfing than conventional text-based passwords. In this paper, we present a new shoulder-surfing resistant password. Our approach makes it difficult for attackers to observe a user's password by requiring the user to locate his or her password in the given password grid instead of entering the password (Figure 1). Security analysis for shoulder-surfing attacks shows that our password is robust against both random and shoulder-surfing attacks.

A new shoulder-surfing resistant password for mobile environments

Although speech recognition is a most intuitive interface, the domain of speech recognition software has been limited until now. However, with the explosive growth of mobile devices such as smart phones and car navigation systems, the applicable range of voice recognition is widening. Furthermore, most speech recognition software manufacturers provide their mobile applications for free. Due to these kinds of support, it is more efficient for users to access specific information through a speech search; however, this method is generally avoided by users because of its inaccuracy. Voice recognition software packages provided by major companies such as Nuance and Google show high-accuracy speech searches in silent spaces (>90%). However, when users run a speech-based search in a noisier location such as a crowded street or inside a car, the accuracy is about 180 shop names in our experiments under 5 classes based on different noise levels. The accuracy of the experimental results was >90%, demonstrating that the results were almost fully corrected.

Developing a system for searching a shop name on a mobile device using voice recognition and GPS information

It is interesting and informative to predict the set of articles that will be popular from the early observation stage. In this paper, we concentrate on the characteristics of hot articles and estimate the saturation point that is the earliest time the hits variation approaches zero. We have shown the statistical measures of our prediction method for popular articles, by observing the hit records from the birth time of the article. Our experiment showed that the more popular the subject article, the harder it is to identify such popular articles by observing only the early stage. The main contributions of this paper are as follows. We revealed the relationship between the amount of observation data and the predictability of popular articles. And We showed that there is a limit in predicting highly popular articles using partial knowledge. This implies the high popularity of online articles have common basic characteristics of a dynamic system that is hard to predict at the early stage.

A model for popularity dynamics to predict hot articles in discussion blog

An increasing number of public web services have attempted to prevent exploitation by bots and automated scripts, by requiring a user to solve a Turing-test problem, namely a ”Completely Automated Public Turing test to tell Cmputers and Humans Apart (CAPTCHA)”, before they are allowed to use web services. In this paper, we present an effective image-based CAPTCHA based on the orientation of N-gonal cropped sub-images as a solution of CAPTCHAs. Our CAPTCHA is based on the difficulty of detecting the orientation of N-gonal sub-images. In our CAPTCHA, the number of orientations and the crop size are important considerations, since our CAPTCHA requires users to find the orientation of sub-images cropped in the form of a regular polygon. So, we discuss usability of our CAPTCHA and the efficient values of the number of orientations and the crop size through user experiments and SVM-based machine learning tests in this paper.

Detecting the Orientation of N-gonal Cropped Sub-images and Its Application

Internet chat programs and instant messaging services are becoming increasingly popular among Internet users. One of the crucial issues with Internet chat is how to manage the corresponding pairs of questions and answers in a sequence of conversations. Although many novel methodologies have been introduced to cope with this problem, most are poor in managing interruptions, organizing turn-taking, and conveying comprehension. The Internet environment is recently evolving into a 3D environment, but the problems with managing chat dialogues with the standard 2D text-based chat have remained. Therefore, we propose a more realistic communication model for chat agents in 3D virtual space in this paper. First, we propose a new method to measure the capacity of communication between chat agents and a novel visualization method to depict the hierarchical structure of chat dialogues. In addition, we are concerned with communication networks for virtual people (avatars) living in virtual worlds. In this paper we consider a microscopic aspect of a social network in a relatively short period of time. Our experiments show that our model is highly effective in a virtual chat environment, and the communication network based on our model greatly facilitates investigation of a very large and complicated communication network.

SeonYeong Kim

Papers

A new shoulder-surfing resistant password for mobile environments

Developing a system for searching a shop name on a mobile device using voice recognition and GPS information

A model for popularity dynamics to predict hot articles in discussion blog

Detecting the Orientation of N-gonal Cropped Sub-images and Its Application

A New Communication Network Model for Chat Agents in Virtual Space