WearPut : Designing Dexterous Wearable Input based on the Characteristics of Human Finger Motions

Department of Biomedical Engineering (Human Factors Engineering)Powerful microchips for computing and networking allow a wide range of wearable devices to be miniaturized with high fidelity and availability. In particular, the commercially successful smartwatches placed on the wrist drive market growth by sharing the role of smartphones and health management. The emerging Head Mounted Displays (HMDs) for Augmented Reality (AR) and Virtual Reality (VR) also impact various application areas in video games, education, simulation, and productivity tools. However, these powerful wearables have challenges in interaction with the inevitably limited space for input and output due to the specialized form factors for fitting the body parts. To complement the constrained interaction experience, many wearable devices still rely on other large form factor devices (e.g., smartphones or hand-held controllers). Despite their usefulness, the additional devices for interaction can constrain the viability of wearable devices in many usage scenarios by tethering users' hands to the physical devices. This thesis argues that developing novel Human-Computer interaction techniques for the specialized wearable form factors is vital for wearables to be reliable standalone products. This thesis seeks to address the issue of constrained interaction experience with novel interaction techniques by exploring finger motions during input for the specialized form factors of wearable devices. The several characteristics of the finger input motions are promising to enable increases in the expressiveness of input on the physically limited input space of wearable devices. First, the input techniques with fingers are prevalent on many large form factor devices (e.g., touchscreen or physical keyboard) due to fast and accurate performance and high familiarity. Second, many commercial wearable products provide built-in sensors (e.g., touchscreen or hand tracking system) to detect finger motions. This enables the implementation of novel interaction systems without any additional sensors or devices. Third, the specialized form factors of wearable devices can create unique input contexts while the fingers approach their locations, shapes, and components. Finally, the dexterity of fingers with a distinctive appearance, high degrees of freedom, and high sensitivity of joint angle perception have the potential to widen the range of input available with various movement features on the surface and in the air. Accordingly, the general claim of this thesis is that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. This thesis demonstrates the general claim by providing evidence in various wearable scenarios with smartwatches and HMDs. First, this thesis explored the comfort range of static and dynamic touch input with angles on the touchscreen of smartwatches. The results showed the specific comfort ranges on variations in fingers, finger regions, and poses due to the unique input context that the touching hand approaches a small and fixed touchscreen with a limited range of angles. Then, finger region-aware systems that recognize the flat and side of the finger were constructed based on the contact areas on the touchscreen to enhance the expressiveness of angle-based touch input. In the second scenario, this thesis revealed distinctive touch profiles of different fingers caused by the unique input context for the touchscreen of smartwatches. The results led to the implementation of finger identification systems for distinguishing two or three fingers. Two virtual keyboards with 12 and 16 keys showed the feasibility of touch-based finger identification that enables increases in the expressiveness of touch input techniques. In addition, this thesis supports the general claim with a range of wearable scenarios by exploring the finger input motions in the air. In the third scenario, this thesis investigated the motions of in-air finger stroking during unconstrained in-air typing for HMDs. The results of the observation study revealed details of in-air finger motions during fast sequential input, such as strategies, kinematics, correlated movements, inter-fingerstroke relationship, and individual in-air keys. The in-depth analysis led to a practical guideline for developing robust in-air typing systems with finger stroking. Lastly, this thesis examined the viable locations of in-air thumb touch input to the virtual targets above the palm. It was confirmed that fast and accurate sequential thumb touch can be achieved at a total of 8 key locations with the built-in hand tracking system in a commercial HMD. Final typing studies with a novel in-air thumb typing system verified increases in the expressiveness of virtual target selection on HMDs. This thesis argues that the objective and subjective results and novel interaction techniques in various wearable scenarios support the general claim that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. Finally, this thesis concludes with thesis contributions, design considerations, and the scope of future research works, for future researchers and developers to implement robust finger-based interaction systems on various types of wearable devices.ope

Ubiquitous computing and natural interfaces for environmental information

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe next computing revolution‘s objective is to embed every street, building, room and object with computational power. Ubiquitous computing (ubicomp) will allow every object to receive and transmit information, sense its surroundings and act accordingly, be located from anywhere in the world, connect every person. Everyone will have the possibility to access information, despite their age, computer knowledge, literacy or physical impairment. It will impact the world in a profound way, empowering mankind, improving the environment, but will also create new challenges that our society, economy, health and global environment will have to overcome. Negative impacts have to be identified and dealt with in advance. Despite these concerns, environmental studies have been mostly absent from discussions on the new paradigm. This thesis seeks to examine ubiquitous computing, its technological emergence, raise awareness towards future impacts and explore the design of new interfaces and rich interaction modes. Environmental information is approached as an area which may greatly benefit from ubicomp as a way to gather, treat and disseminate it, simultaneously complying with the Aarhus convention. In an educational context, new media are poised to revolutionize the way we perceive, learn and interact with environmental information. cUbiq is presented as a natural interface to access that information

Security and Privacy in Mobile Computing: Challenges and Solutions

abstract: Mobile devices are penetrating everyday life. According to a recent Cisco report [10], the number of mobile connected devices such as smartphones, tablets, laptops, eReaders, and Machine-to-Machine (M2M) modules will hit 11.6 billion by 2021, exceeding the world's projected population at that time (7.8 billion). The rapid development of mobile devices has brought a number of emerging security and privacy issues in mobile computing. This dissertation aims to address a number of challenging security and privacy issues in mobile computing. This dissertation makes fivefold contributions. The first and second parts study the security and privacy issues in Device-to-Device communications. Specifically, the first part develops a novel scheme to enable a new way of trust relationship called spatiotemporal matching in a privacy-preserving and efficient fashion. To enhance the secure communication among mobile users, the second part proposes a game-theoretical framework to stimulate the cooperative shared secret key generation among mobile users. The third and fourth parts investigate the security and privacy issues in mobile crowdsourcing. In particular, the third part presents a secure and privacy-preserving mobile crowdsourcing system which strikes a good balance among object security, user privacy, and system efficiency. The fourth part demonstrates a differentially private distributed stream monitoring system via mobile crowdsourcing. Finally, the fifth part proposes VISIBLE, a novel video-assisted keystroke inference framework that allows an attacker to infer a tablet user's typed inputs on the touchscreen by recording and analyzing the video of the tablet backside during the user's input process. Besides, some potential countermeasures to this attack are also discussed. This dissertation sheds the light on the state-of-the-art security and privacy issues in mobile computing.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Exploiting Power for Smartphone Security and Privacy

Power consumption has become a key issue for smartphone security and privacy protection. In this dissertation, we propose to exploit power for smartphone security, as well as to optimize energy consumption for smartphone privacy. First, we show that public USB charging stations pose a significant privacy risk to smartphone users. We present a side-channel attack that allows a charging station to identify which webpages are loaded while the smartphone is charging. to evaluate this side-channel, we collected power traces of Alexa top 50 websites on multiple smartphones under several conditions, including: varied battery charging level, browser cache enabled/disabled, taps/no taps on the screen, WiFi/LTE, TLS encryption enabled/disabled, different amounts of time elapsed between collection of training and testing data, and various hosting locations of the website being visited. The results of our evaluation show that the attack is highly successful: in many settings, we were able to achieve over 90% accuracy on webpage identification. On the other hand, our experiments also show that this side-channel is sensitive to some of the aforementioned conditions. Second, we introduce a new attack that allows a malicious charging station to identify which website is being visited by a smartphone user via Tor network. Our attack solely depends on power measurements performed while the user is charging her smartphone. We evaluated the attack by training a machine learning model on power traces from 50 regular webpages and 50 Tor hidden services. We considered realistic constraints such as different Tor circuits types and battery charging levels. We were able to correctly identify webpages visited using the official mobile Tor browser with accuracy of up to 85.7% when the battery was fully charged, and up to 46% when the battery level was between 30% and 50%. Our results show that hidden services can be identified with higher accuracies than regular webpages. Third, we propose a memory- and energy-efficient garbled circuit evaluation mechanism named MEG on smartphones. MEG utilizes batch data transmission and multi-threading to reduce memory and energy consumption. We implement MEG on android smartphones and compare its performance with existing methods (non-pipelined and pipelined). Two garbled circuits of different scales, AES encryption (AES-128) and Levenshtein distance (EDT-256), are considered. Our measurement results show that compared with non-pipelined method, MEG decreases the memory consumption by up to 97.5% for EDT-256 when batch size is 2 MB. Compared with pipelined method, MEG reduces the energy consumption by up to 42% for AES-128 and 23% for EDT-256. Multi-thread MEG also significantly decreases the circuit evaluation time by up to 56.7% for AES-128 and up to 13.5% for EDT-256

Extending mobile touchscreen interaction

Touchscreens have become a de facto interface for mobile devices, and are penetrating further beyond their core application domain of smartphones. This work presents a design space for extending touchscreen interaction, to which new solutions may be mapped. Specific touchscreen enhancements in the domains of manual input, visual output and haptic feedback are explored and quantitative and experiental findings reported. Particular areas covered are unintentional interaction, screen locking, stereoscopic displays and picoprojection. In addition, the novel interaction approaches of finger identification and onscreen physical guides are also explored. The use of touchscreens in the domains of car dashboards and smart handbags are evaluated as domain specific use cases. This work draws together solutions from the broad area of mobile touchscreen interaction. Fruitful directions for future research are identified, and information is provided for future researchers addressing those topics.Kosketusnäytöistä on muodostunut mobiililaitteiden pääasiallinen käyttöliittymä, ja ne ovat levinneet alkuperäiseltä ydinsovellusalueeltaan, matkapuhelimista, myös muihin laitteisiin. Työssä tutkitaan uusia vuorovaikutuksen, visualisoinnin ja käyttöliittymäpalautteen keinoja, jotka laajentavat perinteistä kosketusnäytön avulla tapahtuvaa vuorovaikutusta. Näihin liittyen väitöskirjassa esitetään sekä kvantitatiivisia tuloksia että uutta kartoittavia löydöksiä. Erityisesti työ tarkastelee tahatonta kosketusnäytön käyttöä, kosketusnäytön lukitusta, stereoskooppisia kosketusnäyttöjä ja pikoprojektoreiden hyödyntämistä. Lisäksi kartoitetaan uusia vuorovaikutustapoja, jotka liittyvät sormien identifioimiseen vuorovaikutuksen yhteydessä, ja fyysisiin, liikettä ohjaaviin rakenteisiin kosketusnäytöllä. Kosketusnäytön käyttöä autossa sekä osana älykästä käsilaukkua tarkastellaan esimerkkeinä käyttökonteksteista. Väitöskirjassa esitetään vuorovaikutussuunnittelun viitekehys, joka laajentaa kosketusnäyttöjen kautta tapahtuvaa vuorovaikutusta mobiililaitteen kanssa, ja johon työssä esitellyt, uudet vuorovaikutustavat voidaan sijoittaa. Väitöskirja yhdistää kosketusnäyttöihin liittyviä käyttöliittymäsuunnittelun ratkaisuja laajalta alueelta. Työ esittelee potentiaalisia suuntaviivoja tulevaisuuden tutkimuksille ja tuo uutta tutkimustietoa, jota mobiililaitteiden vuorovaikutuksen tutkijat ja käyttöliittymäsuunnittelijat voivat hyödyntää

Extending mobile touchscreen interaction

Touchscreens have become a de facto interface for mobile devices, and are penetrating further beyond their core application domain of smartphones. This work presents a design space for extending touchscreen interaction, to which new solutions may be mapped. Specific touchscreen enhancements in the domains of manual input, visual output and haptic feedback are explored and quantitative and experiental findings reported. Particular areas covered are unintentional interaction, screen locking, stereoscopic displays and picoprojection. In addition, the novel interaction approaches of finger identification and onscreen physical guides are also explored. The use of touchscreens in the domains of car dashboards and smart handbags are evaluated as domain specific use cases. This work draws together solutions from the broad area of mobile touchscreen interaction. Fruitful directions for future research are identified, and information is provided for future researchers addressing those topics.Kosketusnäytöistä on muodostunut mobiililaitteiden pääasiallinen käyttöliittymä, ja ne ovat levinneet alkuperäiseltä ydinsovellusalueeltaan, matkapuhelimista, myös muihin laitteisiin. Työssä tutkitaan uusia vuorovaikutuksen, visualisoinnin ja käyttöliittymäpalautteen keinoja, jotka laajentavat perinteistä kosketusnäytön avulla tapahtuvaa vuorovaikutusta. Näihin liittyen väitöskirjassa esitetään sekä kvantitatiivisia tuloksia että uutta kartoittavia löydöksiä. Erityisesti työ tarkastelee tahatonta kosketusnäytön käyttöä, kosketusnäytön lukitusta, stereoskooppisia kosketusnäyttöjä ja pikoprojektoreiden hyödyntämistä. Lisäksi kartoitetaan uusia vuorovaikutustapoja, jotka liittyvät sormien identifioimiseen vuorovaikutuksen yhteydessä, ja fyysisiin, liikettä ohjaaviin rakenteisiin kosketusnäytöllä. Kosketusnäytön käyttöä autossa sekä osana älykästä käsilaukkua tarkastellaan esimerkkeinä käyttökonteksteista. Väitöskirjassa esitetään vuorovaikutussuunnittelun viitekehys, joka laajentaa kosketusnäyttöjen kautta tapahtuvaa vuorovaikutusta mobiililaitteen kanssa, ja johon työssä esitellyt, uudet vuorovaikutustavat voidaan sijoittaa. Väitöskirja yhdistää kosketusnäyttöihin liittyviä käyttöliittymäsuunnittelun ratkaisuja laajalta alueelta. Työ esittelee potentiaalisia suuntaviivoja tulevaisuuden tutkimuksille ja tuo uutta tutkimustietoa, jota mobiililaitteiden vuorovaikutuksen tutkijat ja käyttöliittymäsuunnittelijat voivat hyödyntää

Mobile Device Background Sensors: Authentication vs Privacy

The increasing number of mobile devices in recent years has caused the collection of a large amount of personal information that needs to be protected. To this aim, behavioural biometrics has become very popular. But, what is the discriminative power of mobile behavioural biometrics in real scenarios? With the success of Deep Learning (DL), architectures based on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), such as Long Short-Term Memory (LSTM), have shown improvements compared to traditional machine learning methods. However, these DL architectures still have limitations that need to be addressed. In response, new DL architectures like Transformers have emerged. The question is, can these new Transformers outperform previous biometric approaches? To answers to these questions, this thesis focuses on behavioural biometric authentication with data acquired from mobile background sensors (i.e., accelerometers and gyroscopes). In addition, to the best of our knowledge, this is the first thesis that explores and proposes novel behavioural biometric systems based on Transformers, achieving state-of-the-art results in gait, swipe, and keystroke biometrics. The adoption of biometrics requires a balance between security and privacy. Biometric modalities provide a unique and inherently personal approach for authentication. Nevertheless, biometrics also give rise to concerns regarding the invasion of personal privacy. According to the General Data Protection Regulation (GDPR) introduced by the European Union, personal data such as biometric data are sensitive and must be used and protected properly. This thesis analyses the impact of sensitive data in the performance of biometric systems and proposes a novel unsupervised privacy-preserving approach. The research conducted in this thesis makes significant contributions, including: i) a comprehensive review of the privacy vulnerabilities of mobile device sensors, covering metrics for quantifying privacy in relation to sensitive data, along with protection methods for safeguarding sensitive information; ii) an analysis of authentication systems for behavioural biometrics on mobile devices (i.e., gait, swipe, and keystroke), being the first thesis that explores the potential of Transformers for behavioural biometrics, introducing novel architectures that outperform the state of the art; and iii) a novel privacy-preserving approach for mobile biometric gait verification using unsupervised learning techniques, ensuring the protection of sensitive data during the verification process