Sensor Augmented Large Interactive Surfaces

Large interactive surfaces enable effective multi-user collaboration, but a majority of the current multi-touch systems are not truly multi-user. In this work we present a novel sensor-based approach for both user identification around a touch table and integration of unique gestures above the table. The work proposes the criteria for a successful and robust user identification system. The Cricket sensor based user identification system is integrated with an open source gesture recognition system Sparsh-UI to enable rapid multi-touch application development. Finally we evaluate the Cricket-based algorithm with contemporary multi-user, multi-touch systems and describe the various interaction affordances provided by the Cricket based user identification system

Simplifying Mobile Social Media Authentication On Android

Tänapäeval kasutatakse igapäevaselt nutitelefone. Kui mobiiltelefoni põhiline funktsioon oli helistamine, siis nutitelefonid pakuvad kasutajatele palju suuremaid võimalusi: võimalust suhtlemiseks, kasutada sotsiaalmeediat, saata kiirsõnumeid, telefoniga lindistada, vaadata videoid jne. Pew Research Center poolt 2014. aasta jaanuaris täiskasvanute seas läbiviidud interneti kasutamise uuringu vastustest selgus, et kasutades internetti kasutavad vastajatest 74 protsenti sealjuures sotsiaalmeediat. Juhul, kui need isikud omavad nutitelefoni, on tõenäosus, et nad kasutavad sotsiaalmeediat ka oma\n\rnutiseadmel, kuid piiranguga, mis tuleneb seadme suurusest. Nutitelefoni suurus mõjutab info vaatamist ja teksti sisestamist. Teksti trükkimine võib osutuda raskemaks klaviatuuri väiksuse tõttu, samuti võivad selle tõttu tekkida probleemid autentimisel, eriti kui teksti peab mitmeid kordi sisestama. Sellised olukorrad võivad viia lühemate paroolide kasutamiseni, mis omakorda vähendab meie kontode turvalisust. Käesolev töö pakub välja lahenduse sellistele olukordadele, kasutades trükkimise asemel mustreid. Mustrid võimaldavad\n\refektiivsemat ekraani kasutust ja annavad kasutajale rohkem kindlust. Uuringu\n\rtulemused näitavad, et selline lähenemine autentimisele on võimalik.Nowadays, smartphones are very common and are being used in everyday life. Even though mobile phones were originally invented as calling devices, smartphones allow the user to communicate in different ways including social media, instant messaging, recording and watching videos, etc. Recent statistics presented by Pew Research Center as of January 2014 claim, that 74 percentage of online adults use social media. In case they own a smartphone, they probably use social media on it as well, but with restrictions that come with the size of the device, affecting how we view content and also type. Typing on smartphones can be frustrating, but more so when the keyboard size prevents us from succeeding with authentication and we have to type the same text numerous times, which can lead to shorter passwords decreasing the security of the accounts. This paper proposes a solution to such occurrences by using pattern recognition rather than typing. Patterns allow the screen to be used more efficiently, giving the user more room for accuracy errors. Survey results indicate that approaching authentication in this way is feasible

Android Based Behavioral Biometric Authentication via Multi-Modal Fusion

Because mobile devices are easily lost or stolen, continuous authentication is extremely desirable for them. Behavioral biometrics provides non-intrusive continuous authentication that has much less impact on usability than active authentication. However single-modality behavioral biometrics has proven less accurate than standard active authentication. This thesis presents a behavioral biometric system that uses multi-modal fusion with user data from touch, keyboard, and orientation sensors. Testing of ve users shows that fusion of modalities provides more accurate authentication than each individual modalities by itself. Using the BayesNet classification algorithm, fusion achieves False Acceptance Rate (FAR) and False Rejection Rate (FRR) values of 9.65% and 2% respectively, each of which is 8% lower than the closest individual modality

User-Generated Free-Form Gestures for Authentication : Security and Memorability

Jufo_ID: 50112 ; lyhenne: MobiSys.Peer reviewe

Forgery-Resistant Touch-based Authentication on Mobile Devices

Mobile devices store a diverse set of private user data and have gradually become a hub to control users' other personal Internet-of-Things devices. Access control on mobile devices is therefore highly important. The widely accepted solution is to protect access by asking for a password. However, password authentication is tedious, e.g., a user needs to input a password every time she wants to use the device. Moreover, existing biometrics such as face, fingerprint, and touch behaviors are vulnerable to forgery attacks. We propose a new touch-based biometric authentication system that is passive and secure against forgery attacks. In our touch-based authentication, a user's touch behaviors are a function of some random "secret". The user can subconsciously know the secret while touching the device's screen. However, an attacker cannot know the secret at the time of attack, which makes it challenging to perform forgery attacks even if the attacker has already obtained the user's touch behaviors. We evaluate our touch-based authentication system by collecting data from 25 subjects. Results are promising: the random secrets do not influence user experience and, for targeted forgery attacks, our system achieves 0.18 smaller Equal Error Rates (EERs) than previous touch-based authentication.Comment: Accepted for publication by ASIACCS'1

Multimodal access to social media services

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto, Microsoft Language Development Center. 201

Graphical Password-Based User Authentication with Free-Form Doodles

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. M. Martinez-Diaz, J. Fierrez and J. Galbally, "Graphical Password-Based User Authentication With Free-Form Doodles," in IEEE Transactions on Human-Machine Systems, vol. 46, no. 4, pp. 607-614, Aug. 2016. doi: 10.1109/THMS.2015.2504101User authentication using simple gestures is now common in portable devices. In this work, authentication with free-form sketches is studied. Verification systems using dynamic time warping and Gaussian mixture models are proposed, based on dynamic signature verification approaches. The most discriminant features are studied using the sequential forward floating selection algorithm. The effects of the time lapse between capture sessions and the impact of the training set size are also studied. Development and validation experiments are performed using the DooDB database, which contains passwords from 100 users captured on a smartphone touchscreen. Equal error rates between 3% and 8% are obtained against random forgeries and between 21% and 22% against skilled forgeries. High variability between capture sessions increases the error rates.This work was supported by projects Contexts (S2009/TIC-1485) from CAM, Bio-Shield (TEC2012-34881) from Spanish MINECO, and BEAT (FP7-SEC-284989) from EU

Conceivable security risks and authentication techniques for smart devices

With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques

Continuous User Authentication by the Classification Method Based on the Dynamic Touchscreen Biometrics

When developing protection mechanisms of the confidential data on mobile devices, a balance of reliability and ease of use must be maintained. Such a balance can be provided by a biometric authentication system, which is quite easy to use while being sufficiently reliable. Introduction of the dynamic biometric and behavioral authentication factors into the system can further improve its reliability keeping the balance. Most smartphones have a touchscreen display, which is proven by the previous studies to be able to capture the dynamic biometric and behavioral characteristics of users' input events. This paper proposes a method of distinguishing a legitimate mobile device user from the intruder by analyzing dynamic biometric and behavioral characteristics of touch screen input events