We introduce Pixie, a novel, camera based two factor authentication solution for mobile and wearable devices. A quick and familiar user action of snapping a photo is sufficient for Pixie to simultaneously perform a graphical password authentication and a physical token based authentication, yet it does not require any expensive, uncommon hardware. Pixie establishes trust based on both the knowledge and possession of an arbitrary physical object readily accessible to the user, called trinket. Users choose their trinkets similar to setting a password, and authenticate by presenting the same trinket to the camera. The fact that the object is the trinket, is secret to the user. Pixie extracts robust, novel features from trinket images, and leverages a supervised learning classifier to effectively address inconsistencies between images of the same trinket captured in different circumstances. Pixie achieved a false accept rate below 0.09 in a brute force attack with 14.3 million authentication attempts, generated with 40,000 trinket images that we captured and collected from public datasets. We identify master images, that match multiple trinkets, and study techniques to reduce their impact. In a user study with 42 participants over 8 days in 3 sessions we found that Pixie outperforms text based passwords on memorability, speed, and user preference. Furthermore, Pixie was easily discoverable by new users and accurate under field use. Users were able to remember their trinkets 2 and 7 days after registering them, without any practice between the 3 test dates.
Solutions such as @cite_36 @cite_53 @cite_66 treat the mobile device as a second factor and eliminate user interaction to retrieve a token from the mobile device to the authentication device (e.g. a desktop) by leveraging proximity based connectivity (e.g., Bluetooth, Wi-Fi). In contrast, Pixie assigns the duty of storing the token for the second factor to a physical object outside the mobile device. The mobile device is the sole device that is used to access the services on remote servers. As an added benefit, the physical factor of the trinket renders Pixie immune to the 2FA synchronization vulnerabilities'' introduced by @cite_4 , that exploit the ongoing integration of apps among multiple platforms. Since Pixie authentication requires a simple interaction with the user, it is also possible to combine Pixie with a token stored on the mobile device. The combined Pixie and mobile device token authentication would require the user to possess both the particular mobile device that stores the token and the trinket.
@cite_36 @cite_53 @cite_4 @cite_66
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Two-factor authentication protects online accounts even if passwords are leaked. Most users, however, prefer password-only authentication. One reason why two-factor authentication is so unpopular is the extra steps that the user must complete in order to log in. Currently deployed two-factor authentication mechanisms require the user to interact with his phone to, for example, copy a verification code to the browser. Two-factor authentication schemes that eliminate user-phone interaction exist, but require additional software to be deployed. In this paper we propose Sound-Proof, a usable and deployable two-factor authentication mechanism. Sound-Proof does not require interaction between the user and his phone. In Sound-Proof the second authentication factor is the proximity of the user's phone to the device being used to log in. The proximity of the two devices is verified by comparing the ambient noise recorded by their microphones. Audio recording and comparison are transparent to the user, so that the user experience is similar to the one of password-only authentication. Sound-Proof can be easily deployed as it works with current phones and major browsers without plugins. We build a prototype for both Android and iOS. We provide empirical evidence that ambient noise is a robust discriminant to determine the proximity of two devices both indoors and outdoors, and even if the phone is in a pocket or purse. We conduct a user study designed to compare the perceived usability of Sound-Proof with Google 2-Step Verification. Participants ranked Sound-Proof as more usable and the majority would be willing to use Sound-Proof even for scenarios in which two-factor authentication is optional. Two-factor authentication protects online accounts even if passwords are leaked. Most users, however, prefer password-only authentication. One reason why two-factor authentication is so unpopular is the extra steps that the user must complete in order to log in. Currently deployed two-factor authentication mechanisms require the user to interact with his phone to, for example, copy a verification code to the browser. Two-factor authentication schemes that eliminate user-phone interaction exist, but require additional software to be deployed. In this paper we propose Sound-Proof, a usable and deployable two-factor authentication mechanism. Sound-Proof does not require interaction between the user and his phone. In Sound-Proof the second authentication factor is the proximity of the user's phone to the device being used to log in. The proximity of the two devices is verified by comparing the ambient noise recorded by their microphones. Audio recording and comparison are transparent to the user, so that the user experience is similar to the one of password-only authentication. Sound-Proof can be easily deployed as it works with current phones and major browsers without plugins. We build a prototype for both Android and iOS. We provide empirical evidence that ambient noise is a robust discriminant to determine the proximity of two devices both indoors and outdoors, and even if the phone is in a pocket or purse. We conduct a user study designed to compare the perceived usability of Sound-Proof with Google 2-Step Verification. Participants ranked Sound-Proof as more usable and the majority would be willing to use Sound-Proof even for scenarios in which two-factor authentication is optional. Small, mobile devices without user interfaces, such as Bluetooth headsets, often need to communicate securely over wireless networks. Active attacks can only be prevented by authenticating wireless communication, which is problematic when devices do not have any a priori information about each other. We introduce a new method for device-to-device authentication by shaking devices together. This paper describes two protocols for combining cryptographic authentication techniques with known methods of accelerometer data analysis to the effect of generating authenticated, secret keys. The protocols differ in their design, one being more conservative from a security point of view, while the other allows more dynamic interactions. Three experiments are used to optimize and validate our proposed authentication method. Common authentication methods based on passwords, tokens, or fingerprints perform one-time authentication and rely on users to log out from the computer terminal when they leave. Users often do not log out, however, which is a security risk. The most common solution, inactivity timeouts, inevitably fail security (too long a timeout) or usability (too short a timeout) goals. One solution is to authenticate users continuously while they are using the terminal and automatically log them out when they leave. Several solutions are based on user proximity, but these are not sufficient: they only confirm whether the user is nearby but not whether the user is actually using the terminal. Proposed solutions based on behavioral biometric authentication (e.g., keystroke dynamics) may not be reliable, as a recent study suggests. To address this problem we propose Zero-Effort Bilateral Recurring Authentication (ZEBRA). In ZEBRA, a user wears a bracelet (with a built-in accelerometer, gyroscope, and radio) on her dominant wrist. When the user interacts with a computer terminal, the bracelet records the wrist movement, processes it, and sends it to the terminal. The terminal compares the wrist movement with the inputs it receives from the user (via keyboard and mouse), and confirms the continued presence of the user only if they correlate. Because the bracelet is on the same hand that provides inputs to the terminal, the accelerometer and gyroscope data and input events received by the terminal should correlate because their source is the same - the user's hand movement. In our experiments ZEBRA performed continuous authentication with 85 accuracy in verifying the correct user and identified all adversaries within 11s. For a different threshold that trades security for usability, ZEBRA correctly verified 90 of users and identified all adversaries within 50s. User authentication systems are at an impasse. The most ubiquitous method -- the password -- has numerous problems, including susceptibility to unintentional exposure via phishing and cross-site password reuse. Second-factor authentication schemes have the potential to increase security but face usability and deployability challenges. For example, conventional second-factor schemes change the user authentication experience. Furthermore, while more secure than passwords, second-factor schemes still fail to provide sufficient protection against (single-use) phishing attacks. We present PhoneAuth, a system intended to provide security assurances comparable to or greater than that of conventional two-factor authentication systems while offering the same authentication experience as traditional passwords alone. Our work leverages the following key insights. First, a user's personal device (eg a phone) can communicate directly with the user's computer (and hence the remote web server) without any interaction with the user. Second, it is possible to provide a layered approach to security, whereby a web server can enact different policies depending on whether or not the user's personal device is present. We describe and evaluate our server-side, Chromium web browser, and Android phone implementations of PhoneAuth. Exponential growth in smartphone usage combined with recent advances in mobile technology is causing a shift in (mobile) app behavior: application vendors no longer restrict their apps to a single platform, but rather add synchronization options that allow users to conveniently switch from mobile to PC or vice versa in order to access their services. This process of integrating apps among multiple platforms essentially removes the gap between them. Current, state of the art, mobile phone-based two-factor authentication (2FA) mechanisms, however, heavily rely on the existence of such separation. They are used in a variety of segments (such as consumer online banking services or enterprise secure remote access) to protect against malware. For example, with 2FA in place, attackers should no longer be able to use their PC-based malware to instantiate fraudulent banking transactions. Initiating and bootstrapping secure, yet low-cost, ad-hoc transactions is an important challenge that needs to be overcome if the promise of mobile and pervasive computing is to be fulfilled. For example, mobile payment applications would benefit from the ability to pair devices securely without resorting to conventional mechanisms such as shared secrets, a Public Key Infrastructure (PKI), or trusted third parties. A number of methods have been proposed for doing this based on the use of a secondary out-of-band (OOB) channel that either authenticates information passed over the normal communication channel or otherwise establishes an authenticated shared secret which can be used for subsequent secure communication. A key element of the success of these methods is dependent on the performance and effectiveness of the OOB channel, which usually depends on people performing certain critical tasks correctly. In this paper, we present the results of a comparative usability study on methods that propose using humans to implement the OOB channel and argue that most of these proposals fail to take into account factors that may seriously harm the security and usability of a protocol. Our work builds on previous research in the usability of pairing methods and the accompanying recommendations for designing user interfaces that minimise human mistakes. Our findings show that the traditional methods of comparing and typing short strings into mobile devices are still preferable despite claims that new methods are more usable and secure, and that user interface design alone is not sufficient in mitigating human mistakes in OOB channels. Secure communication over wireless channels necessitates authentication of communication partners to prevent man-in-the-middle attacks. For spontaneous interaction between independent, mobile devices, no a priori information is available for authentication purposes. However, traditional approaches based on manual password input or verification of key fingerprints do not scale to tens to hundreds of interactions a day, as envisioned by future ubiquitous computing environments. One possibility to solve this problem is authentication based on similar sensor data: when two (or multiple) devices are in the same situation, and thus experience the same sensor readings, this constitutes shared, (weakly) secret information. This paper introduces the Candidate Key Protocol (CKP) to interactively generate secret shared keys from similar sensor data streams. It is suitable for two-party and multi-party authentication, and supports opportunistic authentication. A challenge in facilitating spontaneous mobile interactions is to provide pairing methods that are both intuitive and secure. Simultaneous shaking is proposed as a novel and easy-to-use mechanism for pairing of small mobile devices. The underlying principle is to use common movement as a secret that the involved devices share for mutual authentication. We present two concrete methods, ShaVe and ShaCK, in which sensing and analysis of shaking movement is combined with cryptographic protocols for secure authentication. ShaVe is based on initial key exchange followed by exchange and comparison of sensor data for verification of key authenticity. ShaCK, in contrast, is based on matching features extracted from the sensor data to construct a cryptographic key. The classification algorithms used in our approach are shown to robustly separate simultaneous shaking of two devices from other concurrent movement of a pair of devices, with a false negative rate of under 12 percent. A user study confirms that the method is intuitive and easy to use, as users can shake devices in an arbitrary pattern. Mobile devices equipped with positioning capabilities (e.g., GPS) can ask location-dependent queries to Location Based Services (LBS). To protect privacy, the user location must not be disclosed. Existing solutions utilize a trusted anonymizer between the users and the LBS. This approach has several drawbacks: (i) All users must trust the third party anonymizer, which is a single point of attack. (ii) A large number of cooperating, trustworthy users is needed. (iii) Privacy is guaranteed only for a single snapshot of user locations; users are not protected against correlation attacks (e.g., history of user movement). We propose a novel framework to support private location-dependent queries, based on the theoretical work on Private Information Retrieval (PIR). Our framework does not require a trusted third party, since privacy is achieved via cryptographic techniques. Compared to existing work, our approach achieves stronger privacy for snapshots of user locations; moreover, it is the first to provide provable privacy guarantees against correlation attacks. We use our framework to implement approximate and exact algorithms for nearest-neighbor search. We optimize query execution by employing data mining techniques, which identify redundant computations. Contrary to common belief, the experimental results suggest that PIR approaches incur reasonable overhead and are applicable in practice. User authentication is an imperative security mechanism for recognizing legal roaming users. However, designing an expeditious anonymous-user authentication scheme in the global mobility networking (GLOMONET) environment is always a challenging task. Because, due to the broadcast nature of the wireless channels, wireless networks are often susceptible to various attacks and mobile devices powered by batteries that have limited communication, processing, and storage capabilities. In this paper, we propose a lightweight, secure, and an expeditious authentication scheme, which can preserve the user anonymity for roaming services in GLOMONET. In this regard, we use the low-cost cryptographic primitives such as one-way hash functions and exclusive-or operations to accomplish goals, which is more suitable for battery-powered mobile devices. Although some authentication protocols for GLOMONET security have already been proposed, however, they are unable to achieve the desired imperative security properties, such as anonymity, privacy against eavesdroppers, communication security, etc. As a consequence of that, they are vulnerable to various security issues. Security and performance analyses show that our proposed scheme is secure and even more efficient, as compared with other related authentication schemes in GLOMONET. Mobile devices are frequently used as terminals to interact with many security-critical services such as mobile payment and online banking. However, the large client software stack and the continuous proliferation of malware expose such interaction under various threats, including passive attacks like phishing and active ones like direct code manipulation. This paper proposes TrustUI, a new trusted path design for mobile devices that enables secure interaction between end users and services based on ARM's TrustZone technology. TrustUI is built with a combination of key techniques including cooperative randomization of the trusted path and secure delegation of network interaction. With such techniques, TrustUI not only requires no trust of the commodity software stack, but also takes a step further by excluding drivers for user-interacting devices like touch screen from its trusted computing base (TCB). Hence, TrustUI has a much smaller TCB, requires no access to device driver code, and may easily adapt to many devices. A prototype of TrustUI has been implemented on a Samsung Exynos 4412 board and evaluation shows that TrustUI provides strong protection of users interaction. Securing the sensitive data stored and accessed from mobile devices makes user authentication a problem of paramount importance. The tension between security and usability renders however the task of user authentication on mobile devices a challenging task. This paper introduces FAST (Fingergestures Authentication System using Touchscreen), a novel touchscreen based authentication approach on mobile devices. Besides extracting touch data from touchscreen equipped smartphones, FAST complements and validates this data using a digital sensor glove that we have built using off-the-shelf components. FAST leverages state-of-the-art classification algorithms to provide transparent and continuous mobile system protection. A notable feature is FAST 's continuous, user transparent post-login authentication. We use touch data collected from 40 users to show that FAST achieves a False Accept Rate (FAR) of 4.66 and False Reject Rate of 0.13 for the continuous post-login user authentication. The low FAR and FRR values indicate that FAST provides excellent post-login access security, without disturbing the honest mobile users. Today's smartphones provide services and uses that required a panoply of dedicated devices not so long ago. With them, we listen to music, play games or chat with our friends; but we also read our corporate email and documents, manage our online banking; and we have started to use them directly as a means of payment. In this paper, we aim to raise awareness of side-channel attacks even when strong isolation protects sensitive applications. Previous works have studied the use of the phone accelerometer and gyroscope as side channel data to infer PINs. Here, we describe a new side-channel attack that makes use of the video camera and microphone to infer PINs entered on a number-only soft keyboard on a smartphone. The microphone is used to detect touch events, while the camera is used to estimate the smartphone's orientation, and correlate it to the position of the digit tapped by the user. We present the design, implementation and early evaluation of PIN Skimmer, which has a mobile application and a server component. The mobile application collects touch-event orientation patterns and later uses learnt patterns to infer PINs entered in a sensitive application. When selecting from a test set of 50 4-digit PINs, PIN Skimmer correctly infers more than 30 of PINs after 2 attempts, and more than 50 of PINs after 5 attempts on android-powered Nexus S and Galaxy S3 phones. When selecting from a set of 200 8-digit PINs, PIN Skimmer correctly infers about 45 of the PINs after 5 attempts and 60 after 10 attempts. It turns out to be difficult to prevent such side-channel attacks, so we provide guidelines for developers to mitigate present and future side-channel attacks on PIN input. Two-factor authentication (TFA), enabled by hardware tokens and personal devices, is gaining momentum. The security of TFA schemes relies upon a human-memorable password p drawn from some implicit dictionary D and a t-bit device-generated one-time PIN z. Compared to password-only authentication, TFA reduces the probability of adversary’s online guessing attack to 1 (|D| ∗ 2) (and to 1 2 if the password p is leaked). However, known TFA schemes do not improve security in the face of offline dictionary attacks, because an adversary who compromises the service and learns a (salted) password hash can still recover the password with O(|D|) amount of effort. This password might be reused by the user at another site employing password-only authentication. We present a suite of efficient novel TFA protocols which improve upon password-only authentication by a factor of 2 with regards to both the online guessing attack and the offline dictionary attack. To argue the security of the presented protocols, we first provide a formal treatment of TFA schemes in general. The TFA protocols we present enable utilization of devices that are connected to the client over several channel types, formed using manual PIN entry, visual QR code capture, wireless communication (Bluetooth or WiFi), and combinations thereof. Utilizing these various communication settings we design, implement, and evaluate the performance of 13 different TFA mechanisms, and we analyze them with respect to security, usability (manual effort needed beyond typing a password), and deployability (need for additional hardware or software), showing consistent advantages over known TFA schemes. In this study, we present WindTalker, a novel and practical keystroke inference framework that allows an attacker to infer the sensitive keystrokes on a mobile device through WiFi-based side-channel information. WindTalker is motivated from the observation that keystrokes on mobile devices will lead to different hand coverage and the finger motions, which will introduce a unique interference to the multi-path signals and can be reflected by the channel state information (CSI). The adversary can exploit the strong correlation between the CSI fluctuation and the keystrokes to infer the user's number input. WindTalker presents a novel approach to collect the target's CSI data by deploying a public WiFi hotspot. Compared with the previous keystroke inference approach, WindTalker neither deploys external devices close to the target device nor compromises the target device. Instead, it utilizes the public WiFi to collect user's CSI data, which is easy-to-deploy and difficult-to-detect. In addition, it jointly analyzes the traffic and the CSI to launch the keystroke inference only for the sensitive period where password entering occurs. WindTalker can be launched without the requirement of visually seeing the smart phone user's input process, backside motion, or installing any malware on the tablet. We implemented Windtalker on several mobile phones and performed a detailed case study to evaluate the practicality of the password inference towards Alipay, the largest mobile payment platform in the world. The evaluation results show that the attacker can recover the key with a high successful rate. The emergence of powerful, sensor-rich devices has led to the development of continuous authentication (CA) schemes using off-the-shelf hardware, where user behaviour is compared to past experience to produce an authentication decision with the aim of addressing challenges with traditional authentication schemes. Current CA proposals, however, have largely neglected adversaries present in a real-world deployment, namely the ubiquity of mal ware and software attacks. This has particular importance when a device cannot be trusted by a third-party, such as a corporation, that controls access to assets based on that decision. A software compromise, either on the scheme implementation or platform, may enable an adversary to modify authentication scores to alter the status of the device in reality, give insights into user behaviour, or gain unauthorised access to restricted assets. Hence, for the first time, we examine two standardised constructs that offer isolated and trusted execution - Secure Elements (SEs) and Trusted Execution Environments (TEEs) - even when an adversary has root-level privileges, and propose measures for providing trusted CA while retaining deployability. Based on these, we implement the first system for evaluating TEE-based CA on a consumer mobile device using Intel SGX, thus providing confidentiality, integrity and trust while removing the main platform from the TCB. We present an empirical evaluation of TEE-and non-TEE performance using methods proposed in related CA schemes. Our results indicate that trusted CA can be provided with no significant performance penalty, and may even offer performance benefits. Mobile devices use traditional authentication processes, which are vulnerable and unsuitable for highly dynamic environments, such as ubiquitous and pervasive environments. Therefore, new approaches are necessary in such environments. These approaches must be (i) context-aware by considering environmental and operational characteristics, restrictions of devices and information provided by sensors within the pervasive space, and (ii) customizable for balancing the systems proactivity with the control that the user wants to have over his systems. In this paper, it is presented an approach that provides a recommendation system based on the user behavior and the pervasive space where he belongs. The user behavior is defined by the actions and events that compose the activity that is being performed. The experimental results indicate (a) a dynamic and autonomic mechanism, which is more suitable for authenticating users in mobile and pervasive environments, and (b) significant efficiency to detect authentication anomalies by using a similarity model and a spatio-temporal permutation model. Authentication of smartphone users is important because a lot of sensitive data is stored in the smartphone and the smartphone is also used to access various cloud data and services. However, smartphones are easily stolen or co-opted by an attacker. Beyond the initial login, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data. Hence, this paper proposes a novel authentication system for implicit, continuous authentication of the smartphone user based on behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We propose novel context-based authentication models to differentiate the legitimate smartphone owner versus other users. We systematically show how to achieve high authentication accuracy with different design alternatives in sensor and feature selection, machine learning techniques, context detection and multiple devices. Our system can achieve excellent authentication performance with 98.1 accuracy with negligible system overhead and less than 2.4 battery consumption. Recently, remote user authentication schemes are implemented on elliptic curve cryptosystem (ECC) to reduce the computation loads for mobile devices. However, most remote user authentication schemes on ECC are based on public-key cryptosystem, in which the public key in the system requires the associated certificate to prove its validity. Thus, the user needs to perform additional computations to verify the certificate in these schemes. In addition, we find these schemes do not provide mutual authentication or a session key agreement between the user and the remote server. Therefore, we propose an ID-based remote mutual authentication with key agreement scheme on ECC in this paper. Based upon the ID-based concept, the proposed scheme does not require public keys for users such that the additional computations for certificates can be reduced. Moreover, the proposed scheme not only provides mutual authentication but also supports a session key agreement between the user and the server. Compared with the related works, the proposed scheme is more efficient and practical for mobile devices.