TouchPass

User authentication acts as the first line of defense verifying the identity of a mobile user, often as a prerequisite to allow access to resources in a mobile device. For several decades, user authentication was based on the “something the user knows”, known also as knowledge-based user authentication. Recent studies state that although knowledge-based user authentication has been the most popular for authenticating an individual, nowadays it is no more considered secure and convenient for the mobile user as it is imposing several limitations. These limitations stress the need for the development and implementation of more secure and usable user authentication methods. Toward this direction, user authentication based on the “something the user is” has caught the attention. This category includes authentication methods which make use of human physical characteristics (also referred to as physiological biometrics), or involuntary actions (also referred to as behavioral biometrics). In particular, risk-based user authentication based on behavioral biometrics appears to have the potential to increase mobile authentication security without sacrificing usability. In this context, we, firstly, present an overview of user authentication on mobile devices and discuss risk-based user authentication for mobile devices as a suitable approach to deal with the security vs. usability challenge. Afterwards, a set of novelty detection algorithms for risk estimation is tested and evaluated to identify the most appropriate ones for risk-based user authentication on mobile devices.

Benefited from the development of network and communication technologies, E-health care systems and telemedicine have got the fast development. By using the E-health care systems, patient can enjoy the remote medical service provided by the medical server. Medical data are important privacy information for patient, so it is an important issue to ensure the secure of transmitted medical data through public network. Authentication scheme can thwart unauthorized users from accessing services via insecure network environments, so user authentication with privacy protection is an important mechanism for the security of E-health care systems. Recently, based on three factors (password, biometric and smart card), an user authentication scheme for E-health care systems was been proposed by Amin et al., and they claimed that their scheme can withstand most of common attacks. Unfortunate, we find that their scheme cannot achieve the untraceability feature of the patient. Besides, their scheme lacks a password check mechanism such that it is inefficient to find the unauthorized login by the mistake of input a wrong password. Due to the same reason, their scheme is vulnerable to Denial of Service (DoS) attack if the patient updates the password mistakenly by using a wrong password. In order improve the security level of authentication scheme for E-health care application, a robust user authentication scheme with privacy protection is proposed for E-health care systems. Then, security prove of our scheme are analysed. Security and performance analyses show that our scheme is more powerful and secure for E-health care systems when compared with other related schemes.

With rapid growth of wireless local area networks (WLAN) and computing techniques, handheld devices have become a popular tool in terms of working, entertaining and communicating in daily life. Considering the huge amounts of messages travelling in WLAN, a secure authentication scheme is definitely necessary, which is also required to be flexible across multiple organizations. Aiming for establishing a secure and flexible WLAN authentication scheme for various organizations, this paper reviews existing secure authentication mechanisms, describes the details of the proposed authentication scheme, and evaluates achievements of such a scheme.

As the technology of mobile devices spreads fast, the price of mobile devices is getting cheaper. Most of the people have mobile devices, and these devices have the technology of near field communication (NFC). With the long time development and research, the mobile devices use NFC technology on the payment and authentication applications, and replace the smartcard, the access control card, and the credit card by using the card emulation mode. It helps the development of NFC applications. In recent years, more and more users begin using NFC technology on mobile payment and authentication. Many researches have proposed the related NFC authentication protocols, but their schemes are still lack of some security properties and functions, which are necessary for NFC authentication protocols. In this paper, we propose a secure and efficient NFC authentication scheme between two NFC devices by the help of the authentication server that provides mutual authentication.

The increasing use of touchscreen smartphones to access sensitive and privacy data has given rise to the need of secure and usable authentication technique. Smartphone users have their own unique behavioral characteristics when performing touch operations. These personal characteristics are reflected on different rhythm, strength, and angle preferences of touch-interaction behavior. This paper investigates the reliability and applicability on the usage of users' touch-interaction behavior for active authentication on smartphones. For each common type of touch operations, both static and dynamic features are extracted and analyzed for fine-grained characterization of users' touch behavior. Classification techniques (nearest neighbor, neural network, support vector machine, and random forest) are applied to the feature space for performing the task of active authentication. Analyses are conducted using data from around 134 900 touch operations of 71 participants in real-world scenarios, and the authentication performance is evaluated across various types of touch operations, varying operation lengths, different application tasks, and different application scenarios. The extensive experimental results are included to show that touch-interaction behavior exhibits sufficient discriminability and stability among smartphone users for active authentication, and achieves equal-error rates between 1.72% and 9.01% for different types of touch operations with the operation length of 11; the authentication accuracies improve when having long observation or small timespan between the training and testing phases, and express more reliably and stably in a specific task than in the free task. We also discuss a number of avenues for additional research that we believe are necessary to advance the state-of-the-art in this area.

With the rapid development of micro-electronics and Information and Communication Technology (ICT), users can utilize various service such as Internet of Things(IoT), smart-healthcare and smart-home using wearable devices. However, the sensitive information of user are revealed by attackers because the medical services are provided through open channel. Therefore, secure mutual authentication and key establishment are essential to provide secure services for legitimate users in Wireless Body Area Networks(WBAN). In 2019, Gupta et al. proposed a lightweight anonymous user authentication and key establishment scheme for wearable devices. We demonstrate that their scheme cannot withstand user impersonation, session key disclosure and wearable device stolen attacks. We also propose a secure and lightweight mutual authentication and key establishment scheme using wearable devices to resolve the security shortcomings of Gupta et al.'s scheme. The proposed scheme can be suitable to resource-limited environments.

Recent advances in sensing and wireless communication technologies have led to an explosion in the use of touch-screen mobile devices such as smartphones and tablets in mobile commerce and other daily work and life activities. These activities have resulted in more and more private and sensitive information stored on those devices. Therefore, improving the security of mobile devices by effective user authentication to prevent unauthorized information access becomes an imminent task. Mobile user authentication refers to the process of checking a user’s identity and verifying whether he/she is authorized to access a device. Due to the increasing incidence of mobile phones getting lost, stolen, or snatched while being used by the owner, continuous user authentication (CUA) after logging in a mobile device has attracted increasing attention. Prior research has shown that traditional password authentication is insufficient or ineffective for CUA. Despite the recent research progress in CUA, many existing methods are explicit by nature in that they require users to perform specific operations, which can cause interruptions to users’ ongoing activities or may be easily learned from observation by others. In this research, we propose a new touch dynamics based approach to CUA on touch screen mobile devices that authenticates users while they are interacting with mobile devices. Touch dynamics, which is rich in cognitive quality and unique to individuals, has yet to be explored for implicit CUA. We conducted a longitudinal study to evaluate the proposed mobile CUA approach. The results demonstrate that our method can improve the security of CUA for touch screen mobile devices. The findings have significant implications for the security and adoption of m-commerce.

ABSTRACTUser authentication procedures are essential for global mobility networks and enable a mobile user to communicate securely with other users. Chang et al. recently presented an efficient authentication scheme with user anonymity in roaming environments. The authentication scheme of Chang et al. used low‐cost functions and was most suitable for battery‐powered mobile environments. However, Youn et al. pointed out that their authentication scheme cannot ensure user anonymity and resist known session key and side channel attacks. This study will demonstrate that the scheme of Chang et al. cannot resist impersonation attacks and violates session key security. In addition, this study present a secure and efficient authentication scheme based on the scheme of Chang et al. The proposed scheme not only avoids the weaknesses of the authentication scheme of Chang et al. but also ensures data unlinkability and users untrackabilty. Copyright © 2013 John Wiley & Sons, Ltd.

As it becomes commonplace to use mobile devices to store personal and sensitive data, mobile user authentication (MUA) methods have witnessed significant advancement to improve data and device security. On the other hand, traditional MUA methods such as password (or passcode) are still being widely deployed. Despite the growing body of knowledge on technical strengths and security vulnerabilities of various MUA methods, the perception of mobile users may be different, which can play a decisive role in MUA adoption. Additionally, user preferences for MUA methods may be subject to the influence of their demographic factors and device types. Furthermore, the pervasive use of mobile devices has generated many situations that create new usability and security needs of MUA methods such as support of one-handed and/or sight-free interaction. This study investigates user perception and situational needs of MUA methods using a survey questionnaire. The research findings can guide the design and selection of MUA methods.

Personal Identification Numbers (PINs) are widely used today for user authentication on mobile devices. However, this authentication method can be subject to several attacks such as phishing, smudge, and side-channel. In this paper, we increase the security of PIN-based authentication by considering behavioral biometrics, specifically the smartphone movements typical of each user. To this end, we propose a method based on anomaly detection that is capable of recognizing whether the PIN is inserted by the smartphone owner or by an attacker. This decision is taken according to the smartphone movements, which are recorded during the PIN insertion through the built-in motion sensors. For each digit in the PIN, an anomaly score is computed using Machine Learning (ML) techniques. Subsequently, these scores are combined to obtain the final decision metric. Numerical results show that our authentication method can achieve an Equal Error Rate (EER) as low as 5% in the case of 4-digit PINs, and 4% in the case of 6-digit PINs. Considering a reduced training set, composed of solely 50 samples, the EER only slightly worsens, reaching 6%. The practicality of our approach is further confirmed by the low processing time required, on the order of fractions of milliseconds.

A provably secure and lightweight authentication scheme for Internet of Drones for smart city surveillance

Survey on Mobile User's Data Privacy Threats and Defense Mechanisms

In recent years, the use of mobile devices including smartphones has increased significantly all over the world, and e-commerce using smartphones has also greatly increased. Furthermore, many people are using their smartphones to carry out certain aspects of their work according to the BYOD trend. Therefore, it is extremely important that mobile device users are authenticated securely by remote servers when using their smartphones. Digital certificates are one of the many solutions available for authentication, but they are easy to copy and leak. Mobile device services need to properly manage registered devices and users, and trusted means of authenticating their identities are needed. In this paper, we propose a secure certificate-based user authentication framework using the trusted mobile zone (TMZ) system into which the trusted platform is built. The TMZ system is a secure mobile device into which a hypervisor is built on the mobile device, and in which the hypervisor separates the mobile device into a normal zone and a secure zone. Android OS operates in the normal zone on the TMZ systems, and secure OS is run in the secure zone at the same time. The trusted platform is built in the normal zone and the secure zone in order to provide the user with secure services. In this paper, we propose a TMZ system founded on the TEE system of the global platform. The TMZ system provides a secure execution environment in which to store sensitive data and execute security functions securely. In conclusion, we describe the experimental results of generating the signature data in the TMZ system.

User authentication is a basic security requirement during the deployment of the wireless sensor network (WSN), because it may operate in a rather hostile environment, such as a military battlefield. In 2010, Khan and Alghathbar (KA) found out that Das's two-factor user authentication scheme for WSNs is vulnerable to the gateway node (GW-node) bypassing attack and the privileged-insider attack. They further presented an improved scheme to overcome the security flaws of Das's scheme. However, in this paper, we show that KA's scheme still suffers from the GW-node impersonation attack, the GW-node bypassing attack, and the privileged-insider attack. Hence, to fix the security flaws in KA's scheme, we propose a new user authentication scheme for WSNs. The security of the user authentication session in the proposed scheme is reduced by the model of Bellare and Rogaway. The security of partial compromise of secrets in the proposed scheme is reduced and analyzed by our adversarial model. Based on the performance evaluation, the overall cost of the proposed scheme is less than that of KA's scheme. Hence, we believe that the proposed scheme is more suitable for real security applications than KA's scheme.

In this paper, we study a recent biometric modality for user authentication on mobile devices. The proposed solution is a two-factor user authentication scheme and gives some high guarantees on user's identity. We first use the knowledge of user's password represented by a secret path on a grid composed of 9 points. Second, the behavior of the user while giving its path is analyzed to verify its identity. This solution is implemented as an Android application for mobile devices. Experimental results on an own made biometric database show promising results.