Protocol for a Systematic Literature Review on Security-related Research in Ubiquitous Computing

Context: This protocol is as a supplementary document to our review paper that investigates security-related challenges and solutions that have occurred during the past decade (from January 2003 to December 2013). Objectives: The objective of this systematic review is to identify security-related challenges, security goals and defenses in ubiquitous computing by answering to three main research questions. First, demographic data and trends will be given by analyzing where, when and by whom the research has been carried out. Second, we will identify security goals that occur in ubiquitous computing, along with attacks, vulnerabilities and threats that have motivated the research. Finally, we will examine the differences in addressing security in ubiquitous computing with those in traditional distributed systems. Method: In order to provide an overview of security-related challenges, goals and solutions proposed in the literature, we will use a systematic literature review (SLR). This protocol describes the steps which are to be taken in order to identify papers relevant to the objective of our review. The first phase of the method includes planning, in which we define the scope of our review by identifying the main research questions, search procedure, as well as inclusion and exclusion criteria. Data extracted from the relevant papers are to be used in the second phase of the method, data synthesis, to answer our research questions. The review will end by reporting on the results. Results and conclusions: The expected results of the review should provide an overview of attacks, vulnerabilities and threats that occur in ubiquitous computing and that have motivated the research in the last decade. Moreover, the review will indicate which security goals are gaining on their significance in the era of ubiquitous computing and provide a categorization of the security-related countermeasures, mechanisms and techniques found in the literature. (authors' abstract)Series: Working Papers on Information Systems, Information Business and Operation

Authentication schemes for Smart Mobile Devices: Threat Models, Countermeasures, and Open Research Issues

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper presents a comprehensive investigation of authentication schemes for smart mobile devices. We start by providing an overview of existing survey articles published in the recent years that deal with security for mobile devices. Then, we give a classification of threat models in smart mobile devices in five categories, including, identity-based attacks, eavesdropping-based attacks, combined eavesdropping and identity-based attacks, manipulation-based attacks, and service-based attacks. This is followed by a description of multiple existing threat models. We also provide a classification of countermeasures into four types of categories, including, cryptographic functions, personal identification, classification algorithms, and channel characteristics. According to the characteristics of the countermeasure along with the authentication model iteself, we categorize the authentication schemes for smart mobile devices in four categories, namely, 1) biometric-based authentication schemes, 2) channel-based authentication schemes, 3) factors-based authentication schemes, and 4) ID-based authentication schemes. In addition, we provide a taxonomy and comparison of authentication schemes for smart mobile devices in form of tables. Finally, we identify open challenges and future research directions

Authentication and Authorization for Mobile IoT Devices Using Biofeatures: Recent Advances and Future Trends

Biofeatures are fast becoming a key tool to authenticate the IoT devices; in this sense, the purpose of this investigation is to summarise the factors that hinder biometrics models’ development and deployment on a large scale, including human physiological (e.g., face, eyes, fingerprints-palm, or electrocardiogram) and behavioral features (e.g., signature, voice, gait, or keystroke). The different machine learning and data mining methods used by authentication and authorization schemes for mobile IoT devices are provided. Threat models and countermeasures used by biometrics-based authentication schemes for mobile IoT devices are also presented. More specifically, we analyze the state of the art of the existing biometric-based authentication schemes for IoT devices. Based on the current taxonomy, we conclude our paper with different types of challenges for future research efforts in biometrics-based authentication schemes for IoT devices

An Optimal Score Fusion Strategy For a Multimodal Biometric Authentication System for Mobile Device

For its unique advantages of preventing the loss of user identification, biometrics authentication is being increasingly used on mobile devices to meet the demand of access control and electronic transactions. Biometric community has been working on different approaches to improve reliability of security systems, multimodal authentication has attracted a lot of attention for its advantages over uni-modal biometric matchers. Nevertheless, errors caused by noises existing in real-world circumstances have become a major fact that slows down its acceptance in mobile computing. Aimed at improving the reliability of biometric authentication, current practice uses score-level fusion to combine normalized outputs of multiple classifiers. By investigating the performance of different score-level fusion methods with normalization techniques in different noise conditions, this work develops an algorithm to analyze the individual biometric matching scores in different noise conditions and dynamically select the combinations of normalization and fusion methods that are adequate for different working environments

Combined Authentication-Based Multilevel Access Control in Mobile Application for DailyLifeService

In current computing environments, collaborative computing has been a central concern in Ubiquitous, Convergent, and Social Computing. "MobiLife and "MyLifeBits are the leading projects for representing dailylifeservices and their systems require complicate and collaborative network systems. The collaborative computing environments remain in high potential risks for users' security and privacy because of diverse attack routes. In order to solve the problems, we design combined authentication and multilevel access control, which deals with cryptographic methods in a personal database of "MyLifeBits system. We propose a scheme which is flexible in dynamic access authorization changes, secure against all the attacks from various routes, a minimum round of protocol, privacy preserving access control, and multifunctional. © 2010 IEEE.