Abstract Cryptocurrency‐based transactions are exposed to serious security risks, usually higher than risks related to traditional online transactions. The threats range from unintentional credential leaks, through fraudulent cryptocurrency exchanges and poorly implemented protocols, to broken private keys. Therefore, there is a business need for insurance services dedicated to cryptocurrencies that would be technologically as well as economically secure for both insuring and insured party. In this paper an architecture for cryptocurrency insurance framework along with a set of corresponding communication protocols and a smart contract template that jointly reduce various security risks are proposed. The detailed description of the solution is followed by the security analysis section. Also, the description of the presented solution is preceded by a general risk analysis related to cryptocurrency unit security and countermeasures analysis related to those risks. The authors believe that the presented technological solution can potentially enable new business models based on crypto‐insurance services.

This article describes a new approach to creating and securing ubiquitous augmented reality (AR) systems. Creation of AR presentations in distributed environments, where AR presentation can be dynamically composed at runtime based on distributed data sources and the usage context, and where new services can be dynamically added by various service providers, raises security concerns related to both service access control and users’ privacy. To address this challenge, a generic architecture for deployment of ubiquitous AR services and an application-layer security protocol, which enforces usage of AR content according to semantically described usage policies, are proposed.

In this work, the technical feasibility of passive secure payments for brick-and-mortar points of sale is analyzed. The core element of the proposed approach is a new application for context-based risk and trust assessment. It allows for dynamic selection of payment authorization methods that constitutes accurate trade-off between security and convenience. Particularly, the payments can be performed and authorized in the background using biometric means (face recognition), without user’s explicit action. Generally, in the proposed approach, multiple devices are used for authorization: mobile, wearables, or stationary, client’s or seller’s, and multiple authorization methods are used: biometric, knowledge-based, and possession-based. The reported research includes requirement identification, novel architecture and protocol proposition, proof-of-concept prototype system deployment, and evaluation-based lessons learned. The research confirms that with the proposed approach, it is possible to take advantage of client-seller trust dynamism to simplify the payment process while maintaining the security level.

The increasing number and diversity of devices connected to the Internet open new research challenges in the field of cross-platform and device-independent applications. One of the approaches to this problem is the Device-Independent Architecture, which provides application logic and application data device independence. It enables also usage of user interface (UI) adaptation middleware to support application UI device independence. Potentially, device-independent descriptions of application UI can be implemented with existing user interface description languages (UIDLs). In this paper, we present an analysis of eight popular UIDLs that are assumed to be suitable for device-independent GUI descriptions, along with a summary of evaluation results and lessons learned. The selected UIDLs were employed to describe a set of GUI views based on an existing mobile application. The gathered results confirm our research hypothesis that the analyzed popular declarative UIDLs are not capable of describing mobile GUI in a device-independent manner. Therefore, using the knowledge gathered from the reported experiment, we propose a set of guidelines for an optimal device-independent UIDL.

It becomes possible to take advantage of seamless biometric authentication on mobile devices due to increasing quality and quantity of built-in sensors, increasing processing power of the devices, and wireless connectivity. However, practical effectiveness of the biometric authentication application depends on user’s environment conditions that can decrease the accuracy of biometrics recognition or make the acquisition process undesirable for mobile user in a given moment, i.e., effectiveness depends on usage context. In this paper, context-based biometric authentication model for mobile devices is proposed. It enables determining the most accurate authentication method at the moment along with the most accurate form of interacting with a user w.r.t. authentication process. The generic model designed and verified with proof-of-concept implementation constitutes a foundation for building further adaptable and extensible multi-factor context-dependent systems for mobile authentication.

MOTIVATION: Liquid state nuclear magnetic resonance (NMR) spectroscopy has now been well established as a method for RNA tertiary structure determination. Most of the steps involved in the determination of RNA molecules are performed using computer programs. They however, do not apply to resonance assignment being the starting point of the whole procedure. We propose a tabu search algorithm as a tool for automating this step. Nuclear overhause effect (NOE) pathway, which determines the assignment, is constructed during an analysis of possible connections between resonances within aromatic/anomeric region of two-dimensional NOESY spectrum resulting from appropriate NMR experiment. RESULTS: Computational tests demonstrate the superior performance of the tabu search algorithm as compared with the exact enumerative approach and genetic procedure applied to the experimental and simulated spectral data for RNA molecules. AVAILABILITY: The software package can be obtained upon request from Marta Szachniuk.

Resonance assignment remains one of the hardest stages in RNA tertiary structure elucidation with the use of nuclear magnetic resonance spectroscopy. We propose an evolutionary algorithm being a tool for an automatic design of the procedure. NOE pathway, which determines the assignments, is constructed during an analysis of possible connections between resonances within aromatic/anomeric region of 2D-NOESY spectra. Computational tests demonstrate the performance of the genetic algorithm in comparison with the enumerative procedure applied for the experimental and simulated spectral data for RNA molecules.