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Consolidating Principles and Patterns for Human-centred Usable Security Research and Development
(2018)
We present an evaluation of usable security principles and patterns to facilitate the transfer of existing knowledge to researchers and practitioners. Based on a literature review we extracted 23 common usable security principles and 47 usable security patterns and identified their interconnection. The results indicate that current research tends to focus on only a subset of important principles. The fact that some principles are not yet addressed by any design patterns suggests that further work on refining these patterns is needed. We developed an online repository, which stores the harmonized principles and patterns. The tool enables users to search for relevant patterns and explore them in an interactive and programmatic manner. We argue that both the insights presented in this paper and the repository will be highly valuable for students for getting a good overview, practitioners for implementing usable security and researchers for identifying areas of future research.
One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions-including facial expression, speech, gesture or text-and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.
Cryptographic API misuse is responsible for a large number of software vulnerabilities. In many cases developers are overburdened by the complex set of programming choices and their security implications. Past studies have identified significant challenges when using cryptographic APIs that lack a certain set of usability features (e.g. easy-to-use documentation or meaningful warning and error messages) leading to an especially high likelihood of writing functionally correct but insecure code.
To support software developers in writing more secure code, this work investigates a novel approach aimed at these hard-to-use cryptographic APIs. In a controlled online experiment with 53 participants, we study the effectiveness of API-integrated security advice which informs about an API misuse and places secure programming hints as guidance close to the developer. This allows us to address insecure cryptographic choices including encryption algorithms, key sizes, modes of operation and hashing algorithms with helpful documentation in the guise of warnings. Whenever possible, the security advice proposes code changes to fix the responsible security issues. We find that our approach significantly improves code security. 73% of the participants who received the security advice fixed their insecure code.
We evaluate the opportunities and challenges of adopting API-integrated security advice and illustrate the potential to reduce the negative implications of cryptographic API misuse and help developers write more secure code.
This book is about how computer systems might be designed to serve their users rather better. It deals with how to study the natural behaviour of users to see how computer systems might best help them, and how one might also involve them in the design of computer systems that will assist them in their everyday practices.