794 research outputs found

    Software engineering for AI-based systems: A survey

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    AI-based systems are software systems with functionalities enabled by at least one AI component (e.g., for image-, speech-recognition, and autonomous driving). AI-based systems are becoming pervasive in society due to advances in AI. However, there is limited synthesized knowledge on Software Engineering (SE) approaches for building, operating, and maintaining AI-based systems. To collect and analyze state-of-the-art knowledge about SE for AI-based systems, we conducted a systematic mapping study. We considered 248 studies published between January 2010 and March 2020. SE for AI-based systems is an emerging research area, where more than 2/3 of the studies have been published since 2018. The most studied properties of AI-based systems are dependability and safety. We identified multiple SE approaches for AI-based systems, which we classified according to the SWEBOK areas. Studies related to software testing and software quality are very prevalent, while areas like software maintenance seem neglected. Data-related issues are the most recurrent challenges. Our results are valuable for: researchers, to quickly understand the state-of-the-art and learn which topics need more research; practitioners, to learn about the approaches and challenges that SE entails for AI-based systems; and, educators, to bridge the gap among SE and AI in their curricula.This work has been partially funded by the “Beatriz Galindo” Spanish Program BEAGAL18/00064 and by the DOGO4ML Spanish research project (ref. PID2020-117191RB-I00)Peer ReviewedPostprint (author's final draft

    ALT-C 2010 - Conference Introduction and Abstracts

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    Privacy Leakage in Mobile Computing: Tools, Methods, and Characteristics

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    The number of smartphones, tablets, sensors, and connected wearable devices are rapidly increasing. Today, in many parts of the globe, the penetration of mobile computers has overtaken the number of traditional personal computers. This trend and the always-on nature of these devices have resulted in increasing concerns over the intrusive nature of these devices and the privacy risks that they impose on users or those associated with them. In this paper, we survey the current state of the art on mobile computing research, focusing on privacy risks and data leakage effects. We then discuss a number of methods, recommendations, and ongoing research in limiting the privacy leakages and associated risks by mobile computing

    Text-to-Text Extraction and Verbalization of Biomedical Event Graphs

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    Biomedical events represent complex, graphical, and semantically rich interactions expressed in the scientific literature. Almost all contributions in the event realm orbit around semantic parsing, usually employing discriminative architectures and cumbersome multi-step pipelines limited to a small number of target interaction types. We present the first lightweight framework to solve both event extraction and event verbalization with a unified text-to-text approach, allowing us to fuse all the resources so far designed for different tasks. To this end, we present a new event graph linearization technique and release highly comprehensive event-text paired datasets, covering more than 150 event types from multiple biology subareas (English language). By streamlining parsing and generation to translations, we propose baseline transformer model results according to multiple biomedical text mining benchmarks and NLG metrics. Our extractive models achieve greater state-of-the-art performance than single-task competitors and show promising capabilities for the controlled generation of coherent natural language utterances from structured data

    Extending the Exposure Score of Web Browsers by Incorporating CVSS

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    When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Yet its content differs from one browser to another. Despite the privacy and security risks of User-Agent strings, very few works have tackled this problem. Our previous work proposed giving Internet browsers exposure relative scores to aid users to choose less intrusive ones. Thus, the objective of this work is to extend our previous work through: first, conducting a user study to identify its limitations. Second, extending the exposure score via incorporating data from the NVD. Third, providing a full implementation, instead of a limited prototype. The proposed system: assigns scores to users’ browsers upon visiting our website. It also suggests alternative safe browsers, and finally it allows updating the back-end database with a click of a button. We applied our method to a data set of more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available here [4].</p

    Defining, Measuring, and Enabling Transparency for Electronic Medical Systems

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    Transparency is a novel concept in the context of Information and Communication Technology (ICT). It has arisen from regulations as a data protection principle, and it is now being studied to encompass the peculiarities of digital information. Transparency, however, is not the first security concept to be borrowed from regulations; privacy once emerged from discussions on individual’s rights. Privacy began to be vigorously debated in 1890, when Warren and Brandeis analysed legal cases for which penalties were applied on the basis of defamation, infringement of copyrights, and violation of confidence. The authors defended that those cases were, in fact, built upon a broader principle called privacy. But privacy was only given a structured definition almost one century later, in 1960, when Prosser examined cases produced after Warren and Brandeis’ work, classifying violation of privacy into four different torts; it took twenty years more before the concept was thoroughly studied for its functions in ICT. Guidelines by the OECD outlined principles to support the discussion of privacy as a technical requirement. Proceeded by international standards for a privacy framework (ISO/IEC 29100), which translated the former legal concepts into information security terms, such as data minimisation, accuracy, and accountability. Transparency has a younger, but comparable history; the current General Data Protection Regulation (GDPR) defines it as a principle which requires “that any information and communication relating to the processing of those personal data be easily accessible and easy to understand [..]". However, other related and more abstract concepts preceded it. In the Health Insurance Portability and Accountability Act (HIPAA) of 1996, the Privacy Rule demands to document privacy policies and procedures and to notify individuals of uses of their health information. Former European Directives, i.e., 95/46/EC and 2011/24/EU, establish “the right for individuals to have access to their personal data concerning their health [..] also in the context of cross-border healthcare”. The same did the Freedom of Information Act (FOIA) of 1966, instituting that any person has a right to obtain from agencies information regarding their records. These and other similar requests refer to the transversal quality called transparency. Similarly to what happened with privacy, transparency was also the subject of guidelines that clarify its interpretation in ICT. However, no framework or standard has been defined yet that translates transparency into a technical property. This translation is the goal of our work. This thesis is dedicated to debate existing interpretations for transparency, to establish requirements and measurement procedures for it, and to study solutions that can help systems adhere to the transparency principle from a technical perspective. Our work constitutes an initial step towards the definition of a framework that helps accomplish meaningful transparency in the context of Electronic Medical Systems

    Measuring Effectiveness of Address Schemes for AS-level Graphs

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    This dissertation presents measures of efficiency and locality for Internet addressing schemes. Historically speaking, many issues, faced by the Internet, have been solved just in time, to make the Internet just work~\cite{justWork}. Consensus, however, has been reached that today\u27s Internet routing and addressing system is facing serious scaling problems: multi-homing which causes finer granularity of routing policies and finer control to realize various traffic engineering requirements, an increased demand for provider-independent prefix allocations which injects unaggregatable prefixes into the Default Free Zone (DFZ) routing table, and ever-increasing Internet user population and mobile edge devices. As a result, the DFZ routing table is again growing at an exponential rate. Hierarchical, topology-based addressing has long been considered crucial to routing and forwarding scalability. Recently, however, a number of research efforts are considering alternatives to this traditional approach. With the goal of informing such research, we investigated the efficiency of address assignment in the existing (IPv4) Internet. In particular, we ask the question: ``how can we measure the locality of an address scheme given an input AS-level graph?\u27\u27 To do so, we first define a notion of efficiency or locality based on the average number of bit-hops required to advertize all prefixes in the Internet. In order to quantify how far from ``optimal the current Internet is, we assign prefixes to ASes ``from scratch in a manner that preserves observed semantics, using three increasingly strict definitions of equivalence. Next we propose another metric that in some sense quantifies the ``efficiency of the labeling and is independent of forwarding/routing mechanisms. We validate the effectiveness of the metric by applying it to a series of address schemes with increasing randomness given an input AS-level graph. After that we apply the metric to the current Internet address scheme across years and compare the results with those of compact routing schemes
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