4,775 research outputs found

    SoK:Prudent Evaluation Practices for Fuzzing

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    Fuzzing has proven to be a highly effective approach to uncover software bugs over the past decade. After AFL popularized the groundbreaking concept of lightweight coverage feedback, the field of fuzzing has seen a vast amount of scientific work proposing new techniques, improving methodological aspects of existing strategies, or porting existing methods to new domains. All such work must demonstrate its merit by showing its applicability to a problem, measuring its performance, and often showing its superiority over existing works in a thorough, empirical evaluation. Yet, fuzzing is highly sensitive to its target, environment, and circumstances, e.g., randomness in the testing process. After all, relying on randomness is one of the core principles of fuzzing, governing many aspects of a fuzzer's behavior. Combined with the often highly difficult to control environment, the reproducibility of experiments is a crucial concern and requires a prudent evaluation setup. To address these threats to validity, several works, most notably Evaluating Fuzz Testing by Klees et al., have outlined how a carefully designed evaluation setup should be implemented, but it remains unknown to what extent their recommendations have been adopted in practice. In this work, we systematically analyze the evaluation of 150 fuzzing papers published at the top venues between 2018 and 2023. We study how existing guidelines are implemented and observe potential shortcomings and pitfalls. We find a surprising disregard of the existing guidelines regarding statistical tests and systematic errors in fuzzing evaluations. For example, when investigating reported bugs, we find that the search for vulnerabilities in real-world software leads to authors requesting and receiving CVEs of questionable quality. Extending our literature analysis to the practical domain, we attempt to reproduce claims of eight fuzzing papers. These case studies allow us to assess the practical reproducibility of fuzzing research and identify archetypal pitfalls in the evaluation design. Unfortunately, our reproduced results reveal several deficiencies in the studied papers, and we are unable to fully support and reproduce the respective claims. To help the field of fuzzing move toward a scientifically reproducible evaluation strategy, we propose updated guidelines for conducting a fuzzing evaluation that future work should follow

    Meta-learning algorithms and applications

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    Meta-learning in the broader context concerns how an agent learns about their own learning, allowing them to improve their learning process. Learning how to learn is not only beneficial for humans, but it has also shown vast benefits for improving how machines learn. In the context of machine learning, meta-learning enables models to improve their learning process by selecting suitable meta-parameters that influence the learning. For deep learning specifically, the meta-parameters typically describe details of the training of the model but can also include description of the model itself - the architecture. Meta-learning is usually done with specific goals in mind, for example trying to improve ability to generalize or learn new concepts from only a few examples. Meta-learning can be powerful, but it comes with a key downside: it is often computationally costly. If the costs would be alleviated, meta-learning could be more accessible to developers of new artificial intelligence models, allowing them to achieve greater goals or save resources. As a result, one key focus of our research is on significantly improving the efficiency of meta-learning. We develop two approaches: EvoGrad and PASHA, both of which significantly improve meta-learning efficiency in two common scenarios. EvoGrad allows us to efficiently optimize the value of a large number of differentiable meta-parameters, while PASHA enables us to efficiently optimize any type of meta-parameters but fewer in number. Meta-learning is a tool that can be applied to solve various problems. Most commonly it is applied for learning new concepts from only a small number of examples (few-shot learning), but other applications exist too. To showcase the practical impact that meta-learning can make in the context of neural networks, we use meta-learning as a novel solution for two selected problems: more accurate uncertainty quantification (calibration) and general-purpose few-shot learning. Both are practically important problems and using meta-learning approaches we can obtain better solutions than the ones obtained using existing approaches. Calibration is important for safety-critical applications of neural networks, while general-purpose few-shot learning tests model's ability to generalize few-shot learning abilities across diverse tasks such as recognition, segmentation and keypoint estimation. More efficient algorithms as well as novel applications enable the field of meta-learning to make more significant impact on the broader area of deep learning and potentially solve problems that were too challenging before. Ultimately both of them allow us to better utilize the opportunities that artificial intelligence presents

    Planetary Hinterlands:Extraction, Abandonment and Care

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    This open access book considers the concept of the hinterland as a crucial tool for understanding the global and planetary present as a time defined by the lasting legacies of colonialism, increasing labor precarity under late capitalist regimes, and looming climate disasters. Traditionally seen to serve a (colonial) port or market town, the hinterland here becomes a lens to attend to the times and spaces shaped and experienced across the received categories of the urban, rural, wilderness or nature. In straddling these categories, the concept of the hinterland foregrounds the human and more-than-human lively processes and forms of care that go on even in sites defined by capitalist extraction and political abandonment. Bringing together scholars from the humanities and social sciences, the book rethinks hinterland materialities, affectivities, and ecologies across places and cultural imaginations, Global North and South, urban and rural, and land and water

    Characterization of food insecurity among the forced migrants in northern Nigeria

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    Food insecurity affects many people worldwide. More than one billion people in Sub-Saharan Africa are food insecure. About 35% of this population, representing 346 million, are food insecure because of conflicts and political unrest. About 1.6 million people forced to migrate from northern to Central Nigeria in 2018 alone are food insecure. Food insecurity reduces people’s choice, power, and opportunity to access and control their food practices. Forced migrants have difficult circumstances, including physical restrictions on food access, and cultural and financial means during the migration. However, there is little knowledge of how the forced migrants engaged and managed their food practices throughout their migration period, making the form of food insecurity they experienced poorly understood. This calls for an investigation to increase food security for forced migrants. This article draws on the investigation from an in-depth Narrative interview involving 25 people who had experienced forced migration in northern Nigeria to address this gap. Unstructured interviews were, used for data collection to allow a wide range of responses. Their responses were audio recorded and subsequently transcribed and written in English. The contextual data that resulted from transcriptions of the audio data were subjected to computer-assisted qualitative data analysis software (CAQDAS) and the data was analyzed. The study's objectives are to find out the forms of food security/insecurity experienced by the forced migrants, their experiences, and the nature of the migration. The finding revealed that violent conflicts caused by terrorists, Fulani herders, religious bigots, and communal disagreement caused forced migration in the region and resulted in short-term, intermittent, and long-term food insecurity. Short-term food insecurity was more devastating for the migrants than intermittent and long-term food insecurity

    FARC musicians' musical identities and political identities through their music: analysis of their narratives, musical practices and songs in the Colombian peace post-agreement

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    The Colombia Revolutionary Army Forces (FARC) was the largest and most important guerrilla movement in the long and persistent Colombian internal armed conflict. In November 2016, after overcoming significant difficulties, the Colombian government and FARC signed and ratified a Final Peace Agreement; nowadays, FARC has become a lawful political party: Los Comunes. For over fifty years, the movement stimulated cultural and musical activities; FARC's musicians created, composed, arranged, recorded, performed and distributed thousands of songs, initially as part of a guerrilla and now as political party members. This research studies the musical identities of FARC musicians and their political identities as constructed through their music, based on social and cultural perspectives from the field of musical identities, the music and social movements theoretical framework and the transformation of conflict approach. This study observes how musical identities are negotiated as a force for transformative political and cultural changes at the personal and collective levels. The FARC musicians' narratives are a primary source for analysing the sociocultural transformation of identities and how they negotiate their musical and political identities. Based on a phenomenological perspective and qualitative methods, this research applied an ethnographic approach and narrative analysis based on the Listening Guide Method (LGM) to undertake a qualitative study of two narratives: life histories and songs-as-narratives. The life histories and the songs-as-narratives can be understood as sociocultural performances with multiple and continuous constructions of selfhood. The analysis of (5) FARC musicians' musical biographies (life histories), obtained through three in-depth semi-structured interviews each, and four (4) songs-as-narratives, based on music video material, allows us to observe the relationship between their music and the social movement and the role of their music in the conflict transformation process. The analysis reveals how the negotiation of musical and political identities interacts mutually and intertwined during conflict transformation experiences involving personal and collective changes. The life histories and song-as-narratives analysis provide evidence about the relationship between Identities in Music (IIM) and their Music in Identities (MII). The IIM and MII are inseparable dimensions of the self. The former is narrated through ex-combatant musicians' experiences as songwriters, singers, instrumentalists, producers, and music teachers committed to their political ideas. The latter emerges in ideological terms, but mainly through personal and collective experiences, emotionally significant, expressing their belonging to the peasantry, indigenous and popular musical cultures. At individual and collective levels, their musical knowledge, interactions and experiences construct new social roles, particularly in transitioning from guerrilla combatants to political party members. The results reveal that music is a sociocultural resource developed by musicians and the entire movement throughout the decades. The ex-combatant musicians' narratives reveal how they employ their musical experiences to explore the possibilities of the moral imagination, changing lyrics, musical production and distribution processes. Exploring new musical genres or affirming their belonging to some of them, they build different social (political) and cultural (musical) realities in their contexts. The transformation of the conflict is a profound identity negotiation process. During the transformation of the conflict, musical and political identities support each other based on ex-combatant musicians' emotional competence or emotional capital, their different uses of "I" and "we", their personal and collective relationships and connections with broader socioeconomic, political and cultural structures

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    Self-Paced Absolute Learning Progress as a Regularized Approach to Curriculum Learning

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    The usability of Reinforcement Learning is restricted by the large computation times it requires. Curriculum Reinforcement Learning speeds up learning by defining a helpful order in which an agent encounters tasks, i.e. from simple to hard. Curricula based on Absolute Learning Progress (ALP) have proven successful in different environments, but waste computation on repeating already learned behaviour in new tasks. We solve this problem by introducing a new regularization method based on Self-Paced (Deep) Learning, called Self-Paced Absolute Learning Progress (SPALP). We evaluate our method in three different environments. Our method achieves performance comparable to original ALP in all cases, and reaches it quicker than ALP in two of them. We illustrate possibilities to further improve the efficiency and performance of SPALP.Comment: 11 pages, 8 figures. The paper was a result from an Integrated Project at TU Darmstadt for which we received course credit (9 ECTS) and is not meant to be published elsewher

    Game-theoretic statistics and safe anytime-valid inference

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    Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty -- e-processes for testing and confidence sequences for estimation -- that remain valid at all stopping times, accommodating continuous monitoring and analysis of accumulating data and optional stopping or continuation for any reason. These measures crucially rely on test martingales, which are nonnegative martingales starting at one. Since a test martingale is the wealth process of a player in a betting game, SAVI centrally employs game-theoretic intuition, language and mathematics. We summarize the SAVI goals and philosophy, and report recent advances in testing composite hypotheses and estimating functionals in nonparametric settings.Comment: 25 pages. Under review. ArXiv does not compile/space some references properl
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