Oana Inel, Tim Draws, Lora Aroyo, Collect, measure, repeat: Reliability factors for responsible AI data collection, In: Eleventh AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2023), Association for the Advancement of Artificial Intelligence, Delft, the Netherlands, 2023-11-06. (Conference or Workshop Paper published in Proceedings)
The rapid entry of machine learning approaches in our dailyactivities and high-stakes domains demands transparency andscrutiny of their fairness and reliability. To help gauge ma-chine learning models’ robustness, research typically focuseson the massive datasets used for their deployment,e.g., cre-ating and maintaining documentation to understand theirorigin, process of development, and ethical considerations.However, data collection for AI is still typically a one-offpractice, and oftentimes datasets collected for a certain pur-pose or application are reused for a different problem. Addi-tionally, dataset annotations may not be representative overtime, contain ambiguous or erroneous annotations, or be un-able to generalize across domains. Recent research has shownthese practices might lead to unfair, biased, or inaccurate out-comes. We argue that data collection for AI should be per-formed in a responsible manner where the quality of the datais thoroughly scrutinized and measured through a systematicset of appropriate metrics. In this paper, we propose a Re-sponsible AI (RAI) methodology designed to guide the datacollection with a set of metrics for an iterative in-depth analy-sis of thefactors influencing the quality and reliabilityof thegenerated data. We propose a granular set of measurements toinform on theinternal reliabilityof a dataset and itsexternalstabilityover time. We validate our approach across nine ex-isting datasets and annotation tasks and four input modalities.This approach impacts theassessment of data robustnessusedin real world AI applications, where diversity of users andcontent is eminent. Furthermore, it deals with fairness andaccountability aspects in data collection by providing system-atic and transparent quality analysis for data collections. |
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Dieter Pfaff, Patricia Dorothee Ruffing-Straube, David Staubli, Aufdeckung von Steuerhinterziehung in der Schweiz durch den automatischen Informationsaustausch, Perspektiven der Wirtschaftspolitik, Vol. 24 (3), 2023. (Journal Article)
Die Hinterziehung von Steuern soll durch den international eingeführten automatischen Informationsaustausch (AIA) aufgedeckt und eingedämmt werden. Zudem besteht in der Schweiz seit 2010 die straflose Selbstanzeige. Im Zusammenhang mit der internationalen Einführung des AIA ist ein deutlicher Anstieg der straflosen Selbstanzeigen zu beobachten. Dabei werden erhebliche kantonale Unterschiede sichtbar. So ist die Anzahl strafloser Selbstanzeigen pro zehntausend Steuerpflichtige in Kantonen mit hohen Vermögensteuern, getrieben durch die bevölkerungsstarken Genferseekantone, nach der Einführung des AIA tendenziell höher. Da das Selbstanzeigeverhalten im Zuge des AIA vorwiegend ausländisches Vermögen und Einkommen betrifft, könnte auch der Anteil der zugewanderten Wohnbevölkerung eine Rolle spielen. |
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Rafael Henrique Vareto, Manuel Günther, William Robson Schwartz, Open-Set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature Augmentation, In: 2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), Institute of Electrical and Electronics Engineers, 2023-11-06. (Conference or Workshop Paper published in Proceedings)
Open-set face recognition is a scenario in which biometric systems have incomplete knowledge of all existing subjects. This arduous requirement must dismiss irrelevant faces and focus on subjects of interest only. For this reason, this work introduces a novel method that associates an ensemble of compact neural networks with data augmentation at the feature level and an entropy-based cost function. Deep neural networks pre-trained on large face datasets serve as the preliminary feature extraction module. The neural adapter ensemble consists of binary models trained on original feature representations along with negative synthetic mix-up embeddings, which are adequately handled by the designed open-set loss since they do not belong to any known identity. We carry out experiments on well-known LFW and IJB-C datasets where results show that the approach is capable of boosting closed and open-set identification accuracy. |
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Loris Sauter, Tim Bachmann, Luca Rossetto, Heiko Schuldt, Spatially Localised Immersive Contemporary and Historic Photo Presentation on Mobile Devices in Augmented Reality, In: MM '23: The 31st ACM International Conference on Multimedia, ACM Digital Library, New York, NY, USA, 2023-11-02. (Conference or Workshop Paper published in Proceedings)
These days, taking a photo is the most common way of capturing a moment. Some of these photos captured in the moment are never to be seen again. Others are almost immediately shared with the world. Yet, the context of the captured moment can only be shared to a limited extent. The continuous improvement of mobile devices has not only led to higher resolution cameras and, thus, visually more appealing pictures but also to a broader and more precise range of accompanying sensor metadata. Positional and bearing information can provide context for photos and is thus an integral aspect of the captured moment. However, it is commonly only used to sort photos by time and possibly group by place. Such more precise sensor metadata, combined with the increased computing power of mobile devices, can enable more and more powerful Augmented Reality (AR) capabilities, especially for communicating the context of a captured photo. Users can thereby witness the captured moment in its real location and also experience its spatial contextualization. With the help of a suitable data augmentation, such context-preserving presentation can be extended even to non-digitally born content, including historical images. This offers new immersive ways to experience the cultural history of one's current location. In this paper, we present an approach for location-based image presentation in AR on mobile devices. With this approach, users can experience captured moments in their physical context. We demonstrate the power of this approach based on a prototype implementation and evaluate it in a user study. |
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Andreas Barth, Valerie Laturnus, Sasan Mansouri, Alexander Wagner, Conflicted Analysts and Initial Coin Offerings, Management Science, Vol. 69 (11), 2023. (Journal Article)
This paper studies the contribution of analysts to the functioning and failure of the market for Initial Coin Offerings (ICOs). The assessments of freelancing analysts exhibit biases due to reciprocal interactions of analysts with ICO team members. Even favorably rated ICOs tend to fail raising some capital when a greater portion of their ratings reciprocate prior ratings. 90 days after listing on an exchange the market capitalization relative to the initial funds raised is smaller for tokens with more reciprocal ratings. These findings suggest that conflicts of interest help explain the failure of ICOs. |
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Stijn Decoster, Leander de Schutter, Jochen Menges, David De Cremer, Jeroen Stouten, Does change incite abusive supervision? The role of transformational change and hindrance stress, Human Resource Management Journal, Vol. 33 (4), 2023. (Journal Article)
To remain competitive, organizations tend to change their established ways of working, their strategy, the core values, and the organizational structure. Such thorough changes are referred to as transformational change. Unfortunately, transformational change is often unsuccessful because organizational members do not always welcome the change. Although organizations often expect their supervisors to be successful role-models and change-agents during the transformational change process, we argue that initiating transformational change could increase supervisors' hindrance stress levels, which may result in abusive behaviors towards employees. More specifically, in a multi-source survey and an experimental study, we find evidence that transformational change is associated with supervisors' experienced hindrance stress, which subsequently led to more abusive behaviors towards employees. |
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Violetta Splitter, Paula Jarzabkowski, David Seidl, Middle Managers’ Struggle Over Their Subject Position in Open Strategy Processes, Journal of Management Studies, Vol. 60 (7), 2023. (Journal Article)
In this paper we examine middle managers’ struggle over their subject position as strategists in the context of participative strategy processes. Based on a longitudinal case study of a company undertaking an Open Strategy process, we show how the wider inclusion of front-line employees in developing new strategy undermines the traditional subject position of middle managers. Based on these findings, we develop a process model depicting the recursive dynamics of middle managers’ struggles to maintain their subject positions in the face of employee participation. With these findings we contribute to the literature on middle managers by advancing our understanding of the implications of employee participation for middle managers’ subject position as strategists and their different ways of reclaiming their subject position. We also contribute to the literature on Open Strategy by revealing the implications for traditional strategy actors as well as by explaining the processual dynamics of participation over time. |
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Erdinc Akyildirim, Oguzhan Cepni, Shaen Corbet, Gazi Salah Uddin, Forecasting mid-price movement of Bitcoin futures using machine learning, Annals of Operations Research, Vol. 330 (1-2), 2023. (Journal Article)
In the aftermath of the global financial crisis and ongoing COVID-19 pandemic, investors face challenges in understanding price dynamics across assets. This paper explores the performance of the various type of machine learning algorithms (MLAs) to predict mid-price movement for Bitcoin futures prices. We use high-frequency intraday data to evaluate the relative forecasting performances across various time frequencies, ranging between 5 and 60-min. Our findings show that the average classification accuracy for five out of the six MLAs is consistently above the 50% threshold, indicating that MLAs outperform benchmark models such as ARIMA and random walk in forecasting Bitcoin futures prices. This highlights the importance and relevance of MLAs to produce accurate forecasts for bitcoin futures prices during the COVID-19 turmoil. |
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Cédric Chambru, Environmental shocks, religious struggle, and resilience: a contribution to the economic history of Ancien Régime France, European Review of Economic History, Vol. 27 (4), 2023. (Journal Article)
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Ralph Ossa, Robert W Staiger, Alan O Sykes, Standing in international investment and trade disputes, Journal of International Economics, Vol. 145, 2023. (Journal Article)
International investment agreements employ dispute settlement procedures that differ markedly from their counterparts in trade agreements. A prominent and controversial difference arises with respect to the issue of “standing”: Who has the right to complain to adjudicators about a violation of the agreement? While trade agreements limit standing to the member governments (state-to-state dispute settlement), investment agreements routinely extend standing to private investors as well (investor-state dispute settlement). We develop parallel models of trade and investment agreements and employ them to study this difference. We find that the difference in standing between trade and investment agreements can be understood as deriving from the fundamentally different problems that these agreements are designed to solve. Our analysis also identifies some important qualifications to the case for including investor-state dispute settlement provisions in investment agreements, thereby offering a potential explanation for the strong political controversy associated with these provisions. |
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Victoria Böhnke, Steven Ongena, Florentina Paraschiv, Endre J Reite, Back to the roots of internal credit risk models: Does risk explain why banks' risk-weighted asset levels converge over time?, Journal of Banking and Finance, Vol. 156, 2023. (Journal Article)
The internal ratings-based (IRB) approach maps bank risk profiles more adequately than the standardized approach. After switching to IRB, banks’ risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk levels. However, when examining 52 listed banks headquartered in 14 European countries that adopted the IRB approach, we observe a convergence of their RWA densities over time. We test whether this convergence can be entirely explained by differences in the size of the banks, loss levels, country risk, and/or time of IRB implementation. Our findings indicate that this is not the case. Whereas banks in high-risk countries with lax regulation, reduce their RWA densities, banks elsewhere increase theirs. Especially for banks in high-risk countries, RWA densities underestimate banks’ economic risk. Hence, the IRB approach enables regulatory arbitrage, whereby authorities only enforce strict supervision on capital requirements if they do not jeopardize bank viability. |
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Dagmar Schönig, Tobias Straumann, Paria inter pares: das Ende der Bank Wegelin, Stämpfli, Bern, 2023-11. (Book/Research Monograph)
Die Bank Wegelin war bis zu ihrer Auflösung im Jahr 2012 die älteste noch bestehende Bank in der Schweiz. Wie auch andere Banken geriet sie im Zusammenhang mit unversteuerten Vermögen von US-Kunden ins Visier der US-Behörden. Doch im Gegensatz zu anderen Geldinstituten besiegelte der Konflikt mit der US-Justiz das Ende der Bank Wegelin.Dr. Otto Bruderer und Dr. Konrad Hummler, beides ehemalige Teilhaber der Bank, haben die Finanzhistorikerin Dagmar Schönig und den Wirtschaftshistoriker Tobias Straumann beauftragt, den Sachverhalt mit einer Aussensicht aufzuarbeiten unddie Geschichte der Bank für die Nachwelt festzuhalten. Ihr Augenmerk galt nicht zuletzt der Frage, warum damals ausgerechnet eine St. Galler Privatbankverschwinden musste, während fast alle anderen geahndeten Schweizer Banken weiter existieren konnten.Entstanden ist eine umfassende und objektive Darstellung der Geschichte der Bank Wegelin, deren Untergang zu den markantesten Ereignissen der Schweizer Finanzgeschichte zu Beginn des 21. Jahrhunderts gehört. |
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Ning Wang, Nico Mutzner, Karl Blanchet, Societal Acceptance of Urban Drones: A Scoping Literature Review, Technology in society, Vol. 75, 2023. (Journal Article)
The use of drones (or Unmanned Aerial Vehicles) in urban areas has emerged rapidly in the last decade, and continues to expand at an accelerating pace. Alongside the emergent uses of high-impact technology in both public and private sectors, political debates about the potential risks and challenges have arisen, encompassing diverse perspectives and attitudes about the ethical, legal, social, and regulatory implications of introducing and integrating new technology in society. This scoping review offers an assessment of the societal acceptance factors of urban drones discussed in the current academic literature. We used a hybrid approach including quantitative landscape mapping and qualitative content analysis of the selected articles to inductively develop a typology of acceptance factors associated with urban use of drones. This review illuminates areas that have been the focus of attention within the current body of knowledge (e.g., visual and noise pollution of drones), sketches the evolution of the relevant discussions over time (e.g., a focus on the safety of the drone technology toward safety of the cargo it carries and security of the data it collects), and points to areas that have received less considerations (e.g., media appropriation and social group influence). It can, thus, help situate the topic of societal acceptance of urban drones in specific contexts, and orient future research on promoting value sensitive innovation in society more broadly. |
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David Tannenbaum, Michel Maréchal, Alain Cohn, A closer look at civic honesty in collectivist cultures, Proceedings of the National Academy of Sciences of the United States of America, Vol. 120 (49), 2023. (Journal Article)
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Juan Manuel Espín López, Alberto Huertas Celdran, Francisco Esquembre, Gregorio Martínez Pérez, Javier G Marín-Blázquez, CGAPP: A continuous group authentication privacy-preserving platform for industrial scene, Journal of Information Security and Applications, Vol. 78, 2023. (Journal Article)
In Industry 4.0, security begins with the workers’ authentication, which can be done individually or in groups. Recently, group authentication is gaining momentum, allowing users to authenticate as group members without the need to specify the particular individual. Continuous authentication and federated learning are promising techniques that might help group authentication by providing privacy, by its own design, and extra security compared to traditional methods based on passwords, tokens, or biometrics. However, these techniques have not previously been combined or evaluated for authenticating workers in Industry 4.0. Thus, this paper proposes a novel continuous group authentication privacy-preserving (CGAPP)platform that is suitable for the industry. The CGAPP platform incorporates statistical data from workers’ smartphones and employs federated learning-based outlier detection for group worker authentication while ensuring the privacy of personal data vectors. A series of experiments were performed to measure the framework’s suitability and address the following research questions: (i) What is the cost of using FL compared to full data access in industrial scenarios? (ii) How robust is federated learning against adversarial attacks, specifically, how much malicious data is required to deceive the model? and (iii) How much noise is required to disrupt the authentication system? The results demonstrate the effectiveness of the CGAPP platform in the industry since it provides factory safety while preserving privacy. This platform achieves an accuracy of 92%, comparable to the 96% obtained by traditional approaches in the literature that do not address privacy concerns. The platform’s robustness is tested against attacks in the second and third experiments, and various countermeasures are evaluated. While the CGAPP platform exhibits certain vulnerabilities to data injection attacks, straightforward countermeasures can alleviate them. Nevertheless, the system’s performance experiences a notable impact in the event of a data perturbation attack, and the countermeasures investigated are ineffective in addressing this issue. |
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José María Jorquera Valero, Pedro Miguel Sánchez Sánchez, Manuel Gil Pérez, Alberto Huertas Celdran, Gregorio Martínez Pérez, Trust-as-a-Service: A reputation-enabled trust framework for 5G network resource provisioning, Computer Communications, Vol. 211, 2023. (Journal Article)
Trust, security, and privacy are three of the major pillars to assemble the fifth-generation network and beyond. Despite such pillars are principally interconnected, a multitude of challenges arise that need to be addressed separately. 5G networks ought to offer flexible and pervasive computing capabilities across multiple domains according to user demands and assure trustworthy network providers. To this end, distributed marketplaces expect to boost the trading of heterogeneous resources so as to enable the establishment of pervasive service chains between cross-domains. Yet, the need for selecting reliable parties as “marketplace operators” plays a pivotal role in achieving a trustworthy ecosystem. Two of the principal blockages in managing foreseeable networks are the need to consider trust as a property in the resource provisioning process and adapt previous trust models to accomplish the new network and business requirements. In this regard, this article is centered on the trust management of 5G multi-party network resource provisioning. As a result, a reputation-based trust framework is proposed as a Trust-as-a-Service (TaaS) solution for a distributed multi-stakeholder environment where requirements such as zero trust and zero-touch principles should be met. Besides, a literature review is also conducted to recognize the network and business requirements currently envisaged. Finally, the validation of the proposed trust framework was performed in a real research environment, the 5GBarcelona testbed, leveraging 12% of a 2.1 GHz CPU with 20 cores and 2% of the 30 GiB memory. These outcomes reveal the TaaS solution’s feasibility and conservative approach in the context of determining reliable network operators. |
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Jonas Brunner, Bruno Rodrigues, Katharina O E Müller, Salil S Kanhere, Burkhard Stiller, Deciphering DDoS Attacks Through a Global Lens, In: 2023 19th International Conference on Network and Service Management (CNSM), Institute of Electrical and Electronics Engineers, 2023-10-30. (Conference or Workshop Paper published in Proceedings)
With a rising frequency and scale, Distributed Denial-of-Service (DDoS) attacks persist as a critical cybersecurity issue. While shared attack fingerprints aid many intrusion detection systems in identifying threats, their application for DDoS attacks remains limited due to their distinct nature. However, fingerprints observed from multiple locations can provide valuable insights. This paper presents Reassembler, a novel platform for achieving a global DDoS attack analysis using attack fingerprints recorded from various locations. Reassembler consolidates these fingerprints into a unified view allowing to obtain a global overview of DDoS attacks. The evaluation, conducted on four simulated scenarios, demonstrates Reassembler's ability to extract novel properties, such as the count of intermediate nodes and the estimated percentage of spoofed IPs. |
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Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Alberto Huertas Celdran, Robin Wassink, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller, Stealth Spectrum Sensing Data Falsification Attacks Affecting IoT Spectrum Monitors on the Battlefield, In: MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM), Institut of Electrical and Electronics Engineers, 2023-10-30. (Conference or Workshop Paper published in Proceedings)
Resource-constrained spectrum sensors from the Internet of Battlefield Things (IoBT) monitor the frequency spectrum to communicate over unoccupied bands, intercept enemy transmissions, or decode valuable information. However, they are also susceptible to Spectrum Sensing Data Falsification (SSDF) attacks manipulating the sensing data and impacting the previous services. Detection systems based on fingerprinting and machine learning have shown promising performance while detecting existing SSDF attacks. However, novel attacks reducing their impact on sensors behaviors have not been analyzed yet. Thus, this work redesigns and reimplements seven SSDF attacks by modifying spectrum data in the sensor memory instead of at later stages in the file system. Several experiments with current intelligent detection systems demonstrated that more effort is needed from the defensive perspective since the new SSDF attacks evade their detection. In this sense, literature-based detection methods achieve less than a 0.50 True Positive Rate when detecting the new implementations of the attacks. |
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Shide Du, Zihan Fang, Shiyang Lan, Yanchao Tan, Manuel Günther, Shiping Wang, Wenzhong Guo, Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustness, In: MM '23: The 31st ACM International Conference on Multimedia, ACM Digital library, 2023-10-29. (Conference or Workshop Paper published in Proceedings)
As researchers strive to narrow the gap between machine intelligence and human through the development of artificial intelligence multimedia technologies, it is imperative that we recognize the critical importance of trustworthiness in open-world, which has become ubiquitous in all aspects of daily life for everyone. However, several challenges may create a crisis of trust in current open-world artificial multimedia systems that need to be bridged: 1) Insufficient explanation of predictive results; 2) Inadequate generalization for learning models; 3) Poor adaptability to uncertain environments. Consequently, we explore a neural program to bridge trustworthiness and open-world learning, extending from single-modal to multi-modal scenarios for readers.1) To enhance design-level interpretability, we first customize trustworthy networks with specific physical meanings; 2) We then design environmental well-being task-interfaces via flexible learning regularizers for improving the generalization of trustworthy learning; 3) We propose to increase the robustness of trustworthy learning by integrating open-world recognition losses with agent mechanisms. Eventually, we enhance various trustworthy properties through the establishment of design-level explainability, environmental well-being task-interfaces and open-world recognition programs. As a result, these designed open-world protocols are applicable across a wide range of surroundings, under open-world multimedia recognition scenarios with significant performance improvements observed. |
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Daniel Fasnacht, Offene und digitale Ökosysteme: Mehrwert durch Branchen- und Technologiekonvergenz, Springer Fachmedien Wiesbaden GmbH, Berlin, 2023-10-26. (Book/Research Monograph)
In the digital paradigm, collaborative value creation takes place across organisational boundaries while the consumer moves to the centre. Value will be created in the future through the combination of artificial intelligence, augmented reality, the internet of things, blockchain, cloud and quantum computing, and the customer journey will span different sectors. The golden triangle of digital ecosystems includes commerce, social media, and finance. Companies that understand the benefits of the platform economy can achieve exponential growth and become winners of the digital transformation. They can share knowledge and resources across organisational boundaries, react quickly to market changes and find the balance between existing businesses and new markets. The future of work and leadership in open and digital ecosystems requires rethinking and new dynamic capabilities such as openness, agility, and ambidexterity. The book is based on years of research. It expands traditional management models with pragmatic strategy and action concepts, which are explained with diverse practical examples of tech companies from the USA, cross-industry ecosystems from China and healthcare platforms from Switzerland. |
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