scholarly journals Position paper: GPT conjecture: understanding the trade-offs between granularity, performance and timeliness in control-flow integrity

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhilong Wang ◽  
Peng Liu

AbstractPerformance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we ask three questions: ➊ does trade-off really exist in different CFI schemes? ➋ if trade-off do exist, how do previous works comply with it? ➌ how can it inspire future research? Although the three questions probably cannot be directly answered, they are inspiring. We find that a deeper understanding of the nature of the trade-off will help answer the three questions. Accordingly, we proposed the GPT conjecture to pinpoint the trade-off in designing CFI schemes, which says that at most two out of three properties (fine granularity, acceptable performance, and preventive protection) could be achieved.

2020 ◽  
Author(s):  
Abigail Webb

Control faces are key for understanding the extent to which performance relies on affective evaluation versus low-level image properties. Luminance polarity (LP) reversal combined with face inversion is coming an increasingly popular tool for severely disrupting control face recognition. However, recent findings demonstrate visibility-recognition trade-offs, where these control faces are advantaged in terms of salience, despite being harder to explicitly recognise. The present report brings together findings from image analysis, simple stimuli, and behavioural data for face perception, in order to provide an overview and account for why control faces subjected to LP reversal are more easily “seen” compared to other controls, and importantly, the key implications these findings have for studies of subjective face appearance, and the extent to which future research must be aware of behavioural artefacts due to trade-off effects.


2021 ◽  
Vol 11 ◽  
Author(s):  
Abigail L. M. Webb

Control stimuli are key for understanding the extent to which face processing relies on holistic processing, and affective evaluation versus the encoding of low-level image properties. Luminance polarity (LP) reversal combined with face inversion is a popular tool for severely disrupting the recognition of face controls. However, recent findings demonstrate visibility-recognition trade-offs for LP-reversed faces, where these face controls sometimes appear more salient despite being harder to recognize. The present report brings together findings from image analysis, simple stimuli, and behavioral data for facial recognition and visibility, in an attempt to disentangle instances where LP-reversed control faces are associated with a performance bias in terms of their perceived salience. These findings have important implications for studies of subjective face appearance, and highlight that future research must be aware of behavioral artifacts due to the possibility of trade-off effects.


2016 ◽  
Vol 27 (2) ◽  
pp. 185-207 ◽  
Author(s):  
Seyoum Eshetu Birkie

Purpose – The purpose of this paper is to investigate synergy/trade-off relationship between lean and operational resilience paradigms upon disruption. Lean and resilience are operationalised with practice bundles and core functions, respectively. Design/methodology/approach – The study uses the Bayesian inference approach to analyse systematically encoded data from firms that faced disruptions in their supply chain. The data were collected from publicly available sources, and encoded using predefined constructs prior to analysis. Findings – Findings show that the synergetic relations between operational resilience and lean in mitigating performance losses outweigh the trade-off. Just-in-time/flow and total productive maintenance lean practices appear to be major sources for the trade-off; there is limited-synergy leveraged on the anticipative (sense) capability of operational resilience. Research limitations/implications – The dependence on secondary data and small sample size are possible limitations. Future research may employ large-scale studies with the same encoding approach by combining both primary and secondary sources. Practical implications – This study implies that companies need not abandon their lean implementation in order to be resilient against unanticipated disruptive circumstances. Most lean practices can be used to leverage agility to mitigate disruptions. Originality/value – This is a first study to empirically compare synergy/trade-off between operational resilience and lean with reference to changes in operations performance upon disruption. It is also a first study to investigate sources of synergy/trade-off at lean practice bundles and resilience core functions level. This is a much more practical level compared to how previous studies have addressed the issue.


2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.


2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.


2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.


Author(s):  
Steven Bernstein

This commentary discusses three challenges for the promising and ambitious research agenda outlined in the volume. First, it interrogates the volume’s attempts to differentiate political communities of legitimation, which may vary widely in composition, power, and relevance across institutions and geographies, with important implications not only for who matters, but also for what gets legitimated, and with what consequences. Second, it examines avenues to overcome possible trade-offs from gains in empirical tractability achieved through the volume’s focus on actor beliefs and strategies. One such trade-off is less attention to evolving norms and cultural factors that may underpin actors’ expectations about what legitimacy requires. Third, it addresses the challenge of theory building that can link legitimacy sources, (de)legitimation practices, audiences, and consequences of legitimacy across different types of institutions.


2020 ◽  
Vol 2020 (1) ◽  
pp. 114-128
Author(s):  
Carmen Hové ◽  
Benjamin C Trumble ◽  
Amy S Anderson ◽  
Jonathan Stieglitz ◽  
Hillard Kaplan ◽  
...  

Abstract Background and objectives Among placental mammals, females undergo immunological shifts during pregnancy to accommodate the fetus (i.e. fetal tolerance). Fetal tolerance has primarily been characterized within post-industrial populations experiencing evolutionarily novel conditions (e.g. reduced pathogen exposure), which may shape maternal response to fetal antigens. This study investigates how ecological conditions affect maternal immune status during pregnancy by comparing the direction and magnitude of immunological changes associated with each trimester among the Tsimane (a subsistence population subjected to high pathogen load) and women in the USA. Methodology Data from the Tsimane Health and Life History Project (N = 935) and the National Health and Nutrition Examination Survey (N = 1395) were used to estimate population-specific effects of trimester on differential leukocyte count and C-reactive protein (CRP), a marker of systemic inflammation. Results In both populations, pregnancy was associated with increased neutrophil prevalence, reduced lymphocyte and eosinophil count and elevated CRP. Compared to their US counterparts, pregnant Tsimane women exhibited elevated lymphocyte and eosinophil counts, fewer neutrophils and monocytes and lower CRP. Total leukocyte count remained high and unchanged among pregnant Tsimane women while pregnant US women exhibited substantially elevated counts, resulting in overlapping leukocyte prevalence among all third-trimester individuals. Conclusions and implications Our findings indicate that ecological conditions shape non-pregnant immune baselines and the magnitude of immunological shifts during pregnancy via developmental constraints and current trade-offs. Future research should investigate how such flexibility impacts maternal health and disease susceptibility, particularly the degree to which chronic pathogen exposure might dampen inflammatory response to fetal antigens. Lay Summary This study compares immunological changes associated with pregnancy between the Tsimane (an Amazonian subsistence population) and individuals in the USA. Results suggest that while pregnancy enhances non-specific defenses and dampens both antigen-specific immunity and parasite/allergy response, ecological conditions strongly influence immune baselines and the magnitude of shifts during gestation.


Author(s):  
Lisa Best ◽  
Kimberley Fung-Loy ◽  
Nafiesa Ilahibaks ◽  
Sara O. I. Ramirez-Gomez ◽  
Erika N. Speelman

AbstractNowadays, tropical forest landscapes are commonly characterized by a multitude of interacting institutions and actors with competing land-use interests. In these settings, indigenous and tribal communities are often marginalized in landscape-level decision making. Inclusive landscape governance inherently integrates diverse knowledge systems, including those of indigenous and tribal communities. Increasingly, geo-information tools are recognized as appropriate tools to integrate diverse interests and legitimize the voices, values, and knowledge of indigenous and tribal communities in landscape governance. In this paper, we present the contribution of the integrated application of three participatory geo-information tools to inclusive landscape governance in the Upper Suriname River Basin in Suriname: (i) Participatory 3-Dimensional Modelling, (ii) the Trade-off! game, and (iii) participatory scenario planning. The participatory 3-dimensional modelling enabled easy participation of community members, documentation of traditional, tacit knowledge and social learning. The Trade-off! game stimulated capacity building and understanding of land-use trade-offs. The participatory scenario planning exercise helped landscape actors to reflect on their own and others’ desired futures while building consensus. Our results emphasize the importance of systematically considering tool attributes and key factors, such as facilitation, for participatory geo-information tools to be optimally used and fit with local contexts. The results also show how combining the tools helped to build momentum and led to diverse yet complementary insights, thereby demonstrating the benefits of integrating multiple tools to address inclusive landscape governance issues.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoav Kolumbus ◽  
Noam Nisan

AbstractWe study the effectiveness of tracking and testing policies for suppressing epidemic outbreaks. We evaluate the performance of tracking-based intervention methods on a network SEIR model, which we augment with an additional parameter to model pre-symptomatic and asymptomatic individuals, and study the effectiveness of these methods in combination with or as an alternative to quarantine and global lockdown policies. Our focus is on the basic trade-off between human-lives lost and economic costs, and on how this trade-off changes under different quarantine, lockdown, tracking, and testing policies. Our main findings are as follows: (1) Tests combined with patient quarantines reduce both economic costs and mortality, however, an extensive-scale testing capacity is required to achieve a significant improvement. (2) Tracking significantly reduces both economic costs and mortality. (3) Tracking combined with a moderate testing capacity can achieve containment without lockdowns. (4) In the presence of a flow of new incoming infections, dynamic “On–Off” lockdowns are more efficient than fixed lockdowns. In this setting as well, tracking strictly improves efficiency. The results show the extreme usefulness of policies that combine tracking and testing for reducing mortality and economic costs, and their potential to contain outbreaks without imposing any social distancing restrictions. This highlights the difficult social question of trading-off these gains against patient privacy, which is inevitably infringed by tracking.


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