356 research outputs found
You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information
Metadata are associated to most of the information we produce in our daily
interactions and communication in the digital world. Yet, surprisingly,
metadata are often still catergorized as non-sensitive. Indeed, in the past,
researchers and practitioners have mainly focused on the problem of the
identification of a user from the content of a message.
In this paper, we use Twitter as a case study to quantify the uniqueness of
the association between metadata and user identity and to understand the
effectiveness of potential obfuscation strategies. More specifically, we
analyze atomic fields in the metadata and systematically combine them in an
effort to classify new tweets as belonging to an account using different
machine learning algorithms of increasing complexity. We demonstrate that
through the application of a supervised learning algorithm, we are able to
identify any user in a group of 10,000 with approximately 96.7% accuracy.
Moreover, if we broaden the scope of our search and consider the 10 most likely
candidates we increase the accuracy of the model to 99.22%. We also found that
data obfuscation is hard and ineffective for this type of data: even after
perturbing 60% of the training data, it is still possible to classify users
with an accuracy higher than 95%. These results have strong implications in
terms of the design of metadata obfuscation strategies, for example for data
set release, not only for Twitter, but, more generally, for most social media
platforms.Comment: 11 pages, 13 figures. Published in the Proceedings of the 12th
International AAAI Conference on Web and Social Media (ICWSM 2018). June
2018. Stanford, CA, US
Why are managers happier than workers?
This paper studies the determinants of differences in self reported job satisfaction across occupations using data from the 2006/2007 European Social Survey (18 countries). When the effect of other variables is not accounted for, being a Manager yields a "satisfaction bonus" two times as big as the one provided by Workers positions. This substantial satisfaction gap between those holding Managerial positions and Workers practically disappears when we control for individual, household and work related variables. Even though the differences across occupations are reduced, all occupations bring about more job satisfaction than manual and service positions. All results hold when using the European Working Conditions Survey data set. In addition, the results are robust to the use of job satisfaction as a categorical variable and to a variation of the model specification that takes into account the potential endogeneity of the occupational choice.JRC.DG.G.9-Econometrics and applied statistic
Machine learning techniques for identification using mobile and social media data
Networked access and mobile devices provide near constant data generation and collection. Users, environments, applications, each generate different types of data; from the voluntarily provided data posted in social networks to data collected by sensors on mobile devices, it is becoming trivial to access big data caches. Processing sufficiently large amounts of data results in inferences that can be characterized as privacy invasive. In order to address privacy risks we must understand the limits of the data exploring relationships between variables and how the user is reflected in them. In this dissertation we look at data collected from social networks and sensors to identify some aspect of the user or their surroundings. In particular, we find that from social media metadata we identify individual user accounts and from the magnetic field readings we identify both the (unique) cellphone device owned by the user and their course-grained location. In each project we collect real-world datasets and apply supervised learning techniques, particularly multi-class classification algorithms to test our hypotheses. We use both leave-one-out cross validation as well as k-fold cross validation to reduce any bias in the results. Throughout the dissertation we find that unprotected data reveals sensitive information about users. Each chapter also contains a discussion about possible obfuscation techniques or countermeasures and their effectiveness with regards to the conclusions we present. Overall our results show that deriving information about users is attainable and, with each of these results, users would have limited if any indication that any type of analysis was taking place
Strategy and Organisational Cybersecurity: A Knowledge-Problem Perspective
Purpose: The purpose of this paper is to frame organisational cybersecurity through a strategic lens, as a function of an interplay of pragmatism, inference, holism and adaptation. The authors address the hostile epistemic climate for intellectual capital management presented by the dynamics of cybersecurity as a phenomenon. The drivers of this hostility are identified and their implications for research and practice are discussed. Design/methodology/approach: The philosophical foundations of cybersecurity in its relation with strategy, knowledge and intellectual capital are explored through a review of the literature as a mechanism to contribute to the emerging theoretical underpinnings of the cybersecurity domain. Findings: This conceptual paper argues that a knowledge-based perspective can serve as the necessary platform for a phenomenon-based view of organisational cybersecurity, given its multi-disciplinary nature. Research limitations/implications: By recognising the knowledge-related vectors, mechanisms and tendencies at play, a novel perspective on the topic can be developed: cybersecurity as a âknowledge problemâ. In order to facilitate such a perspective, the paper proposes an emergent epistemology, rooted in systems thinking and pragmatism. Practical implications: In practice, the knowledge-problem narrative can underpin the development of new organisational support constructs and systems. These can address the distinctiveness of the strategic challenges that cybersecurity poses for the growing operational reliance on intellectual capital. Originality/value: The research narrative presents a novel knowledge-based analysis of organisational cybersecurity, with significant implications for both interdisciplinary research in the field, and practice
Detecting the Presence of Electronic Devices in Smart Homes Using Harmonic Radar
Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called âSmart Things\u27 now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in applications ranging from explosives detection to insect tracking. We adapt this radar technology to detect consumer electronics in a home setting and show that we can indeed accurately detect the presence of even âsimpleâ electronic devices like a smart lightbulb. We evaluate the performance of our radar in both wired and over-the-air transmission scenarios
Are social enterprises technological innovative?:A quantitative analysis on social entrepreneurs in emerging countries
Technological innovation is the new backbone for companies. Exploiting and exploring new knowledge increase the chance of survival in the current dynamic market. Alongside, there are countries were be an innovative need to face up social and political challenges. This has transformed their economy, spreading an entrepreneurial mindset mingled with the willing to help a local community. This phenomenon is called social entrepreneurship which is leveraging new economies and building wealth, environmental system. In this vein, the present research seeks to offer qualitative research on 142 social entrepreneurs in an emerging country. The scope is to analyse if social entrepreneurship, entrepreneurial characteristics, and entrepreneurial ecosystem influence innovation. As emerged, technological innovation is affected by the first two factors but the entrepreneurial ecosystem is still not supportive. New, several activities should be organised by the government to assist entrepreneurs, whereas, the entrepreneurs are socially motivated to build up his enterprise.</p
I call BS: Fraud Detection in Crowdfunding Campaigns
Donations to charity-based crowdfunding environments have been on the rise in
the last few years. Unsurprisingly, deception and fraud in such platforms have
also increased, but have not been thoroughly studied to understand what
characteristics can expose such behavior and allow its automatic detection and
blocking. Indeed, crowdfunding platforms are the only ones typically performing
oversight for the campaigns launched in each service. However, they are not
properly incentivized to combat fraud among users and the campaigns they
launch: on the one hand, a platform's revenue is directly proportional to the
number of transactions performed (since the platform charges a fixed amount per
donation); on the other hand, if a platform is transparent with respect to how
much fraud it has, it may discourage potential donors from participating.
In this paper, we take the first step in studying fraud in crowdfunding
campaigns. We analyze data collected from different crowdfunding platforms, and
annotate 700 campaigns as fraud or not. We compute various textual and
image-based features and study their distributions and how they associate with
campaign fraud. Using these attributes, we build machine learning classifiers,
and show that it is possible to automatically classify such fraudulent behavior
with up to 90.14% accuracy and 96.01% AUC, only using features available from
the campaign's description at the moment of publication (i.e., with no user or
money activity), making our method applicable for real-time operation on a user
browser
Analysis of the microbial content of probiotic products commercialized worldwide and survivability in conditions mimicking the human gut environment
Introduction: Probiotics are living microorganisms that, when administered in adequate amounts, confer a health benefit on the host. Adequate number of living microbes, the presence of specific microorganisms, and their survival in the gastrointestinal (GI) environment are important to achieve desired health benefits of probiotic products. In this in vitro study, 21 leading probiotic formulations commercialized worldwide were evaluated for their microbial content and survivability in simulated GI conditions. Methods: Plate-count method was used to determine the amount of living microbes contained in the products. Culture-dependent Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry and culture-independent metagenomic analysis through 16S and 18S rDNA sequencing were applied in combination for species identification. To estimate the potential survivability of the microorganisms contained in the products in the harsh GI environment, an in vitro model composed of different simulated gastric and intestinal fluids was adopted. Results: The majority of the tested probiotic products were concordant with the labels in terms of number of viable microbes and contained probiotic species. However, one product included fewer viable microbes than those displayed on the label, one product contained two species that were not declared, and another product lacked one of the labeled probiotic strains. Survivability in simulated acidic and alkaline GI fluids was highly variable depending on the composition of the products. The microorganisms contained in four products survived in both acidic and alkaline environments. For one of these products, microorganisms also appeared to grow in the alkaline environment. Conclusion: This in vitro study demonstrates that most globally commercialized probiotic products are consistent with the claims described on their labels with respect to the number and species of the contained microbes. Evaluated probiotics generally performed well in survivability tests, although viability of microbes in simulated gastric and intestinal environments showed large variability. Although the results obtained in this study indicate a good quality of the tested formulations, it is important to stress that stringent quality controls of probiotic products should always be performed to provide optimal health benefits for the host
Bax regulates neuronal Ca2+ homeostasis
Excessive Ca(2+) entry during glutamate receptor overactivation (\u22excitotoxicity\u22) induces acute or delayed neuronal death. We report here that deficiency in bax exerted broad neuroprotection against excitotoxic injury and oxygen/glucose deprivation in mouse neocortical neuron cultures and reduced infarct size, necrotic injury, and cerebral edema formation after middle cerebral artery occlusion in mice. Neuronal Ca(2+) and mitochondrial membrane potential (ÎÏm) analysis during excitotoxic injury revealed that bax-deficient neurons showed significantly reduced Ca(2+) transients during the NMDA excitation period and did not exhibit the deregulation of ÎÏm that was observed in their wild-type (WT) counterparts. Reintroduction of bax or a bax mutant incapable of proapoptotic oligomerization equally restored neuronal Ca(2+) dynamics during NMDA excitation, suggesting that Bax controlled Ca(2+) signaling independently of its role in apoptosis execution. Quantitative confocal imaging of intracellular ATP or mitochondrial Ca(2+) levels using FRET-based sensors indicated that the effects of bax deficiency on Ca(2+) handling were not due to enhanced cellular bioenergetics or increased Ca(2+) uptake into mitochondria. We also observed that mitochondria isolated from WT or bax-deficient cells similarly underwent Ca(2+)-induced permeability transition. However, when Ca(2+) uptake into the sarco/endoplasmic reticulum was blocked with the Ca(2+)-ATPase inhibitor thapsigargin, bax-deficient neurons showed strongly elevated cytosolic Ca(2+) levels during NMDA excitation, suggesting that the ability of Bax to support dynamic ER Ca(2+) handling is critical for cell death signaling during periods of neuronal overexcitation
Evolutionary trait-based approaches for predicting future global impacts of plant pathogens in the genus Phytophthora
1. Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without inâdepth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens.
2. We use a speciesâlevel trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting speciesâlevel knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models.
3. In the bestâperforming models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect.
4. Rootâattacking species were reported in more countries, and on more host plant families than foliarâattacking species. Host generalist pathogens had thickerâwalled resting structures (stressâtolerant oospores) and faster growth rates at their optima. Coldâtolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding.
5. Policy implications. We evaluate the potential of an evolutionary traitâbased framework to support horizonâscanning approaches for identifying pathogens with greater potential for globalâscale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly underâreported species, with similar traits and/or phylogenetic proximity to other highâimpact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Traitâbased horizonâscanning approaches would benefit from the development of international and crossâsectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny
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