15,079 research outputs found
Towards the characterization of individual users through Web analytics
We perform an analysis of the way individual users navigate in the Web. We
focus primarily in the temporal patterns of they return to a given page. The
return probability as a function of time as well as the distribution of time
intervals between consecutive visits are measured and found to be independent
of the level of activity of single users. The results indicate a rich variety
of individual behaviors and seem to preclude the possibility of defining a
characteristic frequency for each user in his/her visits to a single site.Comment: 8 pages, 4 figures. To appear in Proceeding of Complex'0
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Energy Information Systems: From the Basement to the Boardroom
A significant buildings energy reduction opportunity exists in the office sector, given that this market segment typically is an early adopter of new technology. There is a rising trend towards smart and connected offices through the internet of things (IoT) that provides new opportunities for operational efficiency and environmental sustainability practices. Leading commercial real estate companies have begun to shift from individual building automation systems (BAS) to partially integrated and automated systems such as energy information systems (EIS). In both the United States and India, organizations are seeking operational excellence, enhanced tenant relationships, and topline growth. Hence it is imperative to engage the executives with decision-making power, by tapping into their interest in sustainability, corporate social responsibility, and innovation. This expansion of interest can enable data-driven decisions, strong energy investments, and deeper energy benefits, and would drive innovation in this field. However, none of this would be possible without robust, consistent building energy information to provide visibility across all the levels of decision making, i.e. from the basement where the facilities staff take operational action to the boardroom where the executives make investment decisions.
Price, security, and ease of use remain barriers to the adoption and pervasive use of promising EIS technologies in commercial office buildings. We believe that these barriers can be addressed through the development of ready, simplified, consistent, commercially available, low-cost EIS-in-a-box packages, that have a pre-defined set of hardware components and software features and functionality that are pertinent to a particular building sector. These simplified, sector-specific EIS packages can help to obviate the need for customization, and enhance ease of use, thereby enabling scale-up, in order to facilitate building energy savings. The EIS-in-a-box are adaptable in both U.S. and Indian office buildings, and potentially beyond these two countries
Characterizing web pornography consumption from passive measurements
Web pornography represents a large fraction of the Internet traffic, with
thousands of websites and millions of users. Studying web pornography
consumption allows understanding human behaviors and it is crucial for medical
and psychological research. However, given the lack of public data, these works
typically build on surveys, limited by different factors, e.g. unreliable
answers that volunteers may (involuntarily) provide.
In this work, we collect anonymized accesses to pornography websites using
HTTP-level passive traces. Our dataset includes about broadband
subscribers over a period of 3 years. We use it to provide quantitative
information about the interactions of users with pornographic websites,
focusing on time and frequency of use, habits, and trends. We distribute our
anonymized dataset to the community to ease reproducibility and allow further
studies.Comment: Passive and Active Measurements Conference 2019 (PAM 2019). 14 pages,
7 figure
On participatory service provision at the network edge with community home gateways
Edge computing is considered as a technology to enable new types of services which operate at the network edge. There are important use cases in ambient intelligence and the Internet of Things (IoT) for edge computing driven by huge business potentials. Most of today's edge computing platforms, however, consist of proprietary gateways, which are either closed or fairly restricted to deploy any third-party services. In this paper we discuss a participatory edge computing system running on home gateways to serve as an open environment to deploy local services. We present first motivating use cases and review existing approaches and design considerations for the proposed system. Then we show our platform which materializes the principles of an open and participatory edge environment, to lower the entry barriers for service deployment at the network edge. By using containers, our platform can flexibly enable third-party services, and may serve as an infrastructure to support several application domains of ambient intelligence.Peer ReviewedPostprint (author's final draft
Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling
Spambot detection in online social networks is a long-lasting challenge
involving the study and design of detection techniques capable of efficiently
identifying ever-evolving spammers. Recently, a new wave of social spambots has
emerged, with advanced human-like characteristics that allow them to go
undetected even by current state-of-the-art algorithms. In this paper, we show
that efficient spambots detection can be achieved via an in-depth analysis of
their collective behaviors exploiting the digital DNA technique for modeling
the behaviors of social network users. Inspired by its biological counterpart,
in the digital DNA representation the behavioral lifetime of a digital account
is encoded in a sequence of characters. Then, we define a similarity measure
for such digital DNA sequences. We build upon digital DNA and the similarity
between groups of users to characterize both genuine accounts and spambots.
Leveraging such characterization, we design the Social Fingerprinting
technique, which is able to discriminate among spambots and genuine accounts in
both a supervised and an unsupervised fashion. We finally evaluate the
effectiveness of Social Fingerprinting and we compare it with three
state-of-the-art detection algorithms. Among the peculiarities of our approach
is the possibility to apply off-the-shelf DNA analysis techniques to study
online users behaviors and to efficiently rely on a limited number of
lightweight account characteristics
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