4,404 research outputs found
A systemic and cognitive approach for IoT security
Invited PaperInternational audienceThe Internet of Things (IoT) will enable objects to become active participants of everyday activities. Introducing objects into the control processes of complex systems makes IoT security very difficult to address. Indeed, the Internet of Things is a complex paradigm in which people interact with the technological ecosystem based on smart objects through complex processes. The interactions of these four IoT components, person, intelligent object, technological ecosystem, and process, highlight a systemic and cognitive dimension within security of the IoT. The interaction of people with the technological ecosystem requires the protection of their privacy. Similarly, their interaction with control processes requires the guarantee of their safety. Processes must ensure their reliability and realize the objectives for which they are designed. We believe that the move towards a greater autonomy for objects will bring the security of technologies and processes and the privacy of individuals into sharper focus. Furthermore, in parallel with the increasing autonomy of objects to perceive and act on the environment, IoT security should move towards a greater autonomy in perceiving threats and reacting to attacks, based on a cognitive and systemic approach. In this work, we will analyze the role of each of the mentioned actors in IoT security and their relationships, in order to highlight the research challenges and present our approach to these issues based on a holistic vision of IoT security
SECURITY OF SMART OBJECTS IN IoT
The internet of things involves people interacting with the technological environment based on what we considered things as “smart objects” allowing sharing of information through communication on internet. As the concept of IoT and its application is growing rapidly, the security aspect becomes very important and critical which has to be looked upon with severe importance. Security is needed anywhere where computation happens. Since the IoT allows various objects or devices to connect to internet forming a network communicating with each other or with the human user, the usage of large scale of objects on the network and the heterogeneity of those objects plays as a major security issue. Therefore, we focus on the security and privacy aspects regarding the issues, the various challenges that are being faced, and try to study the feasible solutions for the above security challenges, and also using few applications as examples. According to the observations made, it is found that there are two main approaches as referred in the existing papers which are systemic and cognitive approach. Due to the large number of interactions between things, a systemic and cognitive approach and decentralized approach seems to be an appropriate choice for IoT security
A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines
The concept of social machines is increasingly being used to characterise
various socio-cognitive spaces on the Web. Social machines are human
collectives using networked digital technology which initiate real-world
processes and activities including human communication, interactions and
knowledge creation. As such, they continuously emerge and fade on the Web. The
relationship between humans and machines is made more complex by the adoption
of Internet of Things (IoT) sensors and devices. The scale, automation,
continuous sensing, and actuation capabilities of these devices add an extra
dimension to the relationship between humans and machines making it difficult
to understand their evolution at either the systemic or the conceptual level.
This article describes these new socio-technical systems, which we term
Cyber-Physical Social Machines, through different exemplars, and considers the
associated challenges of security and privacy.Comment: 14 pages, 4 figure
Interfaces of the Agriculture 4.0
The introduction of information technologies in the environmental field is impacting and changing even a traditional sector like agriculture. Nevertheless, Agriculture 4.0 and data-driven decisions should meet user
needs and expectations. The paper presents a broad theoretical overview, discussing both the strategic role of design applied to Agri-tech and the issue of User Interface and Interaction as enabling tools in the field. In
particular, the paper suggests to rethink the HCD approach, moving on a Human-Decentered Design approach that put together user-technology-environment and the importance of the role of calm technologies as a way
to place the farmer, not as a final target and passive spectator, but as an active part of the process to aim the process of mitigation, appropriation from a traditional cultivation method to the 4.0 one
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
Cognitive Machine Individualism in a Symbiotic Cybersecurity Policy Framework for the Preservation of Internet of Things Integrity: A Quantitative Study
This quantitative study examined the complex nature of modern cyber threats to propose the establishment of cyber as an interdisciplinary field of public policy initiated through the creation of a symbiotic cybersecurity policy framework. For the public good (and maintaining ideological balance), there must be recognition that public policies are at a transition point where the digital public square is a tangible reality that is more than a collection of technological widgets. The academic contribution of this research project is the fusion of humanistic principles with Internet of Things (IoT) technologies that alters our perception of the machine from an instrument of human engineering into a thinking peer to elevate cyber from technical esoterism into an interdisciplinary field of public policy. The contribution to the US national cybersecurity policy body of knowledge is a unified policy framework (manifested in the symbiotic cybersecurity policy triad) that could transform cybersecurity policies from network-based to entity-based. A correlation archival data design was used with the frequency of malicious software attacks as the dependent variable and diversity of intrusion techniques as the independent variable for RQ1. For RQ2, the frequency of detection events was the dependent variable and diversity of intrusion techniques was the independent variable. Self-determination Theory is the theoretical framework as the cognitive machine can recognize, self-endorse, and maintain its own identity based on a sense of self-motivation that is progressively shaped by the machine’s ability to learn. The transformation of cyber policies from technical esoterism into an interdisciplinary field of public policy starts with the recognition that the cognitive machine is an independent consumer of, advisor into, and influenced by public policy theories, philosophical constructs, and societal initiatives
End-to-End Privacy for Open Big Data Markets
The idea of an open data market envisions the creation of a data trading
model to facilitate exchange of data between different parties in the Internet
of Things (IoT) domain. The data collected by IoT products and solutions are
expected to be traded in these markets. Data owners will collect data using IoT
products and solutions. Data consumers who are interested will negotiate with
the data owners to get access to such data. Data captured by IoT products will
allow data consumers to further understand the preferences and behaviours of
data owners and to generate additional business value using different
techniques ranging from waste reduction to personalized service offerings. In
open data markets, data consumers will be able to give back part of the
additional value generated to the data owners. However, privacy becomes a
significant issue when data that can be used to derive extremely personal
information is being traded. This paper discusses why privacy matters in the
IoT domain in general and especially in open data markets and surveys existing
privacy-preserving strategies and design techniques that can be used to
facilitate end to end privacy for open data markets. We also highlight some of
the major research challenges that need to be address in order to make the
vision of open data markets a reality through ensuring the privacy of
stakeholders.Comment: Accepted to be published in IEEE Cloud Computing Magazine: Special
Issue Cloud Computing and the La
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