Removing the Digital Divide for Senior Web Users

It is hard for the elderly to use the internet to find the resource they want. Usually help is needed for them to complete the task on the technology things. The main reason for this project is to research ideas on encourage senior people to make use of the web to locate helps they want, such as finding volunteers and professional helps. The scope of this project is to develop a new way of web access and content presentation methodologies that let senior people getting help from volunteers and various service providers more easily that incorporates social networking technology e.g. Facebook. By incorporating the social network web site like Facebook into the web application, senior people will be able to find volunteering help or other related service providers through social networking. Volunteers will show up in Google map in search results for senior to easily locate helps. Senior people can also search for self help videos tutorials through the web application search engine. A mobile version of the senior user application will also be developed for easy access on the road. Other features that benefit senior users includes voice input, control / content posting and collaborative social networking where a sponsors would sponsor a help task volunteer undertake

TellEat: sharing experiences on the move

In a context where, due to the proliferation of mobile devices, virtual social environments on the Web are taking up a very concrete role in the way people experience their surroundings, the Future Internet seems to be headed toward a mixture of Social Web, Semantic Web and Augmented Reality. As a part of a larger project that aims at building a social network of both people and things, we designed and developed TellEat, an iPhone-based application that allows users in mobility to share facts concerning people or objects that participate in the social network, and to discover pertinent events that have been told by others. In this paper we discuss both the client application, with the interaction model and interface metaphors that have been designed to make the experience as playful as possible for users, and the server-side services that provide the necessary knowledge and reasoning mechanisms. We also present the results of preliminary tests with users

Leveraging Machine Learning for Network Intrusion Detection in Social Internet Of Things (SIoT) Systems

This research investigates the application of machine learning models for network intrusion detection in the context of Social Internet of Things (SIoT) systems. We evaluate Convolutional Neural Network with Generative Adversarial Network (CNN+GAN), Generative Adversarial Network (GAN), and Logistic Regression models using the CIC IoT Dataset 2023. CNN+GAN emerges as a promising approach, exhibiting superior performance in accurately identifying diverse intrusion types. Our study emphasizes the significance of advanced machine learning techniques in enhancing SIoT security by effectively detecting anomalous behaviours within socially interconnected environments. The findings provide practical insights for selecting suitable intrusion detection methods and highlight the need for ongoing research to address evolving intrusion scenarios and vulnerabilities in SIoT ecosystems

Research on multi-layer network routing selection strategy based on cooperative evolutionary game in IoT environment

As a new technology and application mode, the Internet of Things has an important impact on social life and economic development. In recent years, low-cost optimization of network transmission to solve the congestion problem of multi-layer communication networks has become one of the research hotspots. In this paper, a multi-dimensional communication data transmission model based on a multi-layer network is proposed. It then uses cooperative evolutionary game theory to calculate revenue, update weights, and adapt neighbors. Finally, the attention mechanism is dynamically introduced to share the weights of the multi-layer network, and the multi-dimensional communication propagation and routing strategies in the Internet of Things are studied and analyzed. The experimental results show that the model proposed in this paper has higher game revenue and application value than traditional single-layer network game theory. In particular, the indicators of cooperation rate, stable state, and maximum cooperation rate are better than the latter. The research results of this paper have important reference value for solving the problems of cooperation dilemma, social stickiness, and synergy in multi-layer networks

Assignment of sensing tasks to IoT devices: Exploitation of a Social Network of Objects

The Social Internet of Things (SIoT) is a novel communication paradigm according to which the objects connected to the Internet create a dynamic social network that is mostly used to implement the following processes: route information and service requests, disseminate data, and evaluate the trust level of each member of the network. In this paper, the SIoT paradigm is applied to a scenario where geolocated sensing tasks are assigned to fixed and mobile devices, providing the following major contributions. The SIoT model is adopted to find the objects that can contribute to the application by crawling the social network through the nodes profile and trust level. A new algorithm to address the resource management issue is proposed so that sensing tasks are fairly assigned to the objects in the SIoT. To this, an energy consumption profile is created per device and task, and shared among nodes of the same category through the SIoT. The resulting solution is also implemented in the SIoT-based Lysis platform. Emulations have been performed, which showed an extension of the time needed to completely deplete the battery of the first device of more than 40% with respect to alternative approaches

NEW ASPECTS OF RUSSIAN NATIONAL SECURITY SYSTEM IN THE CONDITIONS OF PEACEFUL WAR

Abstract Purpose: The aim of the present article is to identify new dangers and threats posed by the state of peaceful war, which is inherent in the information network society, as well as corresponding to these threats’ new aspects of Russia's national security. Methodology: As research methodology we use an interdisciplinary research strategy, a topological approach, a synergy paradigm, the concept of the Internet of things, the theory of cultural-historical psychology, the concept of positive construction of social reality, propositions of quantum sociology, the concept of “peaceful war” (“hybrid war”, “multidimensional war”), strategies and methods for implementing the systemic nature of Russia's national security. Result: The result is that new aspects of Russia's national security, connected with the “peaceful war”, peculiarities of the impact of new information and communication technologies (ICT) and the Internet of Things as a global computing system (network of networks) on human consciousness, giving specific features to the system of security, and, first of all, its information, psychological, military, cultural and educational components, are shown for the first time. Applications: The application of interdisciplinary, topological and synergistic approaches makes it possible to find out the peculiarities of the impact of ICT and Internet of Things on human consciousness, which functions in accordance with the Mobius band metaphor. Novelty/Originality: The scientific novelty consists in an attempt to apply the concept of “peaceful war”, encompassing all spheres of public life, in order to develop an adequate system for ensuring Russia's national security

Network Analysis of Innovation in the Internet of Things

Background: In the Internet of Things (IoT) firms, innovation beyond the border of a company is important. Furthermore, advantageous positioning in the innovation network is thought to enhance the result of innovation and ultimately contribute to profit. Objectives: The objective of this research is to clarify empirically the influence of the network structure among companies on innovation in the IoT field. Method: In this research, the relationship between the network structure and the result of innovation was analysed through social network analysis. Joint application patents related to the IoT companies were extracted from the intellectual property database. Results: As a result, the difference in the network structure of a company was related to the result of research and profitability. In particular, a company with a platform type of business model is considered highly profitable in the IoT business field. Conclusion: Drawing on an intellectual property database and employing social network analysis, this research quantifies the structure of innovation networks in terms of the results and operational efficiency of R&D

RFID/INTERNET OF THINGS SYSTEMS ON THE BOUNDARY BETWEEN PUBLIC AND PRIVATE SECTORS: AN ANT STUDY OF MULTIPLICITY

Radio Frequency Identification (RFID) systems are becoming increasingly common in applications that are shared between the public and private sectors. These systems facilitate supply chain, traceability and sensor functions, not to mention the application of RFID technology in enabling the Internet of Things. Despite their increasing ubiquity, the management of public-private RFID systems is under-researched and little understood. This research addresses a gap in literature by using Actor-Network Theory (ANT) to uncover the public-private RFID network. It was found that the public-private sector relationship is initially characterised by stereotypical views which diminish as sectors work together. Further, the public sector in this context was seen to be a multiplicity with four different performances, public sector as a member of the public-private partnership; as legislator; as enforcer and as funding provider. This multiplicity is shown to lead to confusion within public-private partnerships as members of the partnership are not always clear about which performance of the public sector they are enacting, or interacting with. ANT provided a sound basis to explore such a complex networked system, its inclusion of technology within the construction of the social offers a way of understanding complexity within internet of things based applications

Inferring Network Usage from Passive Measurements in ISP Networks: Bringing Visibility of the Network to Internet Operators

The Internet is evolving with us along the time, nowadays people are more dependent of it, being used for most of the simple activities of their lives. It is not uncommon use the Internet for voice and video communications, social networking, banking and shopping. Current trends in Internet applications such as Web 2.0, cloud computing, and the internet of things are bound to bring higher traffic volume and more heterogeneous traffic. In addition, privacy concerns and network security traits have widely promoted the usage of encryption on the network communications. All these factors make network management an evolving environment that becomes every day more difficult. This thesis focuses on helping to keep track on some of these changes, observing the Internet from an ISP viewpoint and exploring several aspects of the visibility of a network, giving insights on what contents or services are retrieved by customers and how these contents are provided to them. Generally, inferring these information, it is done by means of characterization and analysis of data collected using passive traffic monitoring tools on operative networks. As said, analysis and characterization of traffic collected passively is challenging. Internet end-users are not controlled on the network traffic they generate. Moreover, this traffic in the network might be encrypted or coded in a way that is unfeasible to decode, creating the need for reverse engineering for providing a good picture to the Internet operator. In spite of the challenges, it is presented a characterization of P2P-TV usage of a commercial, proprietary and closed application, that encrypts or encodes its traffic, making quite difficult discerning what is going on by just observing the data carried by the protocol. Then it is presented DN-Hunter, which is an application for rendering visible a great part of the network traffic even when encryption or encoding is available. Finally, it is presented a case study of DNHunter for understanding Amazon Web Services, the most prominent cloud provider that offers computing, storage, and content delivery platforms. In this paper is unveiled the infrastructure, the pervasiveness of content and their traffic allocation policies. Findings reveal that most of the content residing on cloud computing and Internet storage infrastructures is served by one single Amazon datacenter located in Virginia despite it appears to be the worst performing one for Italian users. This causes traffic to take long and expensive paths in the network. Since no automatic migration and load-balancing policies are offered by AWS among different locations, content is exposed to outages, as it is observed in the datasets presented