A multi-dimensional trust-model for dynamic, scalable and resources-efficient trust-management in social internet of things

L'internet des Objets (IoT) est un paradigme qui a rendu les objets du quotidien, intelligents en leur offrant la possibilité de se connecter à Internet, de communiquer et d'interagir. L'intégration de la composante sociale dans l'IoT a donné naissance à l'Internet des Objets Social (SIoT), qui a permis de surmonter diverse problématiques telles que l'interopérabilité et la découverte de ressources. Dans ce type d'environnement, les participants rivalisent afin d'offrir une variété de services attrayants. Certains d'entre eux ont recours à des comportements malveillants afin de propager des services de mauvaise qualité. Ils lancent des attaques, dites de confiance, et brisent les fonctionnalités de base du système. Plusieurs travaux de la littérature ont abordé ce problème et ont proposé différents modèles de confiance. La majorité d'entre eux ont tenté de réappliquer des modèles de confiance conçus pour les réseaux sociaux ou les réseaux pair-à-pair. Malgré les similitudes entre ces types de réseaux, les réseaux SIoT présentent des particularités spécifiques. Dans les SIoT, nous avons différents types d'entités qui collaborent, à savoir des humains, des dispositifs et des services. Les dispositifs peuvent présenter des capacités de calcul et de stockage très limitées et leur nombre peut atteindre des millions. Le réseau qui en résulte est complexe et très dynamique et les répercussions des attaques de confiance peuvent être plus importantes. Nous proposons un nouveau modèle de confiance, multidimensionnel, dynamique et scalable, spécifiquement conçu pour les environnements SIoT. Nous proposons, en premier lieu, des facteurs permettant de décrire le comportement des trois types de nœuds impliqués dans les réseaux SIoT et de quantifier le degré de confiance selon les trois dimensions de confiance résultantes. Nous proposons, ensuite, une méthode d'agrégation basée sur l'apprentissage automatique et l'apprentissage profond qui permet d'une part d'agréger les facteurs proposés pour obtenir un score de confiance permettant de classer les nœuds, mais aussi de détecter les types d'attaques de confiance et de les contrer. Nous proposons, ensuite, une méthode de propagation hybride qui permet de diffuser les valeurs de confiance dans le réseau, tout en remédiant aux inconvénients des méthodes centralisée et distribuée. Cette méthode permet d'une part d'assurer la scalabilité et le dynamisme et d'autre part, de minimiser la consommation des ressources. Les expérimentations appliquées sur des de données synthétiques nous ont permis de valider le modèle proposé.The Internet of Things (IoT) is a paradigm that has made everyday objects intelligent by giving them the ability to connect to the Internet, communicate and interact. The integration of the social component in the IoT has given rise to the Social Internet of Things (SIoT), which has overcome various issues such as interoperability, navigability and resource/service discovery. In this type of environment, participants compete to offer a variety of attractive services. Some of them resort to malicious behavior to propagate poor quality services. They launch so-called Trust-Attacks (TA) and break the basic functionality of the system. Several works in the literature have addressed this problem and have proposed different trust-models. Most of them have attempted to adapt and reapply trust models designed for traditional social networks or peer-to-peer networks. Despite the similarities between these types of networks, SIoT ones have specific particularities. In SIoT, there are different types of entities that collaborate: humans, devices, and services. Devices can have very limited computing and storage capacities, and their number can be as high as a few million. The resulting network is complex and highly dynamic, and the impact of Trust-Attacks can be more compromising. In this work, we propose a Multidimensional, Dynamic, Resources-efficient and Scalable trust-model that is specifically designed for SIoT environments. We, first, propose features to describe the behavior of the three types of nodes involved in SIoT networks and to quantify the degree of trust according to the three resulting Trust-Dimensions. We propose, secondly, an aggregation method based on Supervised Machine-Learning and Deep Learning that allows, on the one hand, to aggregate the proposed features to obtain a trust score allowing to rank the nodes, but also to detect the different types of Trust-Attacks and to counter them. We then propose a hybrid propagation method that allows spreading trust values in the network, while overcoming the drawbacks of centralized and distributed methods. The proposed method ensures scalability and dynamism on the one hand, and minimizes resource consumption (computing and storage), on the other. Experiments applied to synthetic data have enabled us to validate the resilience and performance of the proposed model

IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

IoT trust and reputation: a survey and taxonomy

IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilized across the globe by the end of 2030. To maximize the capability of these connected entities, trust and reputation among IoT entities is essential. Several trust management models have been proposed in the IoT environment; however, these schemes have not fully addressed the IoT devices features, such as devices role, device type and its dynamic behavior in a smart environment. As a result, traditional trust and reputation models are insufficient to tackle these characteristics and uncertainty risks while connecting nodes to the network. Whilst continuous study has been carried out and various articles suggest promising solutions in constrained environments, research on trust and reputation is still at its infancy. In this paper, we carry out a comprehensive literature review on state-of-the-art research on the trust and reputation of IoT devices and systems. Specifically, we first propose a new structure, namely a new taxonomy, to organize the trust and reputation models based on the ways trust is managed. The proposed taxonomy comprises of traditional trust management-based systems and artificial intelligence-based systems, and combine both the classes which encourage the existing schemes to adapt these emerging concepts. This collaboration between the conventional mathematical and the advanced ML models result in design schemes that are more robust and efficient. Then we drill down to compare and analyse the methods and applications of these systems based on community-accepted performance metrics, e.g. scalability, delay, cooperativeness and efficiency. Finally, built upon the findings of the analysis, we identify and discuss open research issues and challenges, and further speculate and point out future research directions.Comment: 20 pages, 5 Figures, 3 tables, Journal of cloud computin

Reputation assessment in collaborative environments.

The popularity of open collaboration platforms is strongly related to the popularity of Internet: the growing of the latter (in technology and users) is a spring to the former. With the advent of Web 2.0, not only the Internet users became from passive receiver of published content to active producer of content, but also active reviewers and editors of content. With the increase of popularity of these platforms, some new interesting problems arise related on how to choose the best one, how to choose the collaborators and how evaluate the quality of the final work. This evolution has brought much benefit to the Internet community, especially related to the availability of free content, but also gave rise to the problem of how much this content, or these people, may be trusted. The purpose of this thesis is to present different reputation systems suitable for collaborative environments; to show that we must use very different techniques to obtain the best from the data we are dealing with and, eventually, to compare reputations systems and recommender systems and show that, under some strict circumstances, they become similar enough and we can just make minor adjustment to one to obtain the other

Reputation assessment in collaborative environments.

The popularity of open collaboration platforms is strongly related to the popularity of Internet: the growing of the latter (in technology and users) is a spring to the former. With the advent of Web 2.0, not only the Internet users became from passive receiver of published content to active producer of content, but also active reviewers and editors of content. With the increase of popularity of these platforms, some new interesting problems arise related on how to choose the best one, how to choose the collaborators and how evaluate the quality of the final work. This evolution has brought much benefit to the Internet community, especially related to the availability of free content, but also gave rise to the problem of how much this content, or these people, may be trusted. The purpose of this thesis is to present different reputation systems suitable for collaborative environments; to show that we must use very different techniques to obtain the best from the data we are dealing with and, eventually, to compare reputations systems and recommender systems and show that, under some strict circumstances, they become similar enough and we can just make minor adjustment to one to obtain the other

Asset rich cash poor in the economic downturn: the financial challenges facing retired older people

Older people are thought to be particularly vulnerable during times of economic downturn. Little is currently understood of the impact of the current economic downturn on the financial circumstances and wellbeing of retired people and the nature of the services and support needed to enable them to cope financially and maintain their wellbeing and quality of life. Retired people are not a homogenous group. Therefore, this study explores the impact of the downturn on a specific group: house owners over the age of 65, not in receipt of means tested state benefits and living on modest incomes. This group may be described as “asset rich cash poor” (ARCPs). It is thought that this group is particularly vulnerable as they are not eligible for state support but are insufficiently well off to be living comfortably. Findings from this research, although focused on retired people with specific circumstances, may have wider relevance in relation to retired people with different financial circumstances. The purpose of this study is to investigate the experiences of asset rich cash poor older people in the economic downturn, in order to establish: • how they manage their financial circumstances in these times; • the impact of the downturn on their wellbeing and quality of life; and • whether services and support available to this group and other older people could be improved. The study comprised two phases. In phase one, the perspectives of older people were explored by carrying out 28 semi-structured interviews with older people in the asset rich cash poor category, permanently resident in Dorset, some of whom lived in a conurbation and others in rural areas. In phase two, the study explored perspectives of key financial advice/information/service providers through four focus groups comprising: health and social care professionals; financial advisors from the private sector; and professionals from the third (not for profit) sector. 6 ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN The study has shown that the economic downturn is having a marked impact on the financial, social, mental and physical wellbeing of this sample of asset rich cash poor older people in Dorset. For many, the level of income that they had expected when planning for retirement had not come to fruition and they feel poor in relation to their previous lifestyle and retirement expectations. The key findings and policy implications of the study are: Key finding 1: Many ARCP older people particularly women, had done little retirement planning. Many ARCP older people had insufficiently planned for their retirement. In particular some women had relied on their husbands to manage all finances and had not provided for their own pensions. This reflects the findings of earlier studies on the older generation. Policy implications The independent Money Advice Service (formerly the FSA Consumer Financial Education Board) should commit greater financial resource to the awareness raising and skill development of future generations to help people plan more carefully for their retirement. Although the findings of this study show a widespread need among older people for information and advice, resources should be targeted particularly at women, especially those who have had extended periods out of workplace. Private, public and voluntary sector services should respond to this increased investment through developing and testing out models of financial capability training, with an emphasis on financial planning, as well as its mode of delivery. There may be potential in raising awareness of the need for retirement planning and associated training to non-working women through health visiting or child care services. For older people who have planned ahead, pensions and savings have been traditionally seen as a key way to plan responsibly for one’s retirement future. But these are not risk free as has been played out in the recent years of economic downturn, with the associated low interest rates and return on investment. People planning ahead for retirement need to be reminded of the impact of any future recession and the risks of this if it coincides with their planned retirement date. ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN 7 Key finding 2: Older people, in the ARCP category, tended to manage the money they had very carefully, despite the economic downturn, and had an aversion to debt. This finding mirrors the quantitative study of Atkinson et al. (2006) who found older people to be better at managing money than the younger generations. In discussion of the financial pressures placed upon them in term of escalating essential and non-essential expenditure, no interviewees referred to having resorted to unsecured debt. Policy implications Managing money is identified in this study and earlier studies as a strength within older people. Therefore, financial capability training for this age group should focus on the other dimensions of financial capability where older people are less skilled, for example choosing financial products and staying informed. Older people should be considered an asset in society and their strong skills in managing money should be utilised. Those organisations wishing to develop and deliver financial capability curricula for younger people could consider intergenerational programmes in which older people participate as guest speakers, sharing their experiences in managing money with younger generations. These educators could be encouraged to work together with the Money Advice Service and the Department of Health and financial advice and information providers to bring various age groups together. Key finding 3: The combination of reduced income from investments, increases in pensions which do not keep pace with inflation, combined with increases in costs for essential and non-essential expenditure, is having an impact on social, physical and mental wellbeing and is causing noticeable life style changes. The effects of the economic downturn on ARCP older people’s wellbeing was highlighted by both older people themselves and service providers. In both phases of the research, reference is made to feelings of anxiety, worry, fear, depression and concern. 8 ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN Policy implications Reduced wellbeing during the economic downturn in this age group is likely to put an increased demand on health and social care services. Policy makers in the Department of Health have a vested interest therefore in developing strategies to counter this negative impact. One recommendation to enhance social wellbeing is that the Money Advice Service, the Department of Health and local councils fund national and local initiatives to further support and develop social clubs or other groups for older people, with an emphasis on financial planning and management. This would help sustain wellbeing and provide a network of peers with whom older people might exchange financial experiences and information. Third and private sector organisations such as care homes and age related charities are well-placed to contribute to the development of these programmes. Key finding 4: The economic downturn is impacting on older people indirectly though cuts to public and third sector services. The economic downturn has been associated with cuts in funding to many services previously relied on by older people for their physical, social and mental wellbeing. Library closures were a cause of concern and a particular worry was the risk of withdrawal of bus passes. Policy implications Private sector service providers will need to fill the gap in services that currently support the health and wellbeing of older people, a gap left by the increased withdrawal of public and third sector services. A reduction of these services in particular will have a strong impact on the social, mental and physical wellbeing of older people. Key finding 5: Older people, in the ARCP category, do not always access enough or appropriate financial information. Many choose to seek financial information from trusted health and social care providers, their family and/or friends rather than from financial professionals. Older people, and professionals that support them, reported that older people are not always accessing the sound financial information which they may need, whether it be on financial products, forward financial planning or how to obtain the benefits they are entitled to. Lack of trust in financial advisors was widespread. Independent financial advisors indicated that older people on lower incomes were using their services less frequently. Some were either self-reliant by researching ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN 9 on the internet or using the media, or tapped into sources of social capital found within their social networks. Policy implications More effort and resource needs to be put in place to address these very serious concerns about access to advice and support by older people. Older people are approaching health professionals for financial advice, despite the fact that these professionals may not be best placed to provide this. Health professionals need to be able to direct these queries to trained financial service providers. Financial services within the private sector should therefore form interagency partnerships with more trusted public and third sector services in order to improve access to the services they provide. There is a very significant concern about lack of trust in advisors and banks. The need to rebuild reputation must be addressed by regulators, the advisors and banks themselves, with an increased emphasis being placed on the value systems of financial services and the role they can play in promoting community and individual wellbeing. The strength of the social networks of older people should also be harnessed, suggesting again that there is potential in targeting or developing social clubs for older people as locations to enhance financial capability. Key finding 6: In order to make ends meet, some older people in the ARCP category may take greater financial risks or be more vulnerable to abuse in an economic downturn. The professionals that support older people expressed concerns that the economic downturn may push older people towards riskier behaviours without them fully understanding the implications of the risks. There is also a risk of older people becoming more vulnerable to financial abuse. Policy implications Policy makers need to ensure that older people are made aware of the risks of financial abuse. As older people are often turning to more trusted health and social care providers for advice on financial matters, health/social care providers as well as financial service providers should both develop means to keep their older clients regularly informed of potential financial risk within the current economic climate. As financial support is not the remit of many of the health care providers and financial services is a regulated activity, it is advisable they form partnerships with the finance sector, in order to better inform their patients/clients of current financial risks or to be able to refer them on to qualified support. Service providers may also 10 ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN offer a helpline in which older people feel safe to disclose, anonymously if need be, any concerns of financial abuse they may be exposed to. Charities already offering these services (e.g. Age UK and Action on Elder Abuse-AEA) should be supported in these endeavours through encouraging partnerships between financial service providers on the one hand and health/social care providers on the other in order that the latter can provide accurate and up to date information on financial risk to its partners. A recent partnership between local financial advisors and the charity Age UK is an excellent example of this (Age UK, 2012). It is also essential that the Money Advice Service raises awareness of this risk. As the provision of financial services is a regulated activity, it is important to ensure that any activities undertaken by health/social care providers are not in breach of financial services regulations. Key finding 7: Older people made no reference to the Money Advice Service or the Financial Services Authority (FSA) as a source of help or advice. At the time of this study none of the interviewees of the focus groups made any reference to the role of the Financial Service Authority (FSA) or the Money Advice Service in providing information or advice about financial matters to older people. Policy implications Although the Money Advice Service is now independent of the FSA, and is endeavoring to target a wider population, it is not clear why our interviewees never referred to it. It may either be due to a lack of awareness of the service, a serious indictment of the outreach of the FSA, or alternatively a lack of IT expertise in older people, demonstrated also by their very limited use of online banking. In either event, older people may be denied access to key forms of help and advice on financial matters. Resources need to be devoted to either increasing IT literacy among older people, or alternatively providing help and support using traditional forms of communication and/or increasing the reach of the Money Advice Service by targeting this age group specifically. In conclusion, therefore, older people in this study reported being affected markedly by the current economic downturn. Members of the financial sector, including accountants, and the Money Advice Service have a responsibility to support older people during this and future downturns. They must reflect on ways in which they might tailor their support towards this group. One way of doing so is by actively seeking collaborative interagency partnerships with third and public sector health and social care professionals to improve their access and understanding of older ASSET RICH CASH POOR IN THE ECONOMIC DOWNTURN 11 clients. These more trusted professionals will be able to direct financial enquiries to accountants and financial advisors who older people may otherwise not have had the confidence, knowledge or trust to approach directly. Accountants and other financial services should also be aware of the particular challenges facing asset rich but cash older people and adapt their advice accordingly when dealing with this group. They should reflect in their consultations that many older people are fully capable of managing their money but are in greater need of advice on how to invest their money and plan ahead for their future. They should also think outside of the box in providing support, considering ways, for example, in which the power of existing social networks might be harnessed. 12 ASSET RICH CASH POOR IN THE ECONOMIC DOWNTUR

Reputation assessment in collaborative environments.

The popularity of open collaboration platforms is strongly related to the popularity of Internet: the growing of the latter (in technology and users) is a spring to the former. With the advent of Web 2.0, not only the Internet users became from passive receiver of published content to active producer of content, but also active reviewers and editors of content. With the increase of popularity of these platforms, some new interesting problems arise related on how to choose the best one, how to choose the collaborators and how evaluate the quality of the final work. This evolution has brought much benefit to the Internet community, especially related to the availability of free content, but also gave rise to the problem of how much this content, or these people, may be trusted. The purpose of this thesis is to present different reputation systems suitable for collaborative environments; to show that we must use very different techniques to obtain the best from the data we are dealing with and, eventually, to compare reputations systems and recommender systems and show that, under some strict circumstances, they become similar enough and we can just make minor adjustment to one to obtain the other

Evolutionary Service Composition and Personalization Ecosystem for Elderly Care

Current demographic trends suggest that people are living longer, while the ageing process entails many necessities, calling for care services tailored to the individual senior’s needs and life style. Personalized provision of care services usually involves a number of stakeholders, including relatives, friends, caregivers, professional assistance organizations, enterprises, and other support entities. Traditional Information and Communication Technology based care and assistance services for the elderly have been mainly focused on the development of isolated and generic services, considering a single service provider, and excessively featuring a techno-centric approach. In contrast, advances on collaborative networks for elderly care suggest the integration of services from multiple providers, encouraging collaboration as a way to provide better personalized services. This approach requires a support system to manage the personalization process and allow ranking the {service, provider} pairs. An additional issue is the problem of service evolution, as individual’s care needs are not static over time. Consequently, the care services need to evolve accordingly to keep the elderly’s requirements satisfied. In accordance with these requirements, an Elderly Care Ecosystem (ECE) framework, a Service Composition and Personalization Environment (SCoPE), and a Service Evolution Environment (SEvol) are proposed. The ECE framework provides the context for the personalization and evolution methods. The SCoPE method is based on the match between the customer´s profile and the available {service, provider} pairs to identify suitable services and corresponding providers to attend the needs. SEvol is a method to build an adaptive and evolutionary system based on the MAPE-K methodology supporting the solution evolution to cope with the elderly's new life stages. To demonstrate the feasibility, utility and applicability of SCoPE and SEvol, a number of methods and algorithms are presented, and illustrative scenarios are introduced in which {service, provider} pairs are ranked based on a multidimensional assessment method. Composition strategies are based on customer’s profile and requirements, and the evolutionary solution is determined considering customer’s inputs and evolution plans. For the ECE evaluation process the following steps are adopted: (i) feature selection and software prototype development; (ii) detailing the ECE framework validation based on applicability and utility parameters; (iii) development of a case study illustrating a typical scenario involving an elderly and her care needs; and (iv) performing a survey based on a modified version of the technology acceptance model (TAM), considering three contexts: Technological, Organizational and Collaborative environment

Trust Management for Internet of Things: A Systematic Literature Review

Internet of Things (IoT) is a network of devices that communicate with each other through the internet and provides intelligence to industry and people. These devices are running in potentially hostile environments, so the need for security is critical. Trust Management aims to ensure the reliability of the network by assigning a trust value in every node indicating its trust level. This paper presents an exhaustive survey of the current Trust Management techniques for IoT, a classification based on the methods used in every work and a discussion of the open challenges and future research directions.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Bidding for Complex Projects: Evidence From the Acquisitions of IT Services

Competitive bidding (as auctions) is commonly used to procure goods and services. Public buyers are often mandated by law to adopt competitive procedures to ensure transparency and promote full competition. Recent theoretical literature, however, suggests that open competition can perform poorly in allocating complex projects. In exploring the determinants of suppliers’ bidding behavior in procurement auctions for complex IT services, we find results that are consistent with theory. We find that price and quality do not exhibit the classical tradeoff one would expect: quite surprisingly, high quality is associated to low prices. Furthermore, while quality is mainly driven by suppliers’ experience, price is affected more by the scoring rule and by the level of expected competition. These results might suggest that (scoring) auctions fail to appropriately incorporate buyers’ complex price/quality preferences in the tender design.Procurement Auctions, Scoring Rules, IT Contracts, Price/Quality Ratio