A layered approach to network management control

Public telecommunications networks have many supporting operations systems to provide network management functions and operational support. These systems must be coordinated to provide a highly reliable network service and to make best use of network resources. With increasing automation of network control, these systems must evolve to provide total network support. One organizing principle for this evolution is the definition of control layers at which individual control functions are exercised. We describe a proposal for layered control, with particular emphasis on the role of network traffic management. Layering will be a significant study item for the next extensions to CCITT's Telecommunications Management Network (TMN) recommendations.     

P2P环境下基于声誉的信任管理模型

在分析以往面向节点与面向资源的信任管理模型的优点与不足的基础上,提出一个新的基于声誉的信任管理模型。该模型首先根据价值量对节点所拥有的资源进行分类,在此基础上进而综合考虑资源与节点的声誉问题。模型通过节点以往交互行为的评价信息来对将要发生的行为进行预测与判断。此外,讨论了关于声誉值初始化的问题,使得模型更加具有实际意义。     

Collaborative trust aware intelligent intrusion detection in VANETs

Trust aware Collaborative Learning Automata based Intrusion Detection System (T-CLAIDS) for VANETs is proposed in this paper. Learning Automata (LA) are assumed to be deployed on vehicles in the network to capture the information about the different states of the vehicles on the road. A Markov Chain Model (MCM) is constructed for representation of states and their transitions in the network. Transitions from one state to other are dependent upon the density of the vehicles in a particular region. A new classifier is designed for detection of any malicious activity in the network and is tuned based upon the new parameter called as Collaborative Trust Index (CTI) so that it covers all possible types of attacks in the network. An algorithm for detection of abnormal events using the defined classifier is also proposed. The results obtained show that T-CLAIDS performs better than the other existing schemes with respect to parameters such as false alarm ratio, detection ratio and overhead generated.     

A service recovery method based on trust evaluation in mobile social network

Mobile social network makes users create and share multimedia contents freely and conveniently. However, some nodes in mobile social network have malicious behavior, such as discarding or tampering packet. These factors will cause service interruptions in the process of providing multimedia contents for the user. When the service interruption happens, how to choose the more reliable backup device, reduce interruption number, increase the packet transmission efficiency and improve user’s experience of sharing multimedia contents is the object of this paper. We propose a service recovery method based on trust evaluation which adopts Dempster-Shafer (D-S) evidence theory. The service requester calculates the direct trust degree and the recommended trust degree of the backup devices, then uses the evidence combination rule to calculate the comprehensive trust degree. The backup device with the highest trust value will be seclected to recover the service. The simulation results show that this method effectively improves the packet delivery ratio, reduces the service execution time and provides users with more stable multimedia contents.     

A social network approach to resolving group-level conflict in context-aware services

Group conflict that occurs when delivering context-aware services negatively affects service usage within a specific service space, and researchers have proposed few conflict resolution methods to address the issue. This paper presents a methodology to autonomously resolve the conflict arising between users in identical contexts, such as place and computing resources. To do so, a two-phase case-based reasoning method is proposed. To minimize privacy concerns, a social network model is applied to produce key social context data, secondary to personal data, and which is used in place of the users’ personal data for case-based reasoning. To show the feasibility of the idea proposed in this paper, a prototype system with simulation-based validation is tested to determine conflict resolution strategies and a simulation test has been performed.     

Context-aware trust network extraction in large-scale trust-oriented social networks

In recent years, social networking sites have been used as a means for a rich variety of activities, such as movie recommendations and product recommendations. In order to evaluate the trust between a truster (i.e., the source) and a trustee (i.e., the target) who have no direct interaction in Online Social Networks (OSNs), the trust network between them that contains important intermediate participants, the trust relations between the participants, and the social context, has an important influence on trust evaluation. Thus, to deliver a reasonable trust evaluation result, before performing any trust evaluation (i.e., trust transitivity), the contextual trust network from a given source to a given target needs to be first extracted from the social network, where constraints on social context should also be considered to guarantee the quality of the extracted networks. However, this problem has been proved to be NP-Complete. Towards solving this challenging problem, we first present a contextual trust-oriented social network structure which takes social contextual impact factors, including trust, social intimacy degree, community impact factor, preference similarity and residential location distance into account. These factors have significant influences on both social interactions between participants and trust evaluation. Then, we present a new concept QoTN (Quality of Trust Network) and propose a social context-aware trust network extraction model. Finally, we propose a Heuristic Social Context-Aware trust Network extraction algorithm (H-SCAN-K) by extending the K-Best-First Search (KBFS) method with several proposed optimization strategies. The experiments conducted on two real datasets illustrate that our proposed model and algorithm outperform the existing methods in both algorithm efficiency and the quality of the extracted trust networks.     

An architectural approach for decentralized trust management

To guard against malicious peers, peer-to-peer applications must incorporate suitable trust mechanisms. Current decentralized trust-management research focuses mainly on producing trust models and algorithms, whereas the actual composition of trust models into real applications has been largely unexplored. The practical architectural approach for composing egocentric trust (Pace) provides detailed design guidance on where and how developers can incorporate trust models into decentralized applications. In addition, Pace's guiding principles promote countermeasures against threats to decentralized systems. Several prototypes demonstrate the approach's use and feasibility.     

A pessimistic approach to trust in mobile agent platforms

The problem of protecting an execution environment from possibly malicious mobile agents has been studied extensively, but the reverse problem, protecting the agent from malicious execution environments, has not. We propose an approach that relies on trusted and tamper-resistant hardware to prevent breaches of trust, rather than correcting them after the fact. We address the question of how to base trust on technical reasoning. We present a pessimistic approach to trust that tries to prevent malicious behavior from occurring in the first place, rather than correcting it after it has occurred     

A metrology-based approach for measuring the social dimension of cognitive trust in collaborative networks

This paper addresses the measurement of the social dimension of cognitive trust in collaborative networks. Trust indicators are typically measured and combined in literature in order to calculate partners’ trustworthiness. When expressing the result of a measurement, some quantitative indication of the quality of the result—the uncertainty of measurement—should be given. However, currently this is not taken into account for the measurement of the social dimension of cognitive trust in collaborative networks. In view of this, an innovative metrology-based approach for the measurement of social cognitive trust indicators in collaborative networks is presented. Thus, a measurement result is always accompanied by its uncertainty of measurement, as well as by information traditionally used to properly interpret the results: the sample size, and the standard deviation of the sample.

     

A network modeling approach to policy implementation in natural resource management agencies

Natural resource agencies are responsible for managing specific aspects of the environment through the development and implementation of policies. Computational advances have emerged in recent years that provide opportunities for simulating the influence that agency structure has on policy outcomes, particularly those stemming from the area of network theory and analysis. However, there remains a need for methods that can measure and visualize the confounding effects that multiple agency characteristics may impose on policy implementation. The complex interactions among these factors require an approach that can evaluate these factors in relation to one another and provide a way to abstract meaningful findings that can be useful for both scientists and agencies to consider for future policy development. In this study, we present a network simulation modeling approach that (1) builds upon existing conceptualizations of bureaucrat decision-making within agency networks, (2) uses network theory to construct idealized natural resource agency networks that can be used to evaluate how agency structure influences policy implementation, and (3) visualizes simulation results to better understand how bureaucrat behaviors and relationships in concert with agency structure influence policy outcomes. Using this approach, we demonstrate how different aspects of decision-making by bureaucrats interact with the spatial constraints of institutional networks to influence policy outcomes. The network modeling and visualization methods presented here offer an alternative approach in the policy science toolbox that can help generate new assumptions and questions about the ways in which natural resources are governed.     

Social network,social trust and shared goals in organizational knowledge sharing

The aim of our study was to further develop an understanding of social capital in organizational-knowledge-sharing. We first developed a measurement tool and then a theoretical framework in which three social capital factors (social network, social trust, and shared goals) were combined with the theory of reasoned action; their relationships were then examined using confirmatory factoring analysis. We then surveyed of 190 managers from Hong Kong firms, we confirm that a social network and shared goals significantly contributed to a person's volition to share knowledge, and directly contributed to the perceived social pressure of the organization. The social trust has however showed no direct effect on the attitude and subjective norm of sharing knowledge.     

LBTM: A lightweight blockchain-based trust management system for social internet of things

The Journal of Supercomputing - In order for the Internet of things to facilitate information sharing, the technology needs trustworthy mechanisms to ensure safe communications and reliable...     

A trust evaluation scheme for complex links in a social network: a link strength perspective

Potential security threats pose a significant challenge to evaluating the trustworthiness of complex links among users in a social network. Traditional trust computation methods typically consider user comments or interaction, thereby reflecting the trustworthiness between users according to their past experiences. However, the tie strength, which reflects the closeness of user relationships, is also a potential factor for estimating the trustworthiness of links among users. To incorporate this indicator, we propose a trust evaluation scheme for complex links comprising two aspects: the reliability and strength of links among uses. Our main contributions are (1) a trust calculation method, including direct trust for directly linked users and indirect trust for indirectly linked users, which is established based on the comment factor, forwarding factor, and approving factor; (2) a link strength evaluation method to determine the trustworthiness of direct and indirect links between users considering comment stability, mutual trust, interaction frequency, and common neighbours and community similarity, and (3) a link trust evaluation algorithm based on the link trust matrix synthesizing the reliability and strength of links. The experimental results and analysis show that our proposed scheme is feasible and effective in improving the performance of trust evaluation in a social network.     

A group trust metric for identifying people of trust in online social networks

With the growth of social network services, the need for identifying trustworthy people has become a primary concern in order to protect users’ vast amounts of information from being misused by unreliable users. In this study, we propose the extended Advogato trust metric that facilitates the identification of trustworthy users associated with each individual user. By incorporating the strength of social relationships, we recursively diffuse a capacity of a target user throughout his/her personal network. Based on the capacity propagation, this paper also presents the capacity-first maximum flow method capable of finding the strongest path pertinent to discovering an ordered set of reliable users and preventing unreliable users from accessing personal networks. Experimental results demonstrate that our approach has advantages over existing representative methods in terms of both the discovery of reliable users and the preventability of unreliable users.     

A proposal to contribute to ITS standardization activity: A valuable network mobility management approach

The introduction of communication services in the demanding ITS scenarios strongly relies on the existence of technologies that enable mobility and security. ITS related standardization bodies, mainly ISO and ETSI, are actively producing and developing new specifications in this regard. In this paper, we study those ITS standards related to security and communication efficiency and analyze the suitability of our NeMHIP protocol, in order to be considered for ITS scenarios. NeMHIP provides secure mobility while at the same time constitutes a framework to protect user data and services. In addition, despite being based on the introduction of a new namespace, its introduction in the current Internet architecture is considered affordable. Aware of the need to satisfy users for having a new technology accepted in a certain scenario, we have also assessed analytically the efficiency of our approach. Specifically, in this paper we analyze and compare the handover signaling delay with the standardized NEMO BS protocol, showing that our approach provides satisfactory results and outperforms it in specific cases. Moreover, we present the results obtained by means of a simulation tool, and show that QoS requirements for the demanding video streaming application are fulfilled. All of these features make our approach a candidate for being considered by standardization organizations and a valuable facility for ensuring secure and efficient communications in the ITS.     

BSEM estimation of network effect and customer orientation empowerment on trust in social media and network environment

This paper presents a stochastic model that identifies network effect and customer orientation empowerment as strong antecedents of trustworthiness and trust in social media network environment. As Trust is emerging as a critical influencer of consumer behavior in organizations, social media has become the facilitator or the enabler of this influence. This paper aims to explore and examine the relationships amongst the antecedents of trust in the context of the social media network environment via Bayesian estimation and testing of the structural equation model. In facilitating the estimation of the stochastic model, a survey was conducted on 255 social media users. A series of statistical analyses were conducted prior to the estimation using Bayesian Markov Chain Monte Carlo (MCMC). Results showed that network effect and customer orientation empowerment were significant predictors of trustworthiness and trust. Bayesian MCMC results confirmed that the findings were consistent with the literature.     

A social approach to context-aware retrieval

We present a general purpose solution to Web content and services perusal by means of mobile devices, named Social Context-Aware Browser. This is a novel approach for information access based on users’ context, that exploits social and collaborative models to overtake the limits of the existing solutions. Instead of relying on a pool of experts and on a rigid categorization, as it is usually done in the context-aware field, our solution allows the crowd of users to model, control, and manage the contextual knowledge through collaboration and participation. To have a dynamic and user-tailored context representation, and to enhance the process of retrieval based on users’ actual situation, the community of users is encouraged to define the contexts of interest, to share, use, and discuss them, and to associate context to content and resources (Web pages, services, applications, etc.). This paper provides an overall presentation of our solution, describing the idea, the implementation, and the evaluation through a benchmark based methodology.     

A neural network approach to freeway network traffic control

The paper investigates the application of a feedforward neural network approach to freeway network control via variable direction recommendations at bifurcation locations. A nonlinear control problem is formulated and solved first by use of computationally expensive nonlinear optimization techniques. A feedforward neural network is then trained by optimally adjusting its weights so as to reproduce the optimal control law for a limited number of traffic scenarios. Generalisation properties of the neural network are investigated and a discussion of advantages and disadvantages compared with alternative control approaches is provided.     

Individuals’ personal network characteristics and patterns of Facebook use: A social network approach

Using the theoretical framework of ego-centric networks, this study examines the associations between the characteristics of both Facebook-specific and pre-existing personal networks and patterns of Facebook use. With data from an ego-network survey of college students, the study discovered that various dimensions of Facebook-specific network characteristics, such as multiplexity, proximity, density, and heterogeneity in race, were positively associated with usage patterns, including time spent on Facebook, posting messages, posting photos, and lurking. In contrast, network characteristics of pre-existing relationships, such as density and heterogeneity in race, were negatively associated with Facebook usage patterns. Theoretical implications and limitations were discussed.