Computational Models of Trust

We provide a defence against whitewashing for trust assessment mechanisms (TAM) by using an underlying social network in MAS and P2P. Since interaction requests are routed through the social network, routers can block requests from portions of the network known for whitewashing. Furthermore, by limiting feedback spread to the interaction routers, the trust assessment can be done without querying for feedback with a small loss in efficiency.

Currently, knowledge management is a key issue for companies as it gives them a competitive advantage. A Community of Practice (CoP) is a means to encourage employees to manage knowledge and enables them to exchange knowledge and experience. Members of these communities, however, are often geographically distributed. This hinders the development of feelings of trust between their members, which limits knowledge reuse. Our proposal seeks to minimize the effect of lack of trust between CoP members, thereby fostering the exchange of knowledge. To achieve this goal, we propose a trust model to calculate trust among CoP members, along with a multi-agent architecture to automatically manage the trust model in a CoP. The agents calculate a trust value in each situation, taking the user’s profile into account. We also present a tool that recommends sources of knowledge and documents that are trustworthy.

Cryptocurrencies based on blockchain infrastructures have shown their advantages such as double-spending
resistance and decentralization. Each transaction of cryptocurrency requires a certain amount of computation and
attracts transaction fees. Often, in practice, many transactions are small; therefore, they add computation and
transmission overheads to the system. In this paper, we introduce a cost-saving approach, which significantly
reduces transaction time and storage for small amount of payment, i.e. micropayment. Micropayment means the
value of transaction is small, i.e., payment worths a few pennies. To achieve instant micropayments, Hearn and
Spilman introduced a notion of payment channel. In this paper, we formally discuss the robustness requirements
of a scheme that is suitable for micropayments, consider the explicit value of penalty and user privacy leakage.
More precisely, we propose a micropayments scheme for decentralized blockchain-based payment system based on
the notion of payment channel, which enables a payee to receive funds at several unsynchronized points of sale and
penalize the double-spenders, with instant confirmation. In our approach, with the notion of ‘transaction
commitment’, the computation of each transaction is much more efficient. Therefore, our approach has advantages
in comparison of other cryptocurrency systems such as the bitcoin system. Our approach can be applied to other
existing cryptocurrency systems.

Nowadays knowledge management is a highly important issue for organizations since it helps to improve their competitive advantage. A means to encourage employees to manage knowledge is that of communities of practice in which employees can exchange knowledge and experience. However, members of these communities are often geographically distributed. This fact decreases the feeling of trust between their members and there is consequently less knowledge sharing. In order to avoid both this problem and others which occur in software organizations this paper describes a recommender system designed to support this kind of organizations.

In this paper we present a trust model for an enhanced version of MR2 micropayment scheme. We named this scheme TMR2. TMR2's lightweight trust model is based on user polling, sales volume and vendor's reputation. We claim that TMR2 can solve the mind barrier problem, which will result in the expansion of micropayment usage. The new token proposed to handle trust is a certificate called Rating certificate. We propose a new Rating certificate for merchants to support users' trust. Our proposed purchase process needs validation of this certificate, therefore, compared to MR2, the proposed scheme needs only one extra on-line digital signature validation. This validation adds less than 4 percent computational overhead in the purchase process, which is acceptable, considering the benefits that users will gain.

The development of novel high-throughput technologies has opened up the opportunity to deeply characterize patient tissues at various molecular levels and has given rise to a paradigm shift in medicine towards personalized therapies. Computational analysis plays a pivotal role in integrating the various genome data and understanding the cellular response to a drug. Based on that data, molecular models can be constructed that incorporate the known downstream effects of drug-targeted receptor molecules and that predict optimal therapy decisions. In this article, we describe the different steps in the conceptual framework of computational modeling. We review resources that hold information on molecular pathways that build the basis for constructing the model interaction maps, highlight network analysis concepts that have been helpful in identifying predictive disease patterns, and introduce the basic concepts of kinetic modeling. Finally, we illustrate this framework with selected stud...

In a multi-agent system (MAS), it is very usual that agents delegate tasks to each other. However, due to the subjectivity of the information used by agents during the decision-making process, an agent may end up delegating a task to an untrustworthy partner. In this work, we present a trust computing approach based on quantitative argumentation with votes (QuAD-V), where a trust measure is estimated according with the agents' opinions about the service provided by a partner. Besides, such an approach provides a mechanism to evaluate the credibility of agents that play as information sources. In our results, we demonstrate how our trust computing approach can be employed for detecting lying agents, which are able to slander or promote other agents. Resumo. Em um sistema multi-agente (SMA),é muito comum que os agentes deleguem tarefas uns aos outros. Contudo, devidoà subjetividade das informações utilizadas pelos agentes durante o processo de tomada de decisão, um agente pode acabar delegando uma tarefa a um parceiro não confiável. Neste trabalho, apresentamos uma abordagem de cálculo de confiança baseada em argumentação quantitativa com votação (QuAD-V), onde a confiançaé estimada de acordo com a opinião dos agentes sobre o serviço prestado por um parceiro. Além disso, tal abordagem fornece um mecanismo para avaliar a credibilidade dos agentes que atuam como fontes de informação. Como resultado, demonstramos como nossa abordagem de cálculo de confiança pode ser empregada para detectar agentes mentirosos capazes de caluniar ou promover outros agentes.

Many computational methods to predict the macromolecular targets of small organic molecules have been presented to date. Despite progress, target prediction methods still have important limitations. For example, the most accurate methods implicitly restrict their predictions to a relatively small number of targets, are not systematically validated on drugs (whose targets are harder to predict than those of non-drug molecules) and often lack a reliability score associated with each predicted target. Here we present a systematic validation of ligand-centric target prediction methods on a set of clinical drugs. These methods exploit a knowledge-base covering 887,435 known ligand-target associations between 504,755 molecules and 4,167 targets. Based on this dataset, we provide a new estimate of the polypharmacology of drugs, which on average have 11.5 targets below IC50 10 µM. The average performance achieved across clinical drugs is remarkable (0.348 precision and 0.423 recall, with la...

A proposal of offline transaction system in cellular transactions based on the study of micro-transactions. Actually, it is an study of implementation of safer transaction system in cellular network. The past framework has wide usage of PKI and hashing to outfit solid and secure transaction in cellular commerce. The present work has endeavoured to give considerably more light weight secure offline transactions. The observational activity is completed on three sorts of exchange process considering most extreme situation of offline cases. Therefore, the present thought presents two new approaches i.e. mobile agents and token that can guarantee better security and relatively less system overhead

Cinnamons are a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming approach combining declarative and imperative features. It supports powerful tools for control of the computation process; in particular, these tools allow easy, intuitive, visual development of heuristic, nondeterministic, or randomized solutions. The paper providesrigorous definitions of the syntax and semantics of the new model of computation, at the same time trying to keep the intuition behind clear. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing completeness), and the "real" CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming and its theoretical foundation into the directions of nondeterminism, randomness and fuzziness.

Abstract. Studies on trust in information sources have mostly focused on whether the source is capable of providing correct and complete information, thus overlooking another essential aspect of trust: the assessment of relevance. Information, even when true, is literally useless, unless it relates meaningfully to the informational needs and practical goals of its recipient. Moreover, relevance, exactly like truth, is not a self-evident feature of information: agents frequently realize whether or not an information was relevant for their purposes only ex ...

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

Currently, knowledge management is a key issue for companies as it gives them a competitive advantage. A Community of Practice (CoP) is a means to encourage employees to manage knowledge and enables them to exchange knowledge and experience. Members of these communities, however, are often geographically distributed. This hinders the development of feelings of trust between their members, which limits knowledge reuse. Our proposal seeks to minimize the e®ect of lack of trust between CoP members, thereby fostering the exchange of knowledge. To achieve this goal, we propose a trust model to calculate trust among CoP members, along with a multi-agent architecture to automatically manage the trust model in a CoP. The agents calculate a trust value in each situation, taking the user's pro¯le into account. We also present a tool that recommends sources of knowledge and documents that are trustworthy.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

The micropayment has a special position in mobile commerce (m-commerce). Micropayment systems allow payments with low values. In these systems amount of payments are very low so implementation of security is limited to necessity. One of the problems which is considerable in Payword base micropayment systems is that users have to create a new payword chain for each vendor. MVPayword system is an extension to Payword which make it possible for users to buy from various vendors using only one hash chain. According to the fact that nowadays many people use mobile device for purchases, in this paper we propose a model for using MVPayword in m-commerce. This model provides anonymity for customers against vendor and broker. Indeed it prevents mobile users (MUs) to do double-spending and it can prevent inventing and stealing Paywords. Moreover this model prevents MUs from spending more than credit and it prevents MU fraud and NO fraud.

In this paper we focus on the importance of generalized knowledge: agents' categories. The cognitive advantage of generalized knowledge can be synthesized in this claim: "It allows us to know a lot about something/somebody we do not directly know". At a social level this means that I can know a lot of things on people that I never met; it is social "prejudice" with its good side and fundamental contribution to social exchange. In this study we experimentally inquire the role played by categories' reputation with respect to the reputation and opinion on single agents: when it is better to rely on the first ones and when are more reliable the second ones. We will consider two different scenarios: one strongly influenced by the spatial distance between agents (localized world); the other totally independent by the spatial distances (non-localized world), quite similar to the modern web society, in which the communicative distance follows different routs with...

We present the results from a series of experiments aimed at uncovering the discourse structure of man-machine communication in natural language (Wizard of Oz experiments). The results suggest the existence of different classes of dialogue situations, requiring computational discourse representations of various complexity. Important factors seem to be the number of different permissible tasks in the system and to what extent the system takes initiative in the dialogue. We also analyse indexical expressions and especially the use of pronouns, and suggest a psychological explanation of their restricted occurrence in these types of dialogues.

Coral reefs are highly biodiverse ecosystems and provide vital resources for the human population. Due to increasing pressure by climate change and local stressors, these ecosystems currently face a global crisis. The development of tools to monitor how coral reefs respond to environmental change is a key aspect of the conservation of their biodiversity and resources. A number of reef organisms produce fluorescent molecules, including photosynthetic pigments and green fluorescent protein (GFP)-like pigments found in Anthozoa. These pigments are responsive to environmental conditions and can be optically monitored in vivo, making them a promising tool to investigate organism- and community-level processes on coral reefs. In this thesis, the fundamental principles and technological developments necessary for the application of fluorescence as a biomarker are explored. First, the mechanisms regulating coral fluorescence are considered for two functionally and biochemically distinct gro...

Recently, electronic commerce has become the focus of Information Technology development. Many electronic payment protocols and systems have been launched onto the Internet, but most of them induce complex cryptography and authentication mechanisms that incur relatively high processing costs and are therefore not feasible for micropayment transactions. For this reason, the mobile agent semantic is integrated to cope with the concerned difficulty. An agent-based transaction model is developed for processing micropayment transactions in a distributed environment and the corresponding system is built upon an OMG MASIF compliant agent platform. The novel agent-based transaction protocols are blends of the existing SET card payment and MilliCent micropayment protocols coupled with mobile agent characteristics respectively. As mobile agents can migrate to the desired communication peer and utilize the advantage of local interactions, goals like reduction of network traffic and simplification of communication protocol are readily attainable through such agentbased transaction protocols.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

In open MAS it is often a problem to achieve agents' interoperability. The heterogeneity of its components turns the establishment of interaction or cooperation among them into a non trivial task, since agents may use different internal models and the decision about trust other agents is a crucial condition to the formation of agents' cooperation. In this paper we propose the use of an ontology to deal with this issue. We experiment this idea by enhancing the ART reputation model with semantic data obtained from this ontology. This data is used during interaction among heterogeneous agents when exchanging reputation values and may be used for agents that use different reputation models.

Trust and reputation have proved to help protect societies against harmful individuals. Inspired by these principles, many computational models have been and new ones continue to be proposed in the literature to protect multiagent systems. In an open system, where few assumptions have to be made on the internals of the agents, it is possible that different agents use different trust and reputation models. Since agents have to exchange information to make their trust and reputation models more robust, and since the models use very different internal concepts and metrics, it is very important to consider the interoperability of these models. Based on experiments, this paper illustrate the usefulness of the SOARI architecture, which allows heterogeneous agents to inter-operate about reputation using high level semantics.

Interaction between heterogeneous agents can raise some problems since agents may not use the same models and concepts. Therefore, the use of some mechanisms to achieve interoperability between models allows agents to interact. In this paper we consider the case of reputation models by describing an experience of using several existing technologies to allow agents to interoperate when they use reputation notions/values during interactions. For this purpose, we have implemented agents on the ART testbed and we make them use a functional ontology of reputation which was developed to allow the interoperability among reputation models.

Everyone agrees on the importance of enabling trust on the SemanticWeb to ensure more efficient agent interaction. Current research on trust seems to focus on developing computational models, semantic representations, inference techniques, etc. However, little attention has been given to the plausible trust strategies or tactics that an agent can follow when interacting with other agents on the Semantic Web. In this paper we identify five most common strategies of trust and discuss their envisaged costs and benefits. The aim is to ...

The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can affect decisions. Existing trust and reputation mechanisms typically rely on reports from as many sources as possible to mitigate the influence of misleading reports on decisions. In the real world, however, it is often the case that querying information sources can be costly in terms of energy, bandwidth, delay overheads, and other constraints. We present a model of source selection and fusion in resource-constrained environments, where there is uncertainty regarding the trustworthiness of sources. We exploit diversity among sources to stratify them into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases. Through controlled experiments, we demonstrate that a diversity-based approach is robust to biases introduced due to dependencies among source reports, performs significantly better than existing approaches when sampling budget is limited and equally as good with an unlimited budget.

This work describes a cognitive heuristic allowing agents to assess trust and delegations merging heterogenous information sources. The model is realized through Uninformed Cognitive Maps, based on the combination of: (i) categorization abilities (ii) history of personal experiences (iii) context awareness.

In open and dynamic multiagent systems (MASs), agents often need to rely on resources or services provided by other agents to accomplish their goals. During this process, agents are exposed to the risk of being exploited by others. These risks, if not mitigated, can cause serious breakdowns in the operation of MASs and threaten their long-term wellbeing. To protect agents from the uncertainty in the behavior of their interaction partners, the age-old mechanism of trust between human beings is re-contexted into MASs. The basic idea is to let agents self-police the MAS by rating each other on the basis of their observed behavior and basing future interaction decisions on such information. Over the past decade, a large number of trust management models were proposed. However, there is a lack of research effort in several key areas, which are critical to the success of trust management in MASs where human beings and agents coexist. The purpose of this paper is to give an overview of existing research in trust management in MASs. We analyze existing trust models from a game theoretic perspective to highlight the special implications of including human beings in an MAS, and propose a possible research agenda to advance the state of the art in this field. INDEX TERMS Trust, reputation, multi-agent systems, game theory. Tran and Cohen [2] Tran [3] Castelfranchi et al. [4] Kollingbaum Fullam and Barber [5] Fullam et al. [6] and Norman [7] Griffiths [8] Yu and Singh [9] Falcone and Huynh et al. [10] Teacy et al. [11] Kerr and Cohen [12] Castelfranchi [13] Zheng et al. [38] Teacy et al. [14] Falcone et al. [15] Hermoso et al. [16] Burnett et al. [17] Bedi et al. [18] Regan et al. [19] Ashri et al. [20] Pasterneck and Roth [21] Dondio and Wang and Singh [22] Casare and Barrett [23] Sichman [24] Osman and Fullam and Messa and Robertson [25] Barber [26] Avesani [27] Reece et al. [28] Hendrix and Katz and Grosz [29] Golbeck [30] Wang and Kawamura et al. [31] Kuter and Singh [32] Golbeck [33] Reches et al. [34] Procaccia et al. [35] O'Donovan et al. [36] Teacy et al. [37] Wang and Singh [32] Rettinger et al. [38] Khosravifar Hang et al. [39] Burnett et al. [40] et al. [41] Matt et al. [42] Tang et al. [43] Koster et al. [44] Salihi-Abari and Liu et al. [45] Li and Wang [46] White [47] Vogiatzis et al. [48] Zhang et al. [49] Liu et al. [50] Koster et al. [44] Fang et al. [51] Liu and Datta [52] Pasternack and Haghpanah and Noorian et al. [53] Roth [21] desJar-dins [54] Witkowski [55] Koster et al. [56] Singh [57] Burnett and Liu et al. [58] Venanzi et al. [59] Oren [60] Jiang et al. [61] Piunti et al. [62] Liu and Datta [63] Serrano et al.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

Electronic payment systems are increasingly in need of improvement as they constitute the base for electronic commerce which is rapidly dominating much trade and particularly retail. One such system that allows payments of low value is known as micropayment system the main requirement for which is naturally 'low cost of transaction'. Payword is a micropayment system which uses hash chains and achieves better computational performance. It is a creditbased protocol involving a customer, vendor and broker. However, in this system users have to generate a new payword chain for each vendor from which they make a purchase and also their payment process is not anonymous. MVPayword was an extension to Payword which enables the user to make purchases from different vendors using only one hash chain. In this paper we shall introduce AMVPayword which is an extension to MVPayword and provides anonymity for customers. So users can be sure about the protection of their privacy in payment system.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

Electronic markets, distributed peer-to-peer applications and other forms of online collaboration are all based on mutual trust, which enables transacting peers to overcome the uncertainty and risk inherent in the environment. Reputation systems provide essential input for computational trust as predictions on future behaviour based on the past actions of a peer. In order to analyze the maturity of current reputation systems, we compare eleven reputation systems within a taxonomy of the credibility aspects of a reputation system. The taxonomy covers three topics: 1) the creation and content of a recommendation, 2) the selection and use of recommenders, and 3) the interpretation and reasoning applied to the gathered information. Although we find it possible to form a trusted reputation management network over an open network environment, there are still many regulatory and technical obstacles to address. This survey reveals various good mechanisms and methods used, but the area still requires both a) formation of standard mechanisms and metrics for reputation system collaboration and b) standard metainformation of right granularity for evaluating the credibility of reputation information provided.

Micropayments (payments worth a few pennies) have numerous potential applications. A challenge in achieving them is that payment networks charge fees that are high compared to "micro" sums of money. Wheeler (1996) and Rivest (1997) proposed probabilistic payments as a technique to achieve micropayments: a merchant receives a macro-value payment with a given probability so that, in expectation, he receives a micro-value payment. Despite much research and trial deployment, micropayment schemes have not seen adoption, partly because a trusted party is required to process payments and resolve disputes. The widespread adoption of decentralized currencies such as Bitcoin (2009) suggests that decentralized micropayment schemes are easier to deploy. Pass and Shelat (2015) proposed several micropayment schemes for Bitcoin, but their schemes provide no more privacy guarantees than Bitcoin itself, whose transactions are recorded in plaintext in a public ledger. We formulate and construct decentralized anonymous micropayment (DAM) schemes, which enable parties with access to a ledger to conduct offline probabilistic payments with one another, directly and privately. Our techniques extend those of Zerocash (2014) with a new privacypreserving probabilistic payment protocol. One of the key ingredients of our construction is fractional message transfer (FMT), a primitive that enables probabilistic message transmission between two parties, and for which we give an efficient instantiation. Double spending in our setting cannot be prevented. Our second contribution is an economic analysis that bounds the additional utility gain of any cheating strategy, and applies to virtually any probabilistic payment scheme with offline validation. In our construction, this bound allows us to deter double spending by way of advance deposits that are revoked when cheating is detected.

We propose MITRA, a meta-model for the information flow in (computational) trust and reputation architectures. On an abstract level, MITRA describes the information flow as it is inherent in prominent trust and reputation models from the literature. We use MITRA to provide a structured comparison of these models. This makes it possible to get a clear overview of the complex research area. Furthermore, by doing so, we identify interesting new approaches for trust and reputation modeling that so far have not been investigated.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

In this paper we will examine two main aspects of trust dynamics: a) How direct experiences involving trust, with their successes or failures, influence the future trust of an agent about similar facts. We challenge the trivial idea that always success increases trust while failure decreases it. Of course, this primitive view cannot be avoided till Trust is modeled just

In the last decades globalization dynamics have determined a continuous increase in freight flows and a growing global competition for the interception of these flows. This had a tremendous impact on the global supply chains configuration especially on ports, which must be able to handle an increasingly quantity of goods and to quickly ship them towards the consumer and production markets. In order to be able to do that, ports needs more and more space and, at the same time, they require an efficient organizational model for effectively manage so a big quantity of cargo. However many ports, being embedded in the city fabric, can't easily enlarge their borders for gaining new space and therefore they are obliged to look for new areas in the hinterland. These inner areas represents an extension of the ports borders and they are managed just as they were part of the maritime domain: for this reason they are called "dry ports". For an effective working of the "port-dry port" system, it is fundamental, among other things, that the related transportation infrastructures are suitable and functional to sustain the current and forecast freight flows. This paper regards the analysis of the railway system that joints Genoa port principal container terminals with an hypothetical dry port set in Alessandria, 90 km far from Genoa, with the objective of studying the possible infrastructural criticalities and suggesting proper solutions. To this aim, a simulation model has been developed and tested. The paper proposes the Discrete Event Simulation utilizing Arena software supported by MySQL Data Base Management System.

Mobile Ad hoc Networks (MANET) is one of the rapidly emanating technologies, which has gained attention in a wide range of applications in the fields of military, private sectors, commercials and natural calamities. Securing MANET is a dominant responsibility, and hence, a trust factor and fuzzy based intrusion detection and prevention system is proposed for routing in this paper. Based on the trust values of the nodes, the fuzzy system identifies the intruder, such that the path generated in the MANET is secured. Moreover, an optimization algorithm, entitled Fuzzy integrated Particle Swarm Optimization (Fuzzy-FPSO), is proposed by the concatenation of the Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) for the optimal path selection in order to provide secure routing. The simulation of the proposed methodology is NS2 simulator and analysis is carried out considering four cases, like without attack, flooding attacks, black hole attack and selective packet drop attack concerning throughput, delay and detection rate. The remarkable evaluation measures of the proposed Fuzzy-FPSO are the maximal throughput of 0.634, minimal delay of 0.044 , maximal detection rate of 0.697 and minimal routing overhead of 0.24550 And the evaluation measure for the case without any attacks are the maximal throughput of 0.762, minimal delay of 0.029 ,maximal detection rate of 0.805 and minimal routing overhead of 0.11511.

Cinnamons are a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming approach combining declarative and imperative features. It supports powerful tools for control of the computation process; in particular, these tools allow easy, intuitive, visual development of heuristic, nondeterministic, or randomized solutions. The paper providesrigorous definitions of the syntax and semantics of the new model of computation, at the same time trying to keep the intuition behind clear. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing completeness), and the "real" CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming and its theoretical foundation into the directions of nondeterminism, randomness and fuzziness.

Intrusion detection on mobile ad hoc networks (MANETs) is difficult. This is because of their dynamic nature, the lack of central points, and their highly resource-constrained nodes. In this paper we explore the use of evolutionary computation techniques, particularly genetic programming and grammatical evolution, to evolve intrusion detection programs for such challenging environments. Cognizant of the particular importance of power efficiency we analyze the power consumption of evolved programs and employ a multi-objective evolutionary algorithm to discover optimal trade-offs between intrusion detection ability and power consumption.

The development of electronic commerce has led to a new trend: the distribution of digital information. Micropayment systems come as an alternative, allowing the implementation of such transactions at low costs. This work introduces a micropayment system based on central generation of electronic coins that are bought by and distributed among customers and easily verified-and thus accepted as payment-by electronic commerce vendors. It differentiates itself by generating a single group of tokens that can be used for shopping in all of these vendors. This process is performed concerning security and scalability requirements. The development of electronic commerce has led to the development of a new category of payment systems. Many of them already exist and are currently being used, such as credit card and electronic money systems. However, these systems usually can't be used for small amount payments and they present high latencies for each transaction. Micropayment systems were designed to solve both questions to small amount transactions-concerning also security and scalability requirements that are inherent to any payment system to be implemented in open networks. The possibility of performing small amount transactions opens interesting new paths to electronic commerce: it makes selling information products-with values in the range of cents, such as images or access to information pages or individual news texts-possible.

Secure multi-party computation (MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. Among many secure MPC primitives, Shamir's secret sharing (SSS) has the advantages of having low complexity and information-theoretic security. However, SSS requires multiple honest participants and is susceptible to collusion attacks. In this paper, we provide a detailed analysis of different types of collusion attacks and propose novel mechanisms to deter such attacks in a fully distributed manner. Focusing on outsourced computing environments where secret data owners can collaborate on a public computing platform, we study collusion attacks using game-theoretic analysis. For those attacks where the thefts are detectable, we show that they can be effectively deterred by an explicit retaliation mechanism between data owners. The result is based on a comprehensive analysis that takes into account the cost of collusion, the privacy preference and the associated uncertainty. For those attacks where the thefts cannot be detected, we expand the analysis to include the computing platform and provide deterrence through deceptive collusion requests as well as a novel cryptographic censorship protocol. The correctness and privacy of the protocols are proved under the rational adversarial model. Our SSS-based protocols are shown to outperform state-of-the-arts garbled circuit systems while our simulation results validate the proposed mechanism designs in deterring collusion.

One-way hash chains have been used in many micropayment schemes due to their simplicity and efficiency. In this paper we introduce the notion of multi-dimensional hash chains, which is a new generalization of traditional one-way hash chains. We show that this construction has storage-computational complexity of O(log 2 N) per chain element, which is comparable with the best result reported in recent literature. Based on multi-dimensional hash chains, we then propose two cash-like micropayment schemes, which have a number of advantages in terms of efficiency and security. We also point out some possible improvements to PayWord and similar schemes by using multi-dimensional hash chains.

Everyone agrees on the importance of enabling trust on the SemanticWeb to ensure more efficient agent interaction. Current research on trust seems to focus on developing computational models, semantic representations, inference techniques, etc. However, little attention has been given to the plausible trust strategies or tactics that an agent can follow when interacting with other agents on the Semantic Web. In this paper we identify five most common strategies of trust and discuss their envisaged costs and benefits. The aim is to ...

Reputation systems have the potential of improving the quality of on-line markets by identifying fraudulent users and subsequently dealing with these users can be prevented. The behaviour of participants involved in e-commerce can be recorded and then this information made available to potential transaction partners to make decisions to choose a suitable counterpart. Unfortunately current reputation systems suffer from various vulnerabilities. Solutions for many of these problems will be discussed. One of the major threats is that of unfair feedback. A large number of negative or positive feedbacks could be submitted to a particular user with the aim to either downgrade or upgrade the user's reputation. As a result the produced reputation does not reflect the user's true trustworthiness. To overcome this threat a variation of Bayesian Reputation system is proposed. The proposed scheme is based on the subjective logic framework proposed Josang et al. [65]. The impact of unfair feedback is countered through some systematic approaches proposed in the scheme. Lack of anonymity for participants leads to reluctance to provide negative feedback. A novel solution for anonymity of feedback providers is proposed to allow participants to provide negative feedback when appropriate without fear of retaliation. The solution is based on several primitive cryptographic mechanisms; e-cash, designated verifier proof and knowledge proof. In some settings it is desirable for the reputation owner to control the distribution of its own reputation and to disclose this at its discretion to the intended parties. To realize this, a solution based on a certificate mechanism is proposed. This solution allows the reputation owner to keep the certificate and to distribute its reputation while not being able to alter that information without detection. The proposed solutions cater for two modes of reputation systems: centralised and decentralised. The provision of an off-line reputation system is discussed by proposing a new solution using certificates. This is achieved through the delegation concept and a variant of digital signature schemes known as proxy signatures. v The thesis presents a security architecture of reputation systems which consists of different elements to safeguard reputation systems from malicious activities. Elements incorporated into this architecture include privacy, verifiability and availability. The architecture also introduces Bayesian approach to counter security threat posed by reputation systems. This means the proposed security architecture in the thesis is a combination of two prominent approaches, namely, Bayesian and cryptographic, to provide security for reputation systems. The proposed security architecture can be used as a basic framework for further development in identifying and incorporating required elements so that a total security solution for reputation systems can be achieved. vi Declaration The work contained in this thesis has not been previously submitted for a degree or diploma at any higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

There have been a number of proposals for trust and reputation-based systems. Some have been implemented, some have been analysed only by simulation. In this paper we first present a general architecture for a trust-based system, placing special emphasis on the management of context information. We investigate the effectiveness of our architecture by simulating distributed attacks on a network that uses trust/reputation as a basis for access control decisions.

Route path identification on the Internet of Vehicles (IoV) is complicated due to the nature of high dynamic mobility, bandwidth constraints, and traffic load. A vehicle present on the IoV communicates with each other to find the status of the road and location of other vehicles for reliable data transmission. However, the existing routing algorithm does not effectively improve the packet delivery ratio and reduce the delay. To resolve these issues, A Quantile Regressive Fish Swarm Optimized Deep Convolutional Neural Learning (QRFSODCNL) technique is introduced reliable data transmission with minimum end to end delay in IoV. The Do Convolutional Neural Learning uses multiple layers such as one input layer, three hidden layers, and one output layer for vehicle location identification and optimal route path discovery. The different node characteristics of vehicle nodes are analyzed in the hidden layers using the quantile regression function. Depends on the regression analysis, the nei...

Recently Peer-to-Peer Content Delivery Networks (P2P CDNs) have attracted considerable attention as a cost-effective way to disseminate digital contents to paid users in a scalable and dependable manner. However, due to its peer-to-peer nature, it faces threat from "colluders" who paid for the contents but illegally share them with unauthorized peers. This means that the detection of colluders is a crucial task for P2P CDNs to preserve the right of contents holders and paid users. In this paper, we propose two colluder detection schemes for P2P CDNs. The first scheme is based on the reputation collected from all peers participating in the network and the second scheme improves the quality of colluder identification by using a technique which is well known in the field of system level diagnosis. The performance of the schemes is evaluated by simulation. The simulation results indicate that even when 10% of authorized peers are colluders, our schemes identify all colluders without causing misidentifications.

Micropayments are increasingly being adopted by a large number of applications. However, processing micropayments individually can be expensive, with transaction fees exceeding the payment value itself. By aggregating these small transactions into a few larger ones, and using cryptocurrencies, today's decentralized probabilistic micropayment schemes can reduce these fees. Unfortunately, existing solutions force micropayments to be issued sequentially, thus to support fast issuance rates a customer needs to create a large number of escrows, which bloats the blockchain. Moreover, these schemes incur a large computation and bandwidth overhead, which limit their applicability in large-scale systems. In this paper, we propose MicroCash, the first decentralized probabilistic framework that supports concurrent micropayments. MicroCash introduces a novel escrow setup that enables a customer to concurrently issue payment tickets at a fast rate using a single escrow. MicroCash is also cost effective because it allows for ticket exchange using only one round of communication, and it aggregates the micropayments using a lottery protocol that requires only secure hashing. Our experiments show that MicroCash can process thousands of tickets per second, which is around 1.7-4.2x times the rate of a state-of-the-art sequential micropayment system. Moreover, MicroCash supports any ticket issue rate over any period using only one escrow, while the sequential scheme would need more than 1000 escrows per second to permit high rates. This enables our system to further reduce transaction fees and data on the blockchain by ∼ 50%.