PRIVACY LEVEL ALIEN PARALLEL TRUST AGAINST SYBIL ATTACK IN P2P E-COMMERCE

Peer to peer (P2P) e-commerce applications exist at the edge of the Internet with vulnerabilities to passive and active attacks. These attacks have pushed away potential business firms and individuals whose aim is to get the best benefit in e-commerce with minimal losses. The attacks occur during interactions between the trading peers as a transaction takes place. Sybil attack is addressed as an active attack, in which peers can have bogus and multiple identities to fake their own. Most existing work, which concentrates on social networks and trusted certification, has not been able to prevent Sybil attack peers from doing transactions. Neighbor similarity trust relationship is used to address Sybil attack. Duplicated Sybil attack peers can be identified as the neighbor peers become acquainted and hence more trusted to each other

A Numerical Approach for Assigning a Reputation to Users of an IoT Framework

AbstractNowadays, in the Internet of Things (IoT) society, the massive use of technological devices available to the people makes possible to collect a lot of data describing tastes, choices and behaviours related to the users of services and tools. These information can be rearranged and interpreted in order to obtain a rating (i.e., evaluation) of the subjects (i.e., users) interacting with specific objects (i.e., items). Generally, reputation systems are widely used to provide ratings to products, services, companies, digital contents and people. Here, we focus on this issue, adopting a Collaborative Reputation System (CRS) to evaluate the visitors' behaviour in a real cultural event. The results obtained, compared with those obtained by other methods (i.e., classification), have confirmed the reliability and the usefulness of CRSes for deeply understand dynamics related to visiting styles

REPUTATION SYSTEMS IN THE SERVICE OF AVOIDANCE OF CRISIS SITUATIONS IN TOURISM

Reputacija predstavlja kolektivni stav kao rezultat pojedinačnih mišljenja određene zajednice. Korisnicima online usluga reputacija predstavlja oblik očekivanoga ponašanja temeljenom na tuđem iskustvu, čime korisnik dobiva dojam da smanjuje rizik svoga poslovanja. Upravo zbog projekcije očekivanoga ponašanja takvi sustavi pridonose izbjegavanju kriznih situacija. U skladu s tim, korisnik usmjerava svoj novac prema pružateljima usluga kod kojih se osjeća sigurno i dobiva pravu vrijednost za svoj novac. Prema tome, prosudba potpuno nepoznatih korisnika može donijeti određenu ekonomsku ili društvenu korist. Cilj je reputacijskih sustava osigurati korisnicima informacije o pouzdanosti određene usluge, stimulirati subjekte na korektno ponašanje, odvratiti korisnike od nepouzdanih prodavača i proširiti znanje o pouzdanim prodavačima. Tako se korisnicima smanjuje osjećaj poslovnoga rizika i povećava povjerenje u odnosu prodavač-kupac. U ovom radu obradit će se pojam reputacijskih sustava i način na koji mogu utjecati na poboljšanje turističke ponude i, prije svega, na izbjegavanje mogućih kriznih situacija. Istražit će se Google Review reputacijski sustav u Varaždinu i usporediti ocjene ugostiteljskih objekata i turistički atraktivnih objekata da bi se pronašli ključni pojmovi u vezi s prednostima i problemima pojedinih ugostiteljskih objekata i turističkih atrakcija s ciljem daljnjega unapređenja poslovanja i povećanja konkurentnosti.Reputation is a collective attitude as a result of the individual opinions of a particular community. For users of online services, a reputation is a form of expected behaviour based on someone else\u27s experience, thus the user has the impression that he is reducing the risk of his business. Precisely because of the projection of expected behaviour, such systems contribute to the avoidance of crisis situations. Accordingly, the user directs his money to those service providers with whom he feels safe and gets the right value for his money. Therefore, the judgment of completely unknown users may bring some economic or social benefit. The goal of reputational systems is to provide users with information about the reliability of a particular service, stimulate entities to behave correctly, deter users from unreliable vendors, and expand knowledge about trusted vendors. This reduces the sense of business risk for customers and increases trust in the seller-buyer relationship. In this paper, we will discuss the concept of reputation systems and how they can affect the improvement of the tourist offer and, above all, the avoidance of possible crisis situations. As an example, we will explore the Google Review reputation system in the city of Varaždin in Croatia, where we will compare the ratings of restaurants and tourist attractions in order to find key concepts related to the advantages and problems of individual restaurants and tourist attractions in order to further improve business and increase competitiveness

The Reputation Evaluation Based on Optimized Hidden Markov Model in E-Commerce

Nowadays, a large number of reputation systems have been deployed in practical applications or investigated in the literature to protect buyers from deception and malicious behaviors in online transactions. As an efficient Bayesian analysis tool, Hidden Markov Model (HMM) has been used into e-commerce to describe the dynamic behavior of sellers. Traditional solutions adopt Baum-Welch algorithm to train model parameters which is unstable due to its inability to find a globally optimal solution. Consequently, this paper presents a reputation evaluation mechanism based on the optimized Hidden Markov Model, which is called PSOHMM. The algorithm takes full advantage of the search mechanism in Particle Swarm Optimization (PSO) algorithm to strengthen the learning ability of HMM and PSO has been modified to guarantee interval and normalization constraints in HMM. Furthermore, a simplified reputation evaluation framework based on HMM is developed and applied to analyze the specific behaviors of sellers. The simulation experiments demonstrate that the proposed PSOHMM has better performance to search optimal model parameters than BWHMM, has faster convergence speed, and is more stable than BWHMM. Compared with Average and Beta reputation evaluation mechanism, PSOHMM can reflect the behavior changes of sellers more quickly in e-commerce systems

On the vulnerabilities of voronoi-based approaches to mobile sensor deployment

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above characterization, we propose two new secure deployment algorithms, named SecureVor and Secure Swap Deployment (SSD). These algorithms allow a sensor to detect compromised nodes by analyzing their movements, under different and complementary operative settings. We show that the proposed algorithms are effective in defeating a barrier attack, and both have guaranteed termination. We perform extensive simulations to study the performance of the two algorithms and compare them with the original approach. Results show that SecureVor and SSD have better robustness and flexibility and excellent coverage capabilities and deployment time, even in the presence of an attac

Securing Logs in Operation-based Collaborative Editing

The Twelfth International Workshop on Collaborative Editing Systems, CSCW'12International audienceIn recent years collaborative editing systems such as wikis, GoogleDocs and version control systems became very popular. In order to improve reliability, fault-tolerance and availability shared data is replicated in these systems. User misbehaviors can make the system inconsistent or bring corrupted updates to replicated data. Solutions to secure data history of state-based replication exist, however they are hardly applied to operation-based replication. In this paper we propose an approach to secure log in operation-based optimistic replication system. authenticators based on hash values and digital signatures are generated each time a site shares or receives new updates on replicas. authenticators secure logs with security properties of integrity and authenticity. We present in detail algorithms to construct and verify authenticators and we analyse their complexities

Flow-based reputation: more than just ranking

The last years have seen a growing interest in collaborative systems like electronic marketplaces and P2P file sharing systems where people are intended to interact with other people. Those systems, however, are subject to security and operational risks because of their open and distributed nature. Reputation systems provide a mechanism to reduce such risks by building trust relationships among entities and identifying malicious entities. A popular reputation model is the so called flow-based model. Most existing reputation systems based on such a model provide only a ranking, without absolute reputation values; this makes it difficult to determine whether entities are actually trustworthy or untrustworthy. In addition, those systems ignore a significant part of the available information; as a consequence, reputation values may not be accurate. In this paper, we present a flow-based reputation metric that gives absolute values instead of merely a ranking. Our metric makes use of all the available information. We study, both analytically and numerically, the properties of the proposed metric and the effect of attacks on reputation values

Manipulating Scrip Systems: Sybils and Collusion

Game-theoretic analyses of distributed and peer-to-peer systems typically use the Nash equilibrium solution concept, but this explicitly excludes the possibility of strategic behavior involving more than one agent. We examine the effects of two types of strategic behavior involving more than one agent, sybils and collusion, in the context of scrip systems where agents provide each other with service in exchange for scrip. Sybils make an agent more likely to be chosen to provide service, which generally makes it harder for agents without sybils to earn money and decreases social welfare. Surprisingly, in certain circumstances it is possible for sybils to make all agents better off. While collusion is generally bad, in the context of scrip systems it actually tends to make all agents better off, not merely those who collude. These results also provide insight into the effects of allowing agents to advertise and loan money. While many extensions of Nash equilibrium have been proposed that address collusion and other issues relevant to distributed and peer-to-peer systems, our results show that none of them adequately address the issues raised by sybils and collusion in scrip systems.Comment: 20 pages, 5 figures. To appear in the Proceedings of The First Conference on Auctions, Market Mechanisms and Their Applications (AMMA '09