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Trust Mechanisms

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Trust In Semantic Web

Muhammad Arslan Shafiq (081212) Department of Computer Science SZABIST Islamabad, Pakistan
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Abstract—Trust management is important in semantic web in order to achieve the goals of semantic web vision. In this paper two approaches of implementing trust have been discussed. One approach is strong and secure i.e. Policy based systems, the other approach is more of a social approach which takes feedback from the users in order to build and maintain trust. Also discussed in this paper are pros and cons of both the techniques.

Keywords-component; semantic web;Trust; Policy Based Systen; Reputation Based Sytems

Introduction

The idea behind semantic web seems great and offers a lot but why one should trust in semantic web. Who would trust such a system where anyone can say anything. We say that it is going to be a smart web, it will be intelligent and it will know the semantics. It will know what we are looking for. But what happens when a person says that x is yellow and another person says x is not yellow. Would semantic web fall apart? The idea behind SW is its authenticity of information which isn’t available in today’s web. Information comes from different sources which could be wrong or write and for a specific situation. So how are we going to determine which is reliable and whom should we believe? To tackle these kinds of situations we have semantic web trust. In this paper we are going to discuss different methods of implementing trust in SW.

1 Day to Day trust policies

Trust policy is a subjective practice used for the evaluation of the trustworthiness of information in a particular situation. For example ➢ Try pizza hut’s pizza but not pasta.

➢ Trust Abdullah on science fiction movies but not on political news.

➢ Believe in media only on sports news.

➢ See a movie if it’s IMDB's rating in above 7.

➢ Trust professors in their research field.

In order to successfully implement trust in semantic web stack we have to allow policies like these. s

2 Semantic Web Trust

At the top of semantic web stack sits Trust. At the core of trust are proof, signature and encryption. Signature and encryption are the two pillars that can provide functionality to all the layers of the SW stack to attain its eventual result.
Some methods that can be used to implement trust are: ➢ Policy Based Trust Management

➢ Reputation Based Trust Management

3 Policy-Based Trust Mechanism

Policy based trust mechanisms are used in those situations where firm security is required. Policy based trust mechanisms are targeted at those systems where performance is guided by complex rules and they should be adoptive to changes in the system easily [1]. In this bidirectional mechanism of trust, trust is established by the exchange of credentials in case of semantic web where those parties interact with each other which are primarily unknown to each other [2]. In environments where access control decisions are critical this system is frequently implemented [3]. Access or denial is given by analyzing the credentials which have been provided by unknown entities and implementation of set of trust policies on the provided credentials. Use of third party services (which are trusted) for the authentication of given credentials is also possible in this mechanism [3]. In sensitive environments where critical transactions are being made, it is an ideal system.

4 Reputation Based Trust Mechanism

The rating or reputation based system guides the people towards decision making process that is what product to trust and what not to. By implementing this reputation based system trustworthy sellers could be encouraged while dishonest ones could be dejected. There are a lot of online markets which have implemented the reputation based trust mechanism to promote trust in online transactions. Different companies bid over the WWW for a variety of items for several online companies. This system encourages both buyers and vendors to rate the transactions positively or negatively [4]. Feedback and comments option is provided by various online vendors for their customer to record what the customer has to say about the product they are selling. Example of these companies includes eBay, Amazon etc [5]. Overall reputation of the products can be seen by the buyers and companies with high rating products can make more profit due to this system [4].

Background

“The WWW is the world of networks-accessible information, and quintessence of human knowledge” –W3C. WWW is an organization of hyperlinked documents interconnected to each other via the network [23].
In today’s world everyone is aware of the World Wide Web, what it does and how it is used as the number of web users has surpassed two billion. The problem with today’s web is that it was designed for humans to read not for computer programs to read and manipulate data. Computers have no steadfast means of processing the semantics and bring structure to the meaningful content on the web i.e. it doesn’t know what you mean.
To make the web smart and intelligent we need “machine-understandable” content instead of machine “readable” (we already have that i.e. today’s web). This machine understandable smart web is called Semantic Web.

Semantic Web extends the currently existing standards of human-computer interaction which will allow the machines to analyze the information in a much better way which they merely display now [21]. This smart web has logic and it reasons why a particular decision has been reached. For example in the age of smart web if you search that you want to go to a movie and have dinner afterwards the web will be able to tell you where you can go to watch the movie and after that where you can have your dinner and probably it will make reservations for you itself depending upon your requirement as all the data objects will be pointing not to a URL but another data object that is through the use of URIs.
Some other emerging technologies like web services, agents; grid computing, p2p computing, and ubiquitous computing are intimately related to SW [6]. They make a pyramid like structure with SW at the base of it. So for the successful implantation of these emerging technologies it is very important that SW is successfully implemented [6].

1 Semantic Web Agents

Programs that gather info from different kind of sources are called Agents and they then have that information processed and have the results exchanged with other agents. In SW, primary consumers of knowledge are these agents. These SW agents are going to do the actual work for us by applying logic and reasoning to attain a result. Some characteristics an agent should have are: Intelligence, Autonomy, Reactivity, Pro-activeness and socials ability.

2 Types of agents

1 Multi-Agent System

MAS is a collection of numerous software agents, together they make they reach their goal which is difficult for individual agent. MAS agents should work autonomously and interpret with other as a part of MAS to achieve a goal [22].

2 Reactive Agents

These agents don’t deduce anything but are triggered by specific events. They respond to change of environment [22].
A (environment state) → action

3 Practical Reasoning Agents

These are the agents that perform reasoning. They work on BDI (Belief, desire, Intensions model) as seen in fig 1.

Figure 1
[pic]

3 Logic Layer

In this layer the actual logic is applied to the content of web. Roles of Logic layer can be seen in fig. 2.

[pic] Figure 2 [20]

IF THEN

4 Semantic Web Components

[pic]
Figure 3: Semantic Web Architecture from Google Images

At the core of Semantic Web stack is URI/IRI. URI is uniform source identifier. They are used to uniquely identify a Semantic Web resource. SW needs to uniquely identify resources to allow provable manipulation with in top layers.

Unicode is used to represent and process text in many languages.

Xml enables creation of documents with structured data.

XML Schema restricts the structure and content of elements contained within xml documents.

RDF is used to express data models which points to objects i.e. resources and their relationships.

Ontology establishes the things the system can talk and reason about. This means vocabulary. It supplies the terms and concepts.

As Query language SPARQL is used. It can be used to query any RDF-based data.

In logic layer computer will apply logical reasoning to every type of “statements” distributed across the web.

Proof explains why a particular conclusion has been reached.

Trust sits at the top of the semantic web stack. It verifies that the premises come from reliable sources. It relies on formal logic to derive new information.

Literature Review

1 Trust strategies for the semantic web [6]

Trust is the basic element in semantic web. Two or more individuals, companies, or countries can communicate at their best and make progress if a bond of trust is built between them. Adopting such a trustworthy behavior, by every person involved in the communication, makes the environment more effective and efficient. Semantic web basically joins or integrates data (on web) from multiple sources (web applications) and presents it on one platform. So when so many sources are involved, there is a huge factor of trust that needs to be addressed. This paper focuses on the probable ways that an entity, within the semantic web, may follow order to communicate with other entities.

Optimistic systems: trusts all other systems on the network, trusting every system is in the nature of such systems. But if a real reason exists, only then it distrusts.

Pessimistic Systems: As there are optimistic systems there are also pessimistic systems. Centralized systems: all the information related to trust is in a central system, the individual entity has trust only this centralized system and leave the rest to it.

Transitive Systems: The main goal of such systems is to gain information and knowledge from other unknown entities on the network.

Cost and Benefits:

Every strategy has its own properties, so before following any strategy one must be aware of its pro’s and con’s.

Operational cost: the whole setup for the trust strategy is managed in this cost. The more a strategy is complex the more the cost increases. Operational cost for optimistic, pessimistic, centralized and transitive is not very high.

Opportunity cost: during the communication, the cost for missing an opportunity of receiving a benefit is the opportunity cost. This cost will reduce in case of optimistic system. But as opposed to optimistic, in pessimistic systems this cost increases. These costs increase in central and the investigation strategy.

Deficiency cost: when one entity, tries to betray the other entity, by pretending what it’s not in reality, the cost involved in this case is the deficiency cost. The cost is high in case of optimistic systems and low in case of pessimistic systems. Investigative system lowers the cost where as the centralized systems increases it. Similarly in transitive systems this cost increases.

Service Charges: an entity might have to buy services from other entities on the network. The cost required for this are the service charges, which is high for the optimistic systems and low for the pessimistic systems. Investigative and transitive strategy has a high cost but in centralized systems this cost is low.

Challenges: When we talk about challenges, optimism and pessimism fail to accomplish the basic requirements of trust, where as centralized and investigation begin similar in some situations do provide a better level of trust.

2 Using context- and content-based trust policies on the semantic web [10]

This paper discusses the policies of trust in the semantic web, by discussing three trust mechanisms and presenting trust architecture. We have policies of trust that we follow in our routine life; similarly semantic web trust architecture also follows such trust policies, these policies till now fall in the reputation-based trust category, which take a lot of overhead to update the ratings [22].
Context-based trust mechanisms give information about the other data; that is, trust decisions are made by gathering information about the role of the person in a certain context.
Content-based trust mechanism unlike context based do not use information about the other data, whereas they use rules and the content information along with the data about those who also have shared their work related to the same topic.
This paper presents a trust architecture that will be a combination of all three, reputation-based, context-based and content-based, which will eventually provide the benefits of all three mechanisms. It suggests that semantic web does not require a third party for doing the trust management between two parties, rather it must be an open architecture and that the user must be able to have the knowledge as to why he/she should trust the other party.

3 An integration of reputation-based and policy-based trust management [7]

This paper compares two approaches to manage trust and then presents a solution for integrating both the approaches. It says that up till now there are basically two trust management approaches which were developed according to the need and circumstances of the situation. Both are not being used together.
Reputation based is very different to that of the policy based, in reputation the trust develops on the past experiences of the users, its reputation and the feedback. Whereas the policy-based, as the name suggests, is based on strict policies, we may call standard ways and rules upon which an entity either trusts or distrusts the other entity, there is no middles situation in this case.
The paper then tries to convince the reader that it’s not possible always that a user is only in need of policy-based -based trust or only reputation trust, for example one maybe interested to know that either a groups well reputed has a Certification authorities certificate or not, and maybe vice versa.
The main goal of policy-based trust management is to decide, whether the other entity is to be trusted or not, and its does so by following rules and policies. It either accepts or denies an entity for being trusted. The main purpose or reason for using policy-based is that a system needs strict and sensitive protection.
Reputation-based trust management is mostly used for the commercial purposed, like online shopping, e.g.; eBay, Amazon. As it is based on different past user’s feedbacks and rating the main challenge in this management scheme is the management and computation of this trust information.
This implies that both strategies, policy-based and reputation-based, have a common goal, but in totally different point of views. Further this paper presents an integrated approach by using some mathematical formulas and integrating both reputation-based and policy-based trust management, through which a semantic web will be able to face both type of problems using a single approach rather than using two separate approaches.

4 Ontology-Based Policy Specification and Management [11]

In this paper the writers have discussed that sharing information through internet has become very easy but few rules are being followed for the purpose of sharing. This paper shows how to develop, implement and manage these policies. In the end of the paper a prototype for such a system has been explained.

5 A Framework for Agent-Based Trust Management in Online Auctions [8]

In this paper the author has discussed that today’s commercial applications are not trustworthy at all until and unless a dynamic trust management system is built for this purpose, this paper discusses the ATM-agent based trust management in online auctions. At the end of this paper the writer has suggested a prototype ATM module.

6 Advantages of Policy Based Systems

➢ For the establishment of trustworthy relationships policy based systems are used because they are efficient and have a bidirectional approach [9].

➢ This system provides privacy and has improved security.

➢ It is well suited for those environments where the system has to decide whether to allow or deny access to specific services by analyzing the credentials [12].

➢ Because of its trustworthy and swift business transactions, good customer relationships are produced as the customers feels insured and part of the business expansion [12] .

➢ This system, in the form of credentials makes use of information like signature, age, nationality, identification to authenticate.

➢ The system answers the questions, explains and provides functionalities, that why specific information was trustworthy [13].

➢ Mostly, trust between two sides is established directly rather than involving any third party [2].

➢ Access is allowed only to those customers whose trustworthiness has been proven by the system.

➢ This system promoted the products and increases market shares [14].

➢ In some cases services of a trusted third party could also be utilized for authorization of certificates.

➢ Promotes lasting liaison with the partners in business [14].

7 Disadvantages of Policy Based Systems

➢ The information required for the pre-registration of the services is often irrelevant [9].

➢ Often, customers are unwilling to reveal their personal information in pre-registration phase and they leave the application [15].

➢ The credentials provided by the customers are also subject to trust in this system [15].

➢ Both sides are unwilling to reveal their information i.e. credentials to the other side.

➢ Because the decisions are binary in nature, customers have limited choices.

➢ Those clients who are willing to reveal their credentials are still insecure about the information they are providing and still think it a risk.

8 Advantages of Reputation Based Systems

➢ In reputation based systems a user is required to fill a simple form about the product which is an easy way of implementing trust.

➢ There is no communication between both the parties, which is an encouragement for high biddings from clients [4].

➢ Low reputation based systems have low probability of sale as compared to the products with high reputation.

➢ This system provides encouragement to make an entry into the auction system for new bidders [4].

➢ Products with high reputation could earn more profit for the seller.

➢ This system relies on indirect repository [16].

➢ Feedback of others can also be rated which lets others to know how much useful this information is [17].

➢ Sellers with less reputation are discouraged.

9 Disadvantages of Policy Based System

➢ How long a seller is going to stay in the market the client doesn’t know [4].

➢ A single person can have multiple identities and rate the products by fake identities to increase its rating.[18].

➢ A person is limited to rate only the selected one, where a same service is being offered across multiple channels [18].

➢ Sellers or buyers who have left the market due to bad reputation could make a re-entry into the system by making a new identity [18].

➢ Unauthentic ratings of the products could be provided that is actually not the original view of the one rating it [18].

➢ There is no insurance to the honest sellers in the market i.e. their products can be rated negatively by other buyers [19].

Conclusion

In this paper, two methods of implementing trust in semantic web have been discussed. Both of these systems have been developed according to the need and circumstances of the situation. One method is Policy based system which is more of a strong and secure system and is under use in critical environments where as the other system that is Reputation based system which works by taking feedback from the parties. Advantages and disadvantages of both the system have also been discussed. We have seen both systems have their own pros and cons. If both the systems are integrated than both systems can help each others’ weaknesses and trust will be implemented more successfully in semantic web and more goals will be achieved.

Future Work

Future work in trust is going to be the integration of both of the methods described in the paper. Or finding a more efficient way of implementing trust to achieve the goals of semantic web. These two techniques have worked independently in different environments. But still research is needed in areas like Trust negotiation success, optimal negotiations, and what will happen in case of environments where multiple strategies will be implemented.

Acknowledgement

At this moment I want to express my sincere gratitude and appreciation for my Adviser Mr. Zubair Ahmed for his constant support and encouragement which has made this research report successful. I would also like to thank my family and friends for their encouragement.

References

1] B. Piero, D. Claudiu, O. Daniel and S. Nahid. “An Integration of Reputation based and Policy-based Trust Management.” presented in Conf. Semantic Web Policy Workshop in conjunction with 4th International Semantic Web Conference, Galway, Ireland, November 2005.
2] N. Wolfgang, O. Daniel, W. Marianne and C. Zhang. “Ontology-Based Policy Specification and Management,” presented at the 2nd Eu. Conf. The Semantic Web: Research and Applications.
3] S. Ali. “An integrated approach for trust management in Semantic Web,” Presented at the 2nd Int. Conf. Computer, Control and Communication, Karachi, Pakistan, 2009.
4] R. Paul, Z. Richard, S. John and L. Kate. “The Value of Reputation on eBay: A Controlled Experiment,” ESA, Boston, MA, 2002.
5] C. Dellarocas. (2005, June). Reputation Mechanisms.
6] Kieron O’Hara, Harith Alani, Yannis Kalfoglou, and Nigel Shadbolt “Trust strategies for the semantic web”
7] Piero Bonatti, Claudiu Duma, Daniel Olmedilla, and Nahid Shahmehri Universita di Napoli Federico II, Napoli, Italy “An integration of reputation-based and policy-based trust management”
8] Haiping Xu, Sol M. Shatz, and Christopher K. Batesv.University of Massachusetts Dartmouth, North Dartmouth. “A Framework for Agent-Based Trust Management in Online Auctions”
9] B. Christoph, D. John, F. Dieter and S Rudi “No Registration Needed: How to Use Declarative Policies and Negotiation to Access Sensitive Resources on the Semantic Web,”. Crete, Greece, 2004
10] Christian Bizer Freie Universität Berlin and Radoslaw Oldakowski Freie Universität Berlin. “Using context- and content-based trust policies on the semantic web”.
11] Wolfgang Nejdl, Daniel Olmedilla, , Marianne Winslett, and Charles C. Zhang. L3S Research Center and University of Hannover, Germany.” Ontology-Based Policy Specification and Management”
12] Haiping Xu, Sol M. Shatz, and Christopher K. Batesv.University of Massachusetts Dartmouth, North Dartmouth. “A Framework for Agent- Based Trust Management in Online Auctions”.
13] B. Christian, O. Radoslaw. “Using Context- and Content-Based Trust Policies on the Semantic Web,”
14] C. A. Shoniregun, O. Adebola, B. Diepriye and L. Oleksandr. “Can eCRM and Trust Improve eC Customer Base?,”.
15] P.A. Bonatti1, C. Duma, N. Fuchs, W. Nejdl and N. Shahmehri. “Semantic Web Policies - A Discussion of Requirements and Research Issues,”.
16] G. E. Bolton, K. Elena and O. Axel. “How Effective Are Electronic Reputation Mechanisms? An Experimental Investigation,”.
17] Z. Ming, D. Martin,J. W. Robert(2008, Mar.). “Online reputation systems: Design and strategic practices.” Decision Support Systems.
18] Audun and G. Jennifer. “Challenges for Robust Trust and Reputation Presented in Conf. Security and Trust Management. (2009).
19] A. Harith, K. Yannis and S. Nigel. “Trust Strategies for the Semantic Web,” presented in Proc. International workshop on Trust, Security and Reputation ISWC04, 2004, pp. 87-85.
20] Introduction to The Semantic Web(http://infomesh.net/2001/swintro/)
21] Katharina Reinecke “Cultural adaptivity for the Semantic Web ”.
22] Liangjun You “An Adaptive Reputation-Based Trust Model For Intelligent Agents in E MarketPlace”
23] W3C

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