Research topic online dating

Can we use trust in online dating

Can We Use Trust in Online Dating?,Can We Use Trust in Online Dating?

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The Future of Social Networks on the Internet: The Need for Semantics by John G Breslin. Recommending people to people: the nature of reciprocal recommenders with a case study in online dating by Judy Kay.

A Study of Edwards Curves in Relation to Elliptic Curve Cryptography by Adarsh Saraf. The physics of forgetting: Landauer's erasure principle and information theory by Martin Plenio. Atomic Cross-chain Swaps: Development, Trajectory and Potential of Non-monetary Digital Token Swap Facilities by Annals of Emerging Technologies in Computing AETiC and Mahdi H.

Download Download PDF. Download Full PDF Package. Translate PDF. James Stanier, Stephen Naicken, Anirban Basu, Jian Li, and Ian Wakeman School of Informatics, University of Sussex, Falmer, East Sussex, UK, BN1 9QJ.

stanier, stephenn, a. basu, jl58, ianw} sussex. We show that the application of trust models to socially emo- tive applications such as online dating, while beneficial, is difficult due to the complexities of the interpersonal relationships that exist. These are discussed with respect to our initial attempt to design a transitive trust model for social network dating services and existing trust taxonomies.

We hope that the issues discussed motivate researchers to consider more complex social relationships in the design of trust models. While this property is complex and dependent on emotional factors that are difficult to formalise, formalisms of trust have been proposed that allow trust to be used in computing applications [1].

Trust formalisms and the increased threats that exist against systems and their users have given rise to a plethora of trust management systems for a variety of application areas, e. peer-to-peer P2P and marketplaces. Many are designed for interpersonal relationships, but are unsuitable for use in scenarios where these are complex, emotional, and at times, irrational. To highlight this, in this work, online dating is considered. These services lack trust systems, but there are a number of reasons why this should not be the case.

Dating sites are increasing in popularity and market value, with the U. Typically as services grow in popularity and value, they are increasingly targeted by attackers. There are also user-related issues to be considered. Dating services implement a matchmaking process that attempts to recommend potential partners based on their profiles, preferences and location. Yet two well matched users are still strangers and this can make initial contact difficult as little is known other than information in their profiles.

Hancock et al. An attacker could use many false profiles to perform a Sybil attack [3] to target a given user or type of user, resulting in well-behaved users perceiving these profiles as genuine and trustworthy. This allows the attacker to engage in malicious behaviour against users, and more damagingly, to build trust with them only to breach this later. These issues show that trust models are required in online dating applica- tions.

The aim of this work was to implement a trust model for use in dating services that made use of the transitive trust in social networks. The motivation for this was that it is common in real life to meet potential partners through a degree of separation from an existing friend. This has a number of benefits. Firstly, the two parties are introduced by a mutually trusted friend which re- duces embarrassment and increases legitimacy. Secondly, by being introduced, it is likely that the two parties share some common interests with the friend and in turn each other.

Lastly, compared to existing dating services, the use of a social network provides a better foundation for matchmaking as it models real life social interaction. However, it soon became evident that dating gives rise to issues that have not been addressed by prior trust models. In this paper, we broadly look at existing trust models, their applications and taxonomy. This is followed by the initial design of a facilitated approach to dating that assumes the presence of a dating service that overlays an existing social network.

The approach makes use of the friend-of-a-friend FOAF concept in the social graph to match users. Finally, it is shown why this does not work, and a discussion of the issues in modelling trust in such applications is given. Their aim is to improve reliability and performance of systems by modelling the trustworthiness of agents. At its simplest, trust is a function of behaviour, with behavioural history allowing the trustworthiness of an agent to be determined.

Good behaviour increases trust and bad decreases it. Once the trustworthiness of an agent has been ascertained, others may decide if they wish to interact with it. A taxonomy of trust has been presented [6] which identifies the components of P2P reputation systems and their mechanisms. These are: a Information gathering: Identity scheme, information sources, information aggregation and stranger policy. b Scoring and ranking: Good vs. bad behaviour, quantity vs. quality, time-dependence, selection threshold and peer selection.

c Response: Incentives and punishment. This taxonomy is applicable to trust in other applications. For example, in an online shopping scenario, information gathering criteria are easily accessible, as each seller is publicly visible for a buyer to interact with. The response criteria are also apparent: succeeding in being a trustworthy seller brings more customers and profit as a result, whereas repeated punishment will drive customers away.

However, there are applications where trust models would be invaluable, but are difficult to implement. Analysing these applications with respect to the taxonomy raises a number of issues. In the rest of this paper, online dating is shown to be one such application. If a user is interested in another, the intermediate friends between them may act as a path of facilitators that decide if the two are a suitable match. Assuming that the user, Alice, wants to date Bob, a number of different routes may exist in the social network between them.

The algorithms attempt to rank these simple path routes on on the pair-wise trust between users on the path and facilitation rankings. This helps Alice choose the best path to contact Bob without knowing any explicit detail about the intermediate friends. The rank function is of the degrees of separation between the two parties, the path trust and facilitation value.

While we make no assumption as to how this trust value is derived, one proposal is to build upon the work of Gill [7, 8], which shows that trust, personality and emotion can be perceived from short texts, e.

status updates and wall posts. Facilitator ranking: The trust values capture pairwise trust between individuals but do not measure their ability to act as facilitators in a matchmaking process.

The aim was to harness the transitive trust relationships that exist in the social network to facilitate matchmaking. The first process to achieve this is to propose a set of k-most trusted paths from Alice to Bob. Alice, presented with these k- paths, chooses one to be used in the matchmaking process. The problem of finding the most trusted path has been addressed in P2P networks [9].

However, given the additional facilitation variable, we choose a more sophisticated approach by modifying the semiring-based trust model presented by Theodorakopoulos and Baras [10] so that the chosen k-most trusted paths are defined by a function over the pairwise trust values and the facilitation value of each intermediate vertex on the path.

Due to space constraints we omit the mathematical preliminaries and details of this, opting instead to only present the facilitation model.

We observe that Bob could be at: 1. one degree of separation, i. Here we assume Alice requires a facilitator, perhaps due to shyness as friendship already exists with Bob, so this becomes two degrees of separation, see 2.

two degrees of separation, i. three degrees of separation, i. There is no single facilitator but p1 and p2 together who are friends act as facilitators. more than three degrees of separation, i. A path reduction algorithm through chain introductions can reduce the degree of separation to three, e.

To achieve this p1 asks p2 for an introduction to p3. Any intermediate person pk has very little reason to co-operate other than altruism, although incentives may help to increase cooperation. Therefore, we do not consider paths longer than three degrees. Facilitation: This process depends on the degrees of separation between Alice and Bob.

We enumerate the process in algorithm 3. Algorithm 3. Given a match, p1 initiates the revelation process in algorithm 3. Given a match, p1 and p2 initiate the revelation process described in algorithm 3. In algorithm 3. Revelation: In order to protect identity, the revealing process, described in al- gorithm 3. These issues are primarily due to the complexities of relationships and are unaddressed by existing models and difficult to resolve.

Information gathering: Collecting the required information for trust systems poses a number of difficulties. Identities must be associated with historical be- haviour, so they must be sufficiently persistent, spoof-resistant, unforgeable and where necessary, offer a degree of anonymity. He is given the ranking along with the recommendations that have been produced by immediate facilitator, p2 or by the single facilitator p1 depending on the degree of separation between Alice and Bob.

If Bob does not wish to continue, he can cancel the matchmaking attempt with a written decision which is fed back to Alice. He is not given her name at this point. From this point, they could add each other as friends on the social network unless they already are friends and message each other directly.

Based on how the two parties get on, they are encouraged to rate how accurate the recommendation process was. This feeds into the facilitator ranking to use in future path computation. as there is no need to hide the association between behaviour and identity, the others give rise to concerns. Persistence and spoof-resistance can be ensured when a centralised server is used for managing identity, as is the case for all existing dating services.

For the model presented in this work, this is also assumed to be true as existing social network services use centralised identity management. Unforgable identities are somewhat harder to ensure. As mentioned above, free dating services are sus- ceptible to Sybil attacks [3], but those using a subscription business model lower their vulnerability as identity has a cost.

Credit-card verification is an alternative way to prevent this and also ensure that minors can not use the system. Even where persistence can be guaranteed, there will be churn in the user base of dating services. Users leave the service after finding a partner or because of negative experiences. Their feedback is important to those remaining in the system, but must decay in importance with time. By implementing the dating service as an application of an existing social network, users remain in the system even after having found a match as they continue to engage in other activities and can participate in facilitation.

Misleading identities must also be considered. Alice may lie in her profile so that her chosen target user is more receptive to her request for a date. While the facilitation model attempts to handle this by having the facilitators verify profile information, Alice and her next-hop friend may collude to defeat this. Obtaining information to be used by a trust model is generally not an issue, as the data is available from users or the application. In P2P file sharing, users provide feedback on the quality of file download transactions.

Models such as Eigentrust [11] provide no incentive for this, with users assumed to be altruistic with feedback. Assuming such altruistic feedback behaviour in dating applications is naive. So why do people do it? And more important, if so many online-dating users assume people are garnishing their profiles in some way, why do they continue to look for relationships on these sites? For some, lying may also seem like the only option for finding dates. Klimentova says her bad date harassed her online for weeks.

MORE: More Satisfaction, Less Divorce for People Who Meet Spouses Online. Understanding why people still find digital dating appealing, despite its shortcomings, is a little more complicated. For one, having more options may be a benefit when it comes to finding a match. Some studies have found that the plethora of candidates online skews relationships toward the shallow side, since people have an instinctive tendency to shop around and not invest time or effort into each choice when there are so many to consider.

edu no longer supports Internet Explorer. To browse Academia. edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser. Sushil Jajodia. The computational load imposed by encryption makes such approaches not suitable for scenarios with lightweight clients.

Rafael Bonilla. Thomas Pasquier. From the start, strong isolation between cloud tenants was seen to be of paramount importance, provided first by virtual machines VM and later by containers, which share the operating system OS kernel. Increasingly it is the case that applications also require facilities to effect isolation and protection of data managed by those applications.

They also require flexible data sharing with other applications, often across the traditional cloud-isolation boundaries; for example, when government provides many related services for its citizens on a common platform. Similar considerations apply to the end-users of applications. These concerns relate to the management of data. Information Flow Control IFC , in addition, offers system-wide, end-to-end, flow control based on the properties of the data.

In addition, the audit log associated with IFC provides transparency, giving configurable system-wide visibility over data flows.

This helps those responsible to meet their data management obligations, providing evidence of compliance, and aids in the ident- fication of policy errors and misconfigurations. We present our IFC model and describe and evaluate our IFC architecture and implementation CamFlow. This comprises an OS level implementation of IFC with support for application management, together with an IFC-enabled middleware. Our contribution is to demonstrate the feasibility of incorporating IFC into cloud services: we show how the incorporation of IFC into cloud-provided OSs underlying PaaS and SaaS would address application sharing and protection requirements, and more generally, greatly enhance the trustworthiness of cloud services at all levels, at little overhead, and transparently to tenants.

Panayiotis Kotzanikolaou. John G Breslin. Judy Kay. Adarsh Saraf. Elliptic curves were introduced to the ancient science of cryptography in the mid s, and Elliptic Curve Cryptography ECC has since been growing rapidly. However, owing to the incompleteness of the Weierstrass addition law, elliptic curve cryptosystems based on the Weierstrass model are vulnerable to side-channel attacks. New addition algorithms and elliptic curve models have been proposed to take elliptic curve cryptosystems resistant to side-channel attacks.

A promising model in this regard is the Edwards model introduced in The Edwards addition law is both complete and has the fastest known implementations for elliptic curve operations like addition and doubling. As a part of this work we study the Edwards model in relation to ECC with an emphasis on its computational aspects. We also study two encoding schemes, Elligator and Elligator Square, for representing elliptic curve points as bit strings indistinguishable from uniform random bit strings, both of which have formulations over Edwards curves.

We implement an hitherto unavailable library for Edwards curves, and two ECC algorithms using the implemented Edwards curves, in the mathematical software Sage. Martin Plenio. This article discusses the concept of information and its intimate relationship with physics. We employ this principle to rederive a number of results in classical and quantum information theory whose rigorous mathematical derivations are difficult.

Annals of Emerging Technologies in Computing AETiC. Annals of Emerging Technologies in Computing AETiC , Mahdi H. Since the introduction of Bitcoin in , many other cryptocurrencies have been introduced and gained popularity. Lack of interoperability and scalability amongst these cryptocurrencies was-and still is-acting as a significant impediment to the general adoption of cryptocurrencies and coloured tokens.

Atomic Swaps-a smart exchange protocol for cryptocurrencies-is designed to facilitate a wallet-to-wallet transfer enabling direct trades amongst different cryptocurrencies. Since swaps between cryptocurrencies are still relatively unknown, this article will investigate the operation and market development thus far and query the advantages they offer and the future challenges they face.

The paper contains detailed literature and technology reviews, followed by the main analysis and findings. Eugene H Spafford.

At the same time, there is a growing concern over the security of Web-based applications, which are rapidly being deployed over the Internet [4]. Jennifer Seberry. Richard Darnell. Love Bin. Bruce J MacLennan. Jens Eisert. Niroj Paudel. Rashid Khan. Ashish Bhujbal. Charles Bennett. Nadinor Zenande. Joseph Bannister. Uri Blumenthal. Adam Champion. Peter Schartner. Sanjay Kimbahune , Ratnendra Shinde. Elisa Bertino. William R Cook.

Luciano Floridi. Achille C. Suleyman Uludag. Barbara Terhal , Debbie Leung. Zahid Anwar. Lorenza Viola. Daniel Hill. John Realpe-Gomez. Minal Bhise. Sai Kanuri. Amitav Mukherjee. Kim Joris Boström. IJMER Journal. Timothy Norman. Youssef Iraqi , R. Ernesto Damiani. Kazuhiro Minami. Takeshi Koshiba.

Assane Gueye. Nicola Zannone. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Download Free PDF. Can We Use Trust in Online Dating? Anirban Basu. Related Papers. Enforcing confidentiality constraints on sensitive databases with lightweight trusted clients. Download Free PDF View PDF. A Survey of PKI Components and Scalability Issues. CamFlow: Managed data-sharing for cloud services.

Lecture Notes in Computer Science Private Proximity Testing on Steroids: An NTRU-based Protocol. IEEE Internet Computing The Future of Social Networks on the Internet: The Need for Semantics. User Modeling and User-Adapted Interaction Recommending people to people: the nature of reciprocal recommenders with a case study in online dating. A Study of Edwards Curves in Relation to Elliptic Curve Cryptography. The physics of forgetting: Landauer's erasure principle and information theory.

Annals of Emerging Technologies in Computing AETiC Atomic Cross-chain Swaps: Development, Trajectory and Potential of Non-monetary Digital Token Swap Facilities. Security models for web-based applications.

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Any intermediate person pk has very little reason to co-operate other than altruism, although incentives may help to increase cooperation. Journal of Wireless Mobile …, Information gathering: Collecting the required information for trust systems poses a number of difficulties. William R Cook. Tor : The Second Generation Onion Router by Sai Kanuri. Gill, A. Bruce J MacLennan.

Competition, Coexistence, and Confidentiality in Multiuser Multi-antenna Wireless Networks by Amitav Mukherjee. Alice, can we use trust in online dating, presented with these k- paths, chooses one to be used in the matchmaking process. Low-Cost Secure Server Connection with Limited-Privilege Clients by Uri Blumenthal. Their feedback is important to those remaining in the system, but must decay in importance with time. Similar considerations apply to the end-users of applications. In P2P file sharing, users provide feedback on the quality of file download transactions.

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