Trust Social web Reputation

Archives of Business Research

As social networking sites (SNSs) have risen in popularity, attackers have been using social engineering traps and tactics to trick SNS users into obeying them, accepting threats, and falling victim to various crimes and attacks, such as phishing, sexual abuse, financial abuse, identity theft, impersonation, physical crime, and many other forms. Recent research on SNS security shows that most of the attackers rely mainly on fake identities. However, one of the key challenges that has faced researchers recently is how to distinguish between legitimate users and attackers. In this paper, we propose a simple yet effective method of evaluating the trustworthiness of an SNS user. The proposed method relies on a user's reputation, which can be evaluated from the user's friendship history. As such, this method contributes to reducing the risks associated with the lack of identity authentication in SNSs, as well as the failure to filter fake profiles when receiving friendship invitations, looking for people on search engines, and dealing with spam messages.

2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications, 2012

Improving trust in social networks appears as the first step toward addressing the existing confidence and privacy concerns related to online social networks. Direct trust is used to develop different trust-based methods such as transitivity and access control, however how to compute direct trust levels is rarely discussed in the literature. To address some of the current limitations, we introduce a novel approach for generating trusted social networks and we compute trust levels between users having direct relationships. Experimental results with data extracted from FOAF files show that our work presents high accuracy.

Online Social Network (OSN) has become the most popular platform on the Internet that can provide an interesting and creative ways to communicate, sharing and meets with peoples. As OSNs mature, issues regarding proper use of OSNs are also growing. In this research, the challenges of online social networks have been investigated. The current issues in some of the Social Network Sites are being studied and compared. Cyber criminals, malware attacks, physical threat, security and usability and some privacy issues have been recognized as the challenges of the current social networking sites. Trust concerns have been raised and the trustworthiness of social networking sites has been questioned. Currently, the trust in social networks is using the single- faceted approach, which is not well personalized, and doesn’t account for the subjective views of trust, according to each user, but only the general trust believes of a group of population. The trust level towards a person cannot be calculated and trust is lack of personalization. From our initial survey, we had found that most people can share their information without any doubts on OSN but they normally do not trust all their friends equally and think there is a need of trust management. We had found mixed opinions in relation to the proposed rating feature in OSNs too. By adopting the idea of multi-faceted trust model, a user-centric model that can personalize the comments/photos in social network with user’s customized traits of trust is proposed. This model can probably solve many of the trust issues towards the social networking sites with personalized trust features, in order to keep the postings on social sites confidential and integrity.

Research Square (Research Square), 2024

The ubiquity of mobile phones and web technology has facilitated continuous communication within Online Social Networks (OSNs) such as Twitter, Instagram, Facebook, and LinkedIn. In OSNs, individuals have the capability to share posts and photos with their relatives and friends, as well as to promote and publicize their businesses. However, this also opens up the potential for malicious users to misuse personal information. Consequently, researchers have turned their attention toward proposing trust-related methods aimed at ensuring a secure environment within social networks. Trust management involves the observation and rating of each user based on his activities, ensuring that only trustworthy users are granted permission to share their activities. In this paper "User Activities Based Trust Management Framework for Online Social Networks-TMFOSN" is proposed. Where users trust values are managed and keep getting updated through the different phases like trust computation, aggregation, propagation, and updations. In TMFOSN, user direct and indirect trust is evaluated with reference of Twitter social network dataset. The performance of TMFOSN is compared with other trust estimation methods, where it is outperformed with increased number of user profiles.

International Journal of Cyber Warfare and Terrorism, 2013

The use of social network sites has exploded with its multitude of functions which include posting pictures, interests, activities and establishing contacts. However, users may be unaware of the lurking dangers of threats originating from Social Networking Sites (SNS) which include malware or fake profiles. This paper investigates the indicators to arouse suspicion that a social networking account is invalid with a specific focus on Facebook as an illustrative example. The results from a survey on users’ opinions on social networks, is presented in the paper. This helps reveal some of the trust indicators that leads users to ascertaining whether a social networking profile is valid or not. Finally, indicators of potentially deceptive agents and profiles are given as a guideline to help users decide whether they should proceed with interaction with certain contacts.

Indonesian Journal of Electrical Engineering and Computer Science, 2025

Online social network is a good platform, where users can share their opinions, ideas, products, and reviews with known (friends and relatives) and unknown users. The growing fame and its easy accesses of new users sometimes lead to security and privacy issues. Many methods are reported so far to address these issues but usage of high complex cryptographic algorithms creating new set of performance related challenges to the mobile users. In this paper, light weight soft security (trust) method is proposed. The proposed method "Trust evaluation in online social networks for secured user interactions-TEOSN" uses user social activities in estimation of his trustworthiness. Each user is observed in terms of followed factor-𝑓 𝑑 (his interactions with others) and follower factor-𝑓 𝑟 (others interaction with him). The factors 𝑓 𝑑 and 𝑓 𝑟 are estimated using fuzzy logic and user trust-𝜏 is estimated using beta distribution. The performance of TEOSN is verified theoretically and practically. In experimental results, TEOSN is verified against different number of users; especially it outperformed existing methods in trust computation of target users at 2 to 4-hop distances.

2015

Online Social Network (OSN) has become the most popular platform on the Internet that can provide an interesting and creative ways to communicate, sharing and meets with peoples. As OSNs mature, issues regarding proper use of OSNs are also growing. In this research, the challenges of online social networks have been investigated. The current issues in some of the Social Network Sites are being studied and compared. Cyber criminals, malware attacks, physical threat, security and usability and some privacy issues have been recognized as the challenges of the current social networking sites. Trust oncerns have been raised and the trustworthiness of social networking sites has been questioned. Currently, the trust in social networks is using the single- faceted approach, which is not well personalized, and doesn’t account for the subjective views of trust, According to each user, but only the general trust believes of a group of population. The trust level towards a person cannot be calculated and trust is lack of personalization. From our initial survey, we had found that most people can share their information without any doubts on OSN but they normally do not trust all their friends equally and think there is a need of trust management. We had found mixed opinions in relation to the proposed rating feature in OSNs too. By adopting the idea of multi-faceted trust model, a user-centric model that can personalize the comments/photos in social network with user’s customized traits of trust is proposed. This model can probably solve many of the trust issues towards the social networking sites with personalized trust features, in order to keep the postings on social sites confidential and integrity.

Zenodo (CERN European Organization for Nuclear Research), 2021

Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART's integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.

Computer Networks, 2012

Trust and Reputation Systems constitute an essential part of many social networks due to the great expansion of these on-line communities in the past few years. As a consequence of this growth, some users try to disturb the normal atmosphere of these communities, or even to take advantage of them in order to obtain some kind of benefits. Therefore, the concept of trust is a key point in the performance of on-line systems such as on-line marketplaces, review aggregators, social news sites, and forums. In this work we propose a method to compute a ranking of the users in a social network, regarding their trustworthiness. The aim of our method is to prevent malicious users from illicitly gaining high reputation in the network by demoting them in the ranking of users. We propose a novel system intended to propagate both positive and negative opinions of the users through a network, in such way that the opinions from each user about others influence their global trust score. Our proposal has been evaluated in different challenging situations. The experiments include the generation of random graphs, the use of a real-world dataset extracted from a social news site, and a combination of both a real dataset and generation techniques, in order to test our proposals in different environments. The results show that our method performs well in every situations, showing the propagation of trust and distrust to be a reliable mechanism in a Trust and Reputation System.

BIS 2008 Workshops …, 2008