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Online Social Network (OSN) is a platform where users are able to share information among them easily and instantly. The sensitive information of an user can be misused by his/her friends or friends of friends due to the lack of reliable Friend Request Acceptance (FRA), which is one of the key issues in OSNs. The existing FRA techniques are functioning based on either blind (i.e., without knowing information of a user, who sends the friend request to become a new friend, referred to as friend-to-be) or manual search method. Although in the second method, the OSN user accepts a new friend based on his/her profile, however, it is not guaranteed that the profile is not fake. A approach is to bring down the misused information by filtering FRA using a reliable method to find out more information about the friend-to-be. This paper has proposed such a method for Reliable Decision Making (RDM) of accepting friend request on OSNs in order to identify the attributes of a friend-to-be. RDM is a function with several parameters such as security, flexibility, effectiveness and satisfaction. To prove the reliability of the proposed method, an extensive quantitative study was carried out, which results indicated user�s preferences for proposed method compared to the existing FRA methods.
A user can adjust his/her preference for accepting friend by exploiting Friend Request Setting (FRS). FRS offers two types of feature such as "Everyone" and "Friends of Friend". The former one indicates that every user on a particular OSN platform can become a user�s friend. On the contrary, the later one indicates that only the friends of a user�s friends can become his/her friend. It limits friend requests to the users who are not interested to make random friends. It also can assist a user to keep information private and secure compared to the former one.
A user can be connected with his/her old/new friends utiliz- ing this feature. It can help to generate a list of people and their profiles according to the user�s provided information such as name, hometown, college or university, e-mail etc. The user can also use this list if he/she can�t remember some- one�s name. By this feature, a user has the higher possibility to search accurately, as the people rarely have same attributes in their personal details
If person X wants to become a friend with another person Y, Xhastosendarequestexploitingthisfeature.Afterreceiving the request, Y can accept the friend request by analysing Y�s profile that basically includes profile picture, name, and mutual friends and so on. Y can reject the X if he/she is not interested. Y can investigate more information of X by connecting through X�s time-line.
ONLINE Social Networks (OSN) is a medium where people are allowed to share personal backgrounds, in- terests, activities, and connections with OSNs users . The evolution of Internet technologies led to significant growth of the OSNs, e.g., Facebook, Twitter, LinkedIn, Google+ and so on. Among them Facebook is the largest online social network in the world which has over 1.86 billion active users. OSN allows registered users to create profiles, send messages, update status, upload photos and videos to connect with family members, friends and business associates. In a process of making a friend, OSNs users give an access to their personal informationto other people, from old friendsto strangers.
The sociable and communal atmosphere of OSNs is very striking to users and it makes easy for the users to unveil information about themselves and their contacts with other users . Moreover, it is dangerous to share sensitive information in online , e.g., time-related information , personal characteristics and activities, and user�s habits. Such sensitive information is targeted by attackers who are involved in malpractice for unwanted purposes such as robbery, kidnapping, stalking, etc. For instance, in March 2013, a teenage girl was murdered while stay at home alone in Tulsa, USA [8]. A few hours before of her death, she tweeted, "Have the house to myself everybody gone" [8]. Therefore, the posted information in online may cause the user in danger.
this paper designed a reliable method for decision making of accepting friend request on online social networks through an automated filtering approach. More in details, we design an algorithm for estimating matching fac- tor based on the attributes of friend-to-be and his/her friends.
Subsequently, we define the RDM as a function (R l ) with several parameters such as security, flexibility, effectiveness and satisfaction. Finally, in order to prove the reliability of the proposed FRA method, this study has followed a survey as a quantitative approach and the findings reflect that the users prefer to use the proposed method compared to the existing FRA methods.
WSharing information with unknown OSN user is a risk which leads being a target by the attackers. In order to address this issue, we studied the existing FRA methods and identified their limitations. Based on those, we proposed a reliable method for decision making of accepting friend request on OSNs. More in detail, we designed an automated filtering
algorithm that estimated a matching factor, which utilized for making reliable decision on accepting a friend request. It is evident from the findings that the proposed method is more reliable compared to the existing FRA methods, which validated the hypothesis of this study.