Abstract:Nowadays, more and more people are engaged in social media to generate multimedia information, i.e., creating text and photo profiles and posting multimedia messages. Such multimodal social networking activities reveal multiple user attributes such as age, gender, and personal interest. Inferring user attributes is important for user profiling, retrieval, and personalization. Existing work is devoted to inferring user attributes independently and ignores the dependency relations between attributes. In this wor… Show more
“…They proposed two different security schemes to provide confidentiality and business data collection via distributed storage. Although various authors [35] have proposed several secure decision-making and inference schemes, very few of them have focused on data alteration, message transmission, and sharing of records through legitimate devices. Further, researchers have proposed some lightweight cryptographic algorithms to further improve the security in IoV systems.…”
Decision-making is of critical significance in Internet-of-Vehicles (IoV), where vehicles need to quickly make decisions in real-time when sharing or transferring the information. In addition, it is necessary to identify the significant factors of an entity while measuring its legitimacy or to record the real-time data generated by it. Traditional automated schemes in IoV are confronted by the issues related to real-time processing and the manner they respond, such as traffic congestion information, fastest route selection, and road accidental information. The exchange of accurate information among vehicles is critical, but the decision-making for IoV has still not been fully investigated in the literature. Further, the involvement of malicious devices in the network may disgrace the network performance by consuming network resources. In this paper, we propose a hybrid decision-making scheme in vehicular informatics for data transferring and processing through VIKOR and analytic hierarchy process (AHP) methods. The proposed model is scrutinized and verified rigorously through several sensing and decision-making metrics against a conventional solution. The simulation results depict that the proposed model leads to 93 percent competence in terms of decision-making, identification of legitimate sensors, and data alteration process when sharing the information through various sensors in IoV.
“…They proposed two different security schemes to provide confidentiality and business data collection via distributed storage. Although various authors [35] have proposed several secure decision-making and inference schemes, very few of them have focused on data alteration, message transmission, and sharing of records through legitimate devices. Further, researchers have proposed some lightweight cryptographic algorithms to further improve the security in IoV systems.…”
Decision-making is of critical significance in Internet-of-Vehicles (IoV), where vehicles need to quickly make decisions in real-time when sharing or transferring the information. In addition, it is necessary to identify the significant factors of an entity while measuring its legitimacy or to record the real-time data generated by it. Traditional automated schemes in IoV are confronted by the issues related to real-time processing and the manner they respond, such as traffic congestion information, fastest route selection, and road accidental information. The exchange of accurate information among vehicles is critical, but the decision-making for IoV has still not been fully investigated in the literature. Further, the involvement of malicious devices in the network may disgrace the network performance by consuming network resources. In this paper, we propose a hybrid decision-making scheme in vehicular informatics for data transferring and processing through VIKOR and analytic hierarchy process (AHP) methods. The proposed model is scrutinized and verified rigorously through several sensing and decision-making metrics against a conventional solution. The simulation results depict that the proposed model leads to 93 percent competence in terms of decision-making, identification of legitimate sensors, and data alteration process when sharing the information through various sensors in IoV.
“…This includes work on gender (Burger, 2011), political affiliation (Conover, 2011;Pennacchiotti, 2011), location (Cheng, 2010) and ethnicity (Mislove, 2011;Chang, 2010;Pennacchiotti, 2011). Also of note is the work of Fang (2015) who focus on modelling the correlations between various demographic attributes.…”
Twitter provides an open and rich source of data for studying human behaviour at scale and is widely used in social and network sciences. However, a major criticism of Twitter data is that demographic information is largely absent. Enhancing Twitter data with user ages would advance our ability to study social network structures, information flows and the spread of contagions. Approaches toward age detection of Twitter users typically focus on specific properties of tweets, e.g., linguistic features, which are language dependent. In this paper, we devise a language-independent methodology for determining the age of Twitter users from data that is native to the Twitter ecosystem. The key idea is to use a Bayesian framework to generalise ground-truth age information from a few Twitter users to the entire network based on what/whom they follow. Our approach scales to inferring the age of 700 million Twitter accounts with high accuracy.
“…In addition, an intruder may launch a data falsification attack, also known as a false data injection attack, to perform various malicious activities (active/passive threats) inside the network [17]- [19]. Lidkea et al [20] have identified another critical threat specific to ITSs using social media, where attackers gain access to sensitive information through e-mails and other social media interactions [21]- [24] by stealing the database or records of a device or a server.…”
Conventional models in the intelligent transportation system (ITS) are confronted by large computational overheads and how they react during real-time scenarios. To appropriately manage the communication process in real-time, a trust-based mechanism can provide an efficient approach to acclimatize its deeds based on indecision sensory information. However, the computational models are not fully demoralized by the businesses owing to the lack of automated integration. In this study, we perform agent-based modeling (ABM) and population-based modeling (PBM) in the ITS mechanism during data transmission and record exchange for real-time communication. In addition, a trust evaluation process is performed to legitimize each device with the integration of ABM and PBM models. The simulation results show that the proposed mechanism is 89% more efficient than baseline methods in various networking scenarios, such as message alteration, distributed denial of service attacks, and information falsification threats.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.