Rethinking Privacy and Security Mechanisms in Online Social Networks

With billions of users, Online Social Networks(OSNs) are amongst the largest scale communication applications on the Internet. OSNs enable users to easily access news from local and worldwide, as well as share information publicly and interact with friends. On the negative side, OSNs are also abused by spammers to distribute ads or malicious information, such as scams, fraud, and even manipulate public political opinions. Having achieved significant commercial success with large amount of user information, OSNs do treat the security and privacy of their users seriously and provide several mechanisms to reinforce their account security and information privacy. However, the efficacy of those measures is either not thoroughly validated or in need to be improved. In sight of cyber criminals and potential privacy threats on OSNs, we focus on the evaluations and improvements of OSN user privacy configurations, account security protection mechanisms, and trending topic security in this dissertation. We first examine the effectiveness of OSN privacy settings on protecting user privacy. Given each privacy configuration, we propose a corresponding scheme to reveal the target user\u27s basic profile and connection information starting from some leaked connections on the user\u27s homepage. Based on the dataset we collected on Facebook, we calculate the privacy exposure in each privacy setting type and measure the accuracy of our privacy inference schemes with different amount of public information. The evaluation results show that (1) a user\u27s private basic profile can be inferred with high accuracy and (2) connections can be revealed in a significant portion based on even a small number of directly leaked connections. Secondly, we propose a behavioral-profile-based method to detect OSN user account compromisation in a timely manner. Specifically, we propose eight behavioral features to portray a user\u27s social behavior. A user\u27s statistical distributions of those feature values comprise its behavioral profile. Based on the sample data we collected from Facebook, we observe that each user\u27s activities are highly likely to conform to its behavioral profile while two different user\u27s profile tend to diverge from each other, which can be employed for compromisation detection. The evaluation result shows that the more complete and accurate a user\u27s behavioral profile can be built the more accurately compromisation can be detected. Finally, we investigate the manipulation of OSN trending topics. Based on the dataset we collected from Twitter, we manifest the manipulation of trending and a suspect spamming infrastructure. We then measure how accurately the five factors (popularity, coverage, transmission, potential coverage, and reputation) can predict trending using an SVM classifier. We further study the interaction patterns between authenticated accounts and malicious accounts in trending. at last we demonstrate the threats of compromised accounts and sybil accounts to trending through simulation and discuss countermeasures against trending manipulation

Fast simulation of the CEPC detector with Delphes

Fast simulation tools are highly appreciated in particle physics phenomenology studies, especially in the exploration of the physics potential of future experimental facilities. The Circular Electron Positron Collider is a proposed Higgs and Z factory that can precisely measure the Higgs boson properties and the electroweak precision observables. A fast-simulation toolkit dedicated to the CEPC detector has been developed using Delphes. The comparison shows that this fast simulation tool is highly consistent with the full simulation, on a set of benchmark distributions. Therefore, we recommend this fast simulation toolkit for CEPC phenomenological investigations

What Scale of Audience a Campaign can Reach in What Price on Twitter?

Abstract—Campaigns with commercial and spam purposes have flooded the Twitter community. To understand what scale of audience a campaign could reach, we first perform a measurement study by collecting a dataset of about 10 million tweets via streaming API and one million search tweets for targeting topics, as well as 37,313 user accounts that are suspended by Twitter. From the dataset, we extract a spam campaign and a commercial promotion campaign accompanied by spamming activities. Then, we characterize the way in which a campaign can reach its audience, especially revealing the features that dominate the information diffusion. After identifying the accounts suspended by Twitter, we further inspect to what extent these features can help to weed out spam accounts. Also, the retrospective inspection is useful to uncover the tactics that malicious accounts utilize to avoid being suspended. Using the measurement results, we then develop a theoretical framework based on an epidemic model to investigate the dynamics of spammers and victims whom spammers reach in the spam campaign. With the theoretical framework, we conduct a benefit-cost analysis of the spam campaign, shedding lights on how to restrict the benefit of the spam campaign. I

Spatial performance of skewed continuous rigid-frame bridges based on finite element analysis

Continuous rigid-frame bridges are usually symmetrically designed along the bridge center line for simplicity and clarity purposes. However, the skewed bridges are necessary in case of complex intersections with space constraint in highways. Previous research mainly focuses on the discussion of skewed angle and the interaction between girders and cross frames on I shape section. Box sections are also used for skewed bridge due to large torsion stiffness, which have many problems during service time. This paper analyzed coupled skew and bending effect for the bridge which combines the continuous rigid-frame system and skewed system. For skewed bridges, significant out-of-lane effect occurs in bridges, which is hard to be predicted through linear analysis. For continuous bridges, at the interior supports, negative bending moments exist. In addition, a part of each diaphragm of the bridge is connected to the main girder, and the rest part only carries its self-weight, which makes the girder behavior more complex in the transverse direction. Therefore, the spatial performance of the bridge is very complex. The design cannot only use simple two dimension analysis. In the paper the three dimensional finite element analysis was conducted to find the effect due to dead load, live load, temperature, and brake force to find critical position for monitoring and maintainance. Primary bending normal stress, warping normal stress, coefficient of shearing force lag and stress distribution of consolidation pier were analyzed and output. The behavior of both superstructure and sub structure were investigated. The effect of coupled bending and torsion is significant to the behavior of the bridge. Finally the design recommendations about the skew bridge are given. The critical positions for the further test and monitoring are found