1,347 research outputs found
Facebook: How Likes and Followers Affect Users Perception and Leadership
The online social network, Facebook, creates a problem in which likes , and followers give a user the appearance of leadership. The accumulation of likes in the online social network environment, such as Facebook, might offer non-legitimate leader status, similar to campaign donations contributing to the appeal of a political candidate. This appearance of Facebook popularity through likes possibly skews the other members\u27 perspective regarding a user\u27s leadership competence. The user often looks official, popular, and influential through the advent of likes and followers. Any opinions of a user with accumulated likes could be taken with greater weight than a user with significantly fewer likes and followers. The objective of this study finds if the accumulation of likes and followers on Facebook leads to perceived user leadership status. The data includes a Facebook user questionnaire survey and subsequent data analysis. This qualitative study may provide a useful expansion of our traditional definition of leadership. The expansion could enhance academic and leadership studies courses with a greater understanding of online social capital
ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic
It is well known that apps running on mobile devices extensively track and
leak users' personally identifiable information (PII); however, these users
have little visibility into PII leaked through the network traffic generated by
their devices, and have poor control over how, when and where that traffic is
sent and handled by third parties. In this paper, we present the design,
implementation, and evaluation of ReCon: a cross-platform system that reveals
PII leaks and gives users control over them without requiring any special
privileges or custom OSes. ReCon leverages machine learning to reveal potential
PII leaks by inspecting network traffic, and provides a visualization tool to
empower users with the ability to control these leaks via blocking or
substitution of PII. We evaluate ReCon's effectiveness with measurements from
controlled experiments using leaks from the 100 most popular iOS, Android, and
Windows Phone apps, and via an IRB-approved user study with 92 participants. We
show that ReCon is accurate, efficient, and identifies a wider range of PII
than previous approaches.Comment: Please use MobiSys version when referencing this work:
http://dl.acm.org/citation.cfm?id=2906392. 18 pages, recon.meddle.mob
A Credential Store for Multi-tenant Science Gateways
Science Gateways bridge multiple computational grids and clouds, acting as overlay cyberinfrastructure. Gateways have three logical tiers: a user interfacing tier, a resource tier and a bridging middleware tier. Different groups may operate these tiers. This introduces three security challenges. First, the gateway middleware must manage multiple types of credentials associated with different resource providers. Second, the separation of the user interface and middleware layers means that security credentials must be securely delegated from the user interface to the middleware. Third, the same middleware may serve multiple gateways, so the middleware must correctly isolate user credentials associated with different gateways. We examine each of these three scenarios, concentrating on the requirements and implementation of the middleware layer. We propose and investigate the use of a Credential Store to solve the three security challenges
Report of the 2014 NSF Cybersecurity Summit for Large Facilities and Cyberinfrastructure
This event was supported in part by the National Science Foundation under Grant Number 1234408. Any opinions, findings, and conclusions or recommendations expressed at the event or in this report are those of the authors and do not necessarily reflect the views of the National Science Foundation
2015 XSEDE Federation Risk Assessment Overview
The methodology and working documentation for performing the 2012 and 2015 XSEDE Security Risk Assessments.NSF #1053575Ope
Security attacks taxonomy on bring your own devices (BYOD) model
Mobile devices, specifically smartphones, have become ubiquitous. For this reason, businesses are starting to develop “Bring Your Own Device” policies to allow their employees to use their owned devices in the workplace. BYOD offers many potential advantages: enhanced productivity, increased revenues, reduced mobile costs and IT efficiencies. However, due to emerging attacks and limitations on device resources, it is difficult to trust these devices with access to critical proprietary information. Therefore, in this paper, the potential attacks of BYOD and taxonomy of BYOD attacks are presented. Advanced persistent threat (APT) and malware attack are discussed in depth in this paper. Next, the proposed solution to mitigate the attacks of BYOD is discussed. Lastly, the evaluations of the proposed solutions based on the X. 800 security architecture are presented
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