5,782 research outputs found
Uncovering Download Fraud Activities in Mobile App Markets
Download fraud is a prevalent threat in mobile App markets, where fraudsters
manipulate the number of downloads of Apps via various cheating approaches.
Purchased fake downloads can mislead recommendation and search algorithms and
further lead to bad user experience in App markets. In this paper, we
investigate download fraud problem based on a company's App Market, which is
one of the most popular Android App markets. We release a honeypot App on the
App Market and purchase fake downloads from fraudster agents to track fraud
activities in the wild. Based on our interaction with the fraudsters, we
categorize download fraud activities into three types according to their
intentions: boosting front end downloads, optimizing App search ranking, and
enhancing user acquisition&retention rate. For the download fraud aimed at
optimizing App search ranking, we select, evaluate, and validate several
features in identifying fake downloads based on billions of download data. To
get a comprehensive understanding of download fraud, we further gather stances
of App marketers, fraudster agencies, and market operators on download fraud.
The followed analysis and suggestions shed light on the ways to mitigate
download fraud in App markets and other social platforms. To the best of our
knowledge, this is the first work that investigates the download fraud problem
in mobile App markets.Comment: Published as a conference paper in IEEE/ACM ASONAM 201
IoTSan: Fortifying the Safety of IoT Systems
Today's IoT systems include event-driven smart applications (apps) that
interact with sensors and actuators. A problem specific to IoT systems is that
buggy apps, unforeseen bad app interactions, or device/communication failures,
can cause unsafe and dangerous physical states. Detecting flaws that lead to
such states, requires a holistic view of installed apps, component devices,
their configurations, and more importantly, how they interact. In this paper,
we design IoTSan, a novel practical system that uses model checking as a
building block to reveal "interaction-level" flaws by identifying events that
can lead the system to unsafe states. In building IoTSan, we design novel
techniques tailored to IoT systems, to alleviate the state explosion associated
with model checking. IoTSan also automatically translates IoT apps into a
format amenable to model checking. Finally, to understand the root cause of a
detected vulnerability, we design an attribution mechanism to identify
problematic and potentially malicious apps. We evaluate IoTSan on the Samsung
SmartThings platform. From 76 manually configured systems, IoTSan detects 147
vulnerabilities. We also evaluate IoTSan with malicious SmartThings apps from a
previous effort. IoTSan detects the potential safety violations and also
effectively attributes these apps as malicious.Comment: Proc. of the 14th ACM CoNEXT, 201
Creation, Deployment, Diffusion and Export of Sub-Saharan Africa-originated Information Technology-Related Innovations
A number of high profile innovations have been created in Sub-Saharan Africa. In this paper, we examine the mechanisms associated with the development, deployment, diffusion, and export of SSA-originated innovations. The paper gives special consideration to the relative roles and contributions of local and outside resources in the creation and deployment of innovations in SSA economies. A key focus of the article is on the roles of local infrastructural facilities, systems and services in affecting the diffusion of SSA-originated innovations. Also discussed are the features of SSA-originated innovations that explain the diffusion rates. It provides a detailed analysis and description of the key characteristics of SSA-originated innovations that can increase the possibility of being internationalized or exported to other countries. Finally, we analyze how such mechanisms vary across large and small scale innovations
StoryDroid: Automated Generation of Storyboard for Android Apps
Mobile apps are now ubiquitous. Before developing a new app, the development
team usually endeavors painstaking efforts to review many existing apps with
similar purposes. The review process is crucial in the sense that it reduces
market risks and provides inspiration for app development. However, manual
exploration of hundreds of existing apps by different roles (e.g., product
manager, UI/UX designer, developer) in a development team can be ineffective.
For example, it is difficult to completely explore all the functionalities of
the app in a short period of time. Inspired by the conception of storyboard in
movie production, we propose a system, StoryDroid, to automatically generate
the storyboard for Android apps, and assist different roles to review apps
efficiently. Specifically, StoryDroid extracts the activity transition graph
and leverages static analysis techniques to render UI pages to visualize the
storyboard with the rendered pages. The mapping relations between UI pages and
the corresponding implementation code (e.g., layout code, activity code, and
method hierarchy) are also provided to users. Our comprehensive experiments
unveil that StoryDroid is effective and indeed useful to assist app
development. The outputs of StoryDroid enable several potential applications,
such as the recommendation of UI design and layout code
Designing Queer Connection: An Ethnography of Dating App Production in Urban India
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153662/1/epic1295.pd
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