25,604 research outputs found
Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos
Despite the rapid progress of the techniques for image classification, video
annotation has remained a challenging task. Automated video annotation would be
a breakthrough technology, enabling users to search within the videos.
Recently, Google introduced the Cloud Video Intelligence API for video
analysis. As per the website, the system can be used to "separate signal from
noise, by retrieving relevant information at the video, shot or per frame"
level. A demonstration website has been also launched, which allows anyone to
select a video for annotation. The API then detects the video labels (objects
within the video) as well as shot labels (description of the video events over
time). In this paper, we examine the usability of the Google's Cloud Video
Intelligence API in adversarial environments. In particular, we investigate
whether an adversary can subtly manipulate a video in such a way that the API
will return only the adversary-desired labels. For this, we select an image,
which is different from the video content, and insert it, periodically and at a
very low rate, into the video. We found that if we insert one image every two
seconds, the API is deceived into annotating the video as if it only contained
the inserted image. Note that the modification to the video is hardly
noticeable as, for instance, for a typical frame rate of 25, we insert only one
image per 50 video frames. We also found that, by inserting one image per
second, all the shot labels returned by the API are related to the inserted
image. We perform the experiments on the sample videos provided by the API
demonstration website and show that our attack is successful with different
videos and images
Diavideos: a Diabetes Health Video Portal
Diavideos1 is a web platform that collects trustworthy
diabetes health videos from YouTube and offers them in a easy
way. YouTube is a big repository of health videos, but good
content is sometimes mixed with misleading and harmful
videos such as promoting anorexia [1].Diavideos is a web
portal that provides easy access to a repository of trustworthy
diabetes videos. This poster describes Diavideos and explains
the crawling method used to retrieve these videos from trusted
channels
iTeleScope: Intelligent Video Telemetry and Classification in Real-Time using Software Defined Networking
Video continues to dominate network traffic, yet operators today have poor
visibility into the number, duration, and resolutions of the video streams
traversing their domain. Current approaches are inaccurate, expensive, or
unscalable, as they rely on statistical sampling, middle-box hardware, or
packet inspection software. We present {\em iTelescope}, the first intelligent,
inexpensive, and scalable SDN-based solution for identifying and classifying
video flows in real-time. Our solution is novel in combining dynamic flow rules
with telemetry and machine learning, and is built on commodity OpenFlow
switches and open-source software. We develop a fully functional system, train
it in the lab using multiple machine learning algorithms, and validate its
performance to show over 95\% accuracy in identifying and classifying video
streams from many providers including Youtube and Netflix. Lastly, we conduct
tests to demonstrate its scalability to tens of thousands of concurrent
streams, and deploy it live on a campus network serving several hundred real
users. Our system gives unprecedented fine-grained real-time visibility of
video streaming performance to operators of enterprise and carrier networks at
very low cost.Comment: 12 pages, 16 figure
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