# Phil 4.22.19

7:00 – 4:00 ASRC TL

• The mission of the Conference on Truth and Trust Online (TTO) is to bring together all parties working on automated approaches to augment manual efforts on improving the truthfulness and trustworthiness of online communications.
• The inaugural Truth and Trust Online conference will be taking place on October 4th and 5th 2019 at BMA House in London.
•

### Key Dates

• First call for papers: 2nd of April, 2019 *

• Deadline for all submissions: 3rd of June, 2019
• Notification of acceptance: Early July
• Registration opens: End of June
• Conference: 4th and 5th of October, 2019, BMA House, London, UK
• From On Being with Pádraig Ó Tuama, about belonging gone bad and the scale of sectarianism:
• Fooling automated surveillance cameras: adversarial patches to attack person detection
• Adversarial attacks on machine learning models have seen increasing interest in the past years. By making only subtle changes to the input of a convolutional neural network, the output of the network can be swayed to output a completely different result. The first attacks did this by changing pixel values of an input image slightly to fool a classifier to output the wrong class. Other approaches have tried to learn “patches” that can be applied to an object to fool detectors and classifiers. Some of these approaches have also shown that these attacks are feasible in the real-world, i.e. by modifying an object and filming it with a video camera. However, all of these approaches target classes that contain almost no intra-class variety (e.g. stop signs). The known structure of the object is then used to generate an adversarial patch on top of it.
• In this paper, we present an approach to generate adversarial patches to targets with lots of intra-class variety, namely persons. The goal is to generate a patch that is able successfully hide a person from a person detector. An attack that could for instance be used maliciously to circumvent surveillance systems, intruders can sneak around undetected by holding a small cardboard plate in front of their body aimed towards the surveillance camera. From our results we can see that our system is able significantly lower the accuracy of a person detector. Our approach also functions well in real-life scenarios where the patch is filmed by a camera. To the best of our knowledge we are the first to attempt this kind of attack on targets with a high level of intra-class variety like persons.
• More adding Wayne’s notes into JASS paper. Figured out how to make something that looks like blockquotes without screwing up the JASS formatting:
\hspace{1cm}\begin{minipage}{\dimexpr\textwidth-2cm}
\textit{"Get him home.  And deliver my cut of earnings to the people of Phandalin near Neverwinter, my home". With this, before anyone can stop him, Edmund turns to the dragon. "I make a counter offer.  In exchange for them motions to the two caged people. I offer myself to take their place.  I will remain.  I will starve.  You will lose two peasants, and in return you will gain all that I have to offer.  Edmund of house DeVir of Neverwinter.  The last of a noble bloodline of the ruling class."} - Edmond: Group 2
\end{minipage}
• More Machine Teaching paper