Download 60 second binary options strategies system

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to emulation [link] [comments]

Games playable on Intel HD4400 (and how to get them running) in 2020

I used to be a "LoFi Gamer".
It wasn't ideal BUT I managed to play thru tonnes of modern games thanks to a bit of research and elbow grease. The obvious choice was to eventually upgrade, which I did and I am relieved to have my new set up. HOWEVER these things take time, and you don' t need to miss out whilst you're saving your pennies up!!
The games listed below are my complete list of titles that I managed to run successfully, between 30 - 60 frames per second and I think it's pretty amazing I was running games released in 2020 from a beat up old Dell laptop that cost me under £300 4 years ago.
Hopefully this guide will help some people out there who, like me, were chomping at the bit to get a powerful setup but didn't want to miss out on some great gaming experiences in the meantime.

My laptop specs were: Intel HD4400 // Intel Core i5 // Win 10 // 8G Ram

Additionally I installed:
- Intel Extreme Tuning Utility (overclocking tool, Google / Youtube for user guides, very easy)
- SpeedFan (fan control application, because your laptop will be as hot as a toaster otherwise)
- NVIDIA 3D Vision Driver 353.62
- NVIDIA Graphics Driver 353.62
- NVIDIA HD Audio Driver 1.3.34.3
- NVIDIA nView 146.33
- NVIDIA PhysX System Software 9.18.0907
- NVIDIA Control Panel

I also recommend:
- Updating DirectX and Intel graphics card drivers
- Setting Windows 10 to "Game Mode"
- Optimising the "Visual Effects Settings" by selecting the "Adjust for Best Performance" option
- Using a "High Performance Power Plan"
- Playing the games with the laptop battery removed, taking power only from the mains
- Tweaking each games, in-game graphic settings individually to find the right balance between looks and performance
If you need help or advice about anything listed above, a quick Google search using the search terms I have provided you with, will give you all the insight you need. It is all available freeware and easy peasy to get hold of, especially as you now know exactly what to search for and download.

For the best results, it's essential you get/do everything on the list and it's probably worth mentioning that the overclocking and fan control software needs to be running before you launch a game (duh).
It also goes without saying that you WILL NOT BE RUNNING ANY GAMES AT MAX SETTINGS. We're prioritising frames per second over everything else here.

And so, without further ado...

THE LIST (A-Z + year of release)
- Alien Isolation (2014)
- American Fugitive (2019)
- Aragami (2016)
- Arrest of a stone Buddah (2020)
- Assassins Creed Black Flag (2014)
- Assassins Creed Chronicles (China, India and Russia) (2015)
- Assasins Creed Rogue (2014)
- Axiom Verge (2015)
- Bayonetta (2009)
- BELOW (2018)
- Bendy and the Ink Machine (2017)
- Betrayer (2014)
- Binary Domain (2012)
- Blasphemous (2019)
- Blazblue: Calamity Trigger (2008)
- Bully: Scholarship Edition (2006)
- Carrion (2020)
- Catherine Classic (2011)
- Cloudpunk (2020)
- Condemned: Criminal Origins (2006)
- Cuphead (2017)
- D4: Dark Dreams Don't Die (2014)
- Darkwood (2017)
- DEADBOLT (2016)
- Dead Cells (2017)
- Deadly Premonition: The Directors Cut (2013)
- Death to Spies (2007)
- Desperados III (2020)
- Deus EX: Human Revolution Directors Cut (2011)
- Deus Ex: Breach (2017)
- Disco Elysium (2019)
- DOOM 3 (2004)
- DOOM (2016)
- Don't Starve (2013)
- Don't Starve Together (2016)
- The Dream Machine (2012)
- Dust: An Elysian Tail (2013)
- Enter the Gungeon (2016)
- The Flame In The Flood (2016)
- The friends of Ringo Ishikawa (2018)
- Furi (2016)
- The Guild 2: renaissance (2010)
- Grand Theft Auto V (2013)
- GRIP: Combat Racing (2016)
- Gunfire Reborn (2020, still in Early Access)
- Hades (2020, still in Early Access)
- High Hell (2017)
- Hob (2017)
- Hollow Knight (2017)
- The Hong Kong Massacre (2019)
- Hotline Miami ( I+II) (2012 // 2015)
- How To Survive 2 (2016)
- Hyper Light Drifter (2016)
- INSIDE (2016)
- Ion Fury (2019)
- Just Cause 2 (+ JC2MP) (2013)
- Just Cause 3 (2015)
- Just Shapes & Beats (2018)
- KATANA KAMI: A Way of the Samurai Story (2020)
- Katana Kata (2020, still in Early Access)
- Katana ZERO (2019)
- Kenshi (2018)
- Killer Is Dead: Nightmare Edition (2014)
- killer7 (2018)
- L.A. Noire (2011)
- Lucius (I+II) (2012 // 2015)
- Lucius Demake (2016)
- Mad Max (2015)
- Mafia II (Classic) (2012)
- Mark of the Ninja (2016)
- MAXIMUM Action (2020, still in Early Access)
- Max Payne 3 (2012)
- The Messenger (2018)
- Metal Gear Rising: Revengeance (2014)
- Metal Gear Solid V: Ground Zeroes (2014)
- Metal Gear Solid V: The Phantom Pain (2015)
- Mother Russia Bleeds (2016)
- Omensight: Definitive Edition (2018)
- Ori and the Blind Forest: Definitive Edition (2016)
- Ori and the Will of the Wisps (2020)
- Pathologic 2 (2019)
- Pathologic Classic HD (2015)
- Persona 4 Golden (2020)
- POSTAL 2 (2003)
- Project Warlock (2018)
- Rain World (2017)
- Redeemer: Enhanced Edition (2017)
- Rim World (2018)
- Risk of Rain (2013)
- Risk of Rain 2 (2020)
- Ryse: Son of Rome (2014)
- Saints Row 2 (2009)
- Saints Row The Third (2011)
- Saints Row IV (2014)
- Saints Row: Gat out of Hell (2015)
- Salt and Sanctuary (2016)
- Samurai Shodown V Special (2019)
- Shadow Tactics: Blades of the Shogun (2016)
- Shadow Warrior (2013)
- Shadow Warrior 2 (?2016)
- Shenmue I & II (2018)
- Sleeping Dogs Definitive Edition (2014)
- State Of Mind (2018)
- Street Fighter 4 (2008)
- Street Fighter X Tekken (2012)
- Streets of Rage 4 (2020)
- Streets of Rogue (2019)
- Strider (2014)
- Subterrain (2016)
- Sunless Sea (2015)
- Sunless Skies (2019)
- SUPERHOT (2016)
- SUPERHOT: MIND CONTROL DELETE (2020)
- SYNTHETIK (2018)
- The Takeover (2019)
- TEKKEN 7 (201
- Thief (2014)
- Thief Deadly Shadows (2004)
- This War of Mine (2014)
- Thumper (2016)
- Transistor (2014)
- Travis Strikes Again: No More Heroes (2019)
- Ultrakill (2020)
- Unforgiving - A Northern Hymn (2017)
- Valfaris (2019)
- Way Of The Samurai 4 (2015)
- West of Dead (2020)
- The Witcher 2 (2011)
- Wonder Boy: The Dragon's Trap (2017)
- XCOM 2 (2016)
- Yakuza 0 (2017)
- Yakuza Kiwami (2019)

Happy gaming!
My advice is to buy these games during a Steam sale, alongside a Logitech F310 controller and enjoy the hours of entertainment ahead of you. With even more trial and error, you could add loads of games to this list too. Don't forget the Steam refund policy works in your favour to see if you can get a game running on your setup :)

*One last (boring) thing\*
This is abusing your laptop and in reality asking it to do something it wasn't built to. Be aware that you could shorten its lifespan through the constant demands of gaming and the potential risk from over-heating caused by regular gaming sessions for hours at a time is a real one.
Your plan should be to upgrade in the future... But until then I'd say treat your laptop like an emulator!!

- Aggressive Chicken
submitted by Aggressive_Chicken_ to u/Aggressive_Chicken_ [link] [comments]

MAME 0.222

MAME 0.222

MAME 0.222, the product of our May/June development cycle, is ready today, and it’s a very exciting release. There are lots of bug fixes, including some long-standing issues with classics like Bosconian and Gaplus, and missing pan/zoom effects in games on Seta hardware. Two more Nintendo LCD games are supported: the Panorama Screen version of Popeye, and the two-player Donkey Kong 3 Micro Vs. System. New versions of supported games include a review copy of DonPachi that allows the game to be paused for photography, and a version of the adult Qix game Gals Panic for the Taiwanese market.
Other advancements on the arcade side include audio circuitry emulation for 280-ZZZAP, and protection microcontroller emulation for Kick and Run and Captain Silver.
The GRiD Compass series were possibly the first rugged computers in the clamshell form factor, possibly best known for their use on NASA space shuttle missions in the 1980s. The initial model, the Compass 1101, is now usable in MAME. There are lots of improvements to the Tandy Color Computer drivers in this release, with better cartridge support being a theme. Acorn BBC series drivers now support Solidisk file system ROMs. Writing to IMD floppy images (popular for CP/M computers) is now supported, and a critical bug affecting writes to HFE disk images has been fixed. Software list additions include a collection of CDs for the SGI MIPS workstations.
There are several updates to Apple II emulation this month, including support for several accelerators, a new IWM floppy controller core, and support for using two memory cards simultaneously on the CFFA2. As usual, we’ve added the latest original software dumps and clean cracks to the software lists, including lots of educational titles.
Finally, the memory system has been optimised, yielding performance improvements in all emulated systems, you no longer need to avoid non-ASCII characters in paths when using the chdman tool, and jedutil supports more devices.
There were too many HyperScan RFID cards added to the software list to itemise them all here. You can read about all the updates in the whatsnew.txt file, or get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

submitted by cuavas to MAME [link] [comments]

MAME 0.219

MAME 0.219

MAME 0.219 arrives today, just in time for the end of February! This month we’ve got another piece of Nintendo Game & Watch history – Pinball – as well as a quite a few TV games, including Dream Life Superstar, Designer’s World, Jenna Jameson’s Strip Poker, and Champiyon Pinball. The previously-added Care Bears and Piglet’s Special Day TV games are now working, as well as the big-endian version of the MIPS Magnum R4000. As always, the TV games vary enormously in quality, from enjoyable titles, to low-effort games based on licensed intellectual properties, to horrible bootlegs using blatantly copied assets. If music/rhythm misery is your thing, there’s even a particularly bad dance mat game in there.
On the arcade side, there are fixes for a minor but long-standing graphical issue in Capcom’s genre-defining 1942, and also a fairly significant graphical regression in Seibu Kaihatsu’s Raiden Fighters. Speaking of Seibu Kaihatsu, our very own Angelo Salese significantly improved the experience in Good E-Jan, and speaking of graphics fixes, cam900 fixed some corner cases in Data East’s innovative, but little-known, shoot-’em-up Boogie Wings. Software list additions include the Commodore 64 INPUT 64 collection (courtesy of FakeShemp) and the Spanish ZX Spectrum Load’N’Run collection (added by ICEknight). New preliminary CPU cores and disassemblers include IBM ROMP, the NEC 78K family, Samsung KS0164 and SSD Corp’s Xavix 2.
As always, you can get the source and 64-bit Windows binary packages from the download page.

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to emulation [link] [comments]

Полезно. ПО Fawkes - клоакинг фотографий для защиты от систем распознавания лиц. Защитите ваши фото ! Скачать ПО Fawkes. Как использовать ПО Fawkes установка. Image "Cloaking" for Personal Privacy. Fawkes Usage - Setup Instructions

Как защититься от системы распознавания лиц при помощи ПО Fawkes
Как защититься от массовой слежки и идентификации людей по лицу

Полезно. ПО Fawkes - клоакинг фотографий для защиты от систем распознавания лиц. Защитите ваши фото !
Скачать ПО Fawkes. Как использовать ПО Fawkes , установка.
Image "Cloaking" for Personal Privacy. Fawkes Usage - Setup Instructions

Алгоритм Fawkes эффективно подрывает базу обучения «вражеской» нейросети. Перед публикацией каждой фотографии в ней делаются незаметные попиксельные изменения, после чего она становится не то что непригодной для использования при обучении, а буквально портит систему распознавания лиц.

Обработайте ваши фотографии с помощью Fawkes -> Загружайте ваши фото в социальные сети

сайт: http://sandlab.cs.uchicago.edu/fawkes/

Fawkes - Image "Cloaking" for Personal Privacy
For more information about the project, please refer to our project webpage http://sandlab.cs.uchicago.edu/fawkes/

Как использовать ПО Fawkes и установка - Fawkes Usage - Setup Instructions
https://github.com/Shawn-Shan/fawkes/blob/mastefawkes/README.md
https://github.com/Shawn-Shan/fawkes/tree/maste

Инструкции по установке Fawkes Setup Instructions
https://github.com/Shawn-Shan/fawkes/blob/mastefawkes/README.md
Publication & Presentation - PDF
Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models.
Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, and Ben Y. Zhao.
In Proceedings of USENIX Security Symposium 2020. ( Download PDF here )
https://people.cs.uchicago.edu/%7Eravenben/publications/abstracts/fawkes-usenix20.html
https://people.cs.uchicago.edu/%7Eravenben/publications/pdf/fawkes-usenix20.pdf


Frequently Asked Questions http://sandlab.cs.uchicago.edu/fawkes/

---------------------------------

Скачать ПО Fawkes:

Downloads and Source Code - Version 0.3 (July 2020)
http://sandlab.cs.uchicago.edu/fawkes/

Download the Fawkes Software:

Fawkes.dmg for Mac (v0.3)
DMG file with installer app
Compatibility: MacOS 10.13, 10.14, 10.15
https://mirror.cs.uchicago.edu/fawkes/files/0.3/Fawkes-0.3.dmg

Fawkes.exe for Windows (v0.3)
EXE file
Compatibility: Windows 10
https://mirror.cs.uchicago.edu/fawkes/files/0.3/Fawkes-0.3.exe

Бинарник для Mac
Fawkes Executable Binary
https://mirror.cs.uchicago.edu/fawkes/files/0.3/fawkes_binary_mac-v0.3.zip

Бинарник для Windows
Fawkes Executable Binary
https://mirror.cs.uchicago.edu/fawkes/files/0.3/fawkes_binary_windows-v0.3.zip

Бинарник для Linux
Fawkes Executable Binary
https://mirror.cs.uchicago.edu/fawkes/files/0.3/fawkes_binary_linux-v0.3.zip

Инструкции по установке Setup Instructions
https://github.com/Shawn-Shan/fawkes/blob/mastefawkes/README.md

Исходный код Fawkes на GitHub
Fawkes Source Code on Github, for development
https://github.com/Shawn-Shan/fawkes

---------------------------------------------------------------------

Клоакинг фотографий для защиты от систем распознавания лиц

https://habr.com/ru/company/itsumma/news/t/512122/
23 июля 2020
Информационная безопасность,
Open source,
Обработка изображений,
Киберпанк
Современные системы распознавания лиц представляют угрозу личной приватности. Уже сейчас такие системы ежедневно сканируют миллионы лиц в Китае, Великобритании и России без их согласия. Поставлена задача, чтобы в следующем году 100% пассажиров в топ-20 аэропортов США незаметно подвергали этой процедуре.
https://www.whitehouse.gov/presidential-actions/executive-order-protecting-nation-foreign-terrorist-entry-united-states-2/


Исследователи из Чикагского университета придумали любопытный алгоритм клоакинга, который позволяет защититься от распознавания лиц.
http://sandlab.cs.uchicago.edu/fawkes/

Дело в том, что системы распознавания лиц берут фотографии для обучения своей системы из ваших открытых данных — в основном, из профилей в социальных сетях и других открытых источников.

Например, крупнейшая система распознавания лиц Clearview.ai для обучения использовала более трёх миллиардов фотографий из интернета и социальных сетей. Clearview.ai демонстрирует, насколько легко построить такую систему распознавания на снимках из Facebook и «Вконтакте».
https://clearview.ai/

https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial-recognition.html

Так вот, новый алгоритм Fawkes эффективно подрывает базу обучения «вражеской» нейросети. Перед публикацией каждой фотографии в ней делаются незаметные попиксельные изменения, после чего она становится не то что непригодной для использования при обучении, а буквально портит систему распознавания лиц.


Схема работы Fawkes https://hsto.org/webt/vu/r2/ao/vur2aoiyij6hcfibjxpfo8-q9b8.jpeg

Программа Fawkes работает локально на вашем компьютере и выполняет клоакинг фотографий. После обработки вы можете использовать фотографии как угодно — публиковать в социальных сетях, передавать друзьям или распечатывать на бумаге. В любом случае, для распознавания лиц они уже бесполезны, как показала проверка в ходе научного исследования чикагской группы.


Интуитивно понятное пояснение в 2D-пространстве из четырёх признаков A, B, U, T, почему модель, обученная на искажённых фотографиях, не распознаёт лица на оригиналах. Слева — границы принятия решений при обучении на оригиналах, справа — границы принятия решений при обучении после клоакинга
https://hsto.org/webt/gc/bq/f1/gcbqf1bgswyycpjzszuirvgjv6w.png

Тестирование показало, что эффект клоакинга трудно распознать при обучении нейросети и он не вызывает ошибок при обучении. Другими словами, операторы системы распознавания лиц не заподозрят ничего неладного. Но просто если кто-то попытается выполнить распознавание на вашем оригинальном изображении (например, с камер наблюдения), поиск по базе не найдёт совпадений.

Fawkes протестирован и показал эффективность 100% против самых известных моделей распознавания Microsoft Azure Face API, Amazon Rekognition и Face++.

Алгоритмы сжатия изображений тоже не портят защиту клоакинга. Исследователи проверяли материал на прогрессивном JPEG, который используется в Facebook и Twitter для пережатия картинок, на уровнях качества от 5 до 95. В общем, сжатие немного ослабляет защиту клоакинга, но при этом ещё более значительно снижается качество распознавания лиц. То есть нашей задачи помех в классификации это не мешает.

Как ни странно, заблюривание фотографий и применение разных графических фильтров тоже не снимает защиту, поскольку по своей сути клоакинг происходит не на уровне пикселей, а на уровне пространства признаков, то есть пиксельные измененимя на самом деле имеют глубокую природу и не стираются в растровом редакторе.

Техническая статья с описанием алгоритма (pdf) будет представлена на ближайшем симпозиуме USENIX по безопасности 12? 14 августа 2020 года.
http://people.cs.uchicago.edu/~ravenben/publications/pdf/fawkes-usenix20.pdf

Кстати, название программы позаимствовано от маски Гая Фокса из фильма «V — значит вендетта».

Скачать программу Fawkes: http://sandlab.cs.uchicago.edu/fawkes/
Open Source
Обработка изображений
Информационная безопасность
Киберпанк
Fawkes
распознавание лиц
клоакинг
V — значит вендетта
Информационная безопасность
Обработка изображений
Киберпанк

--------------------------------------------------------
How to Setup
Fawkes Binary
https://github.com/Shawn-Shan/fawkes/blob/mastefawkes/README.md

This application is built for individuals to cloak their images before uploading to the Internet. For more information about the project, please refer to our project webpage.

If you are a developer or researcher planning to customize and modify on our existing code. Please refer to fawkes.

How to Setup

MAC:

Download the binary following this link and unzip the download file.
Create a directory and move all the images you wish to protect into that directory. Note the path to that directory (e.g. ~/Desktop/images).
Open terminal and change directory to fawkes (the unzipped folder).
(If your MacOS is Catalina) Run sudo spctl --master-disable to enable running apps from unidentified developer. We are working on a solution to bypass this step.
Run ./protection-v0.3 -d IMAGE_DIR_PATH to generate cloak for images in IMAGE_DIR_PATH.
When the cloaked image is generated, it will output a *_min_cloaked.png image in IMAGE_DIR_PATH. The generation takes ~40 seconds per image depending on the hardware.

PC:

Download the binary following this link and unzip the download file.
Create a directory and move all the images you wish to protect into that directory. Note the path to that directory (e.g. ~/Desktop/images).
Open terminal(powershell or cmd) and change directory to protection (the unzipped folder).
Run protection-v0.3.exe -d IMAGE_DIR_PATH to generate cloak for images in IMAGE_DIR_PATH.
When the cloaked image is generated, it will output a *_min_cloaked.png image in IMAGE_DIR_PATH. The generation takes ~40 seconds per image depending on the hardware.

Linux:

Download the binary following this link and unzip the download file.
Create a directory and move all the images you wish to protect into that directory. Note the path to that directory (e.g. ~/Desktop/images).
Open terminal and change directory to protection (the unzipped folder).
Run ./protection-v0.3 -d IMAGE_DIR_PATH to generate cloak for images in IMAGE_DIR_PATH.
When the cloaked image is generated, it will output a *_min_cloaked.png image in IMAGE_DIR_PATH. The generation takes ~40 seconds per image depending on the hardware.

More details on the optional parameters check out the github repo
https://github.com/Shawn-Shan/fawkes/tree/maste
------------------------

Usage
Fawkes https://github.com/Shawn-Shan/fawkes/tree/maste

Fawkes is a privacy protection system developed by researchers at SANDLab, University of Chicago. For more information about the project, please refer to our project webpage. Contact us at [[email protected]](mailto:[email protected]).

We published an academic paper to summarize our work "Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models" at USENIX Security 2020.

NEW! If you would like to use Fawkes to protect your identity, please check out our software and binary implementation on the website.
Copyright
This code is intended only for personal privacy protection or academic research.
We are currently exploring the filing of a provisional patent on the Fawkes algorithm.


Usage

$ fawkes

Options:

-m, --mode : the tradeoff between privacy and perturbation size. Select from min, low, mid, high. The higher the mode is, the more perturbation will add to the image and provide stronger protection.
-d, --directory : the directory with images to run protection.
-g, --gpu : the GPU id when using GPU for optimization.
--batch-size : number of images to run optimization together. Change to >1 only if you have extremely powerful compute power.
--format : format of the output image (png or jpg).

when --mode is custom:

--th : perturbation threshold
--max-step : number of optimization steps to run
--lr : learning rate for the optimization
--feature-extractor : name of the feature extractor to use
--separate_target : whether select separate targets for each faces in the diectory.

Example

fawkes -d ./imgs --mode min
Tips

The perturbation generation takes ~60 seconds per image on a CPU machine, and it would be much faster on a GPU machine. Use batch-size=1 on CPU and batch-size>1 on GPUs.
Turn on separate target if the images in the directory belong to different people, otherwise, turn it off.

How do I know my images are secure?

We are actively working on this. Python scripts that can test the protection effectiveness will be ready shortly.
Quick Installation

Install from PyPI:

pip install fawkes

If you don't have root privilege, please try to install on user namespace: pip install --user fawkes.


---------------------------------------------------------------------------------
Image "Cloaking" for Personal Privacy http://sandlab.cs.uchicago.edu/fawkes/

Original Cloaked
http://sandlab.cs.uchicago.edu/fawkes/images/shawn.jpg
http://sandlab.cs.uchicago.edu/fawkes/images/shawncloaked.jpg

Original Cloaked
http://sandlab.cs.uchicago.edu/fawkes/images/emily.jpg
http://sandlab.cs.uchicago.edu/fawkes/images/emilycloaked.jpg

2020 is a watershed year for machine learning. It has seen the true arrival of commodized machine learning, where deep learning models and algorithms are readily available to Internet users. GPUs are cheaper and more readily available than ever, and new training methods like transfer learning have made it possible to train powerful deep learning models using smaller sets of data.

But accessible machine learning also has its downsides. A recent New York Times article by Kashmir Hill profiled clearview.ai, an unregulated facial recognition service that has downloaded over 3 billion photos of people from the Internet and social media and used them to build facial recognition models for millions of citizens without their knowledge or permission. Clearview.ai demonstrates just how easy it is to build invasive tools for monitoring and tracking using deep learning.

So how do we protect ourselves against unauthorized third parties building facial recognition models that recognize us wherever we may go? Regulations can and will help restrict the use of machine learning by public companies but will have negligible impact on private organizations, individuals, or even other nation states with similar goals.

The SAND Lab at University of Chicago has developed Fawkes1, an algorithm and software tool (running locally on your computer) that gives individuals the ability to limit how their own images can be used to track them. At a high level, Fawkes takes your personal images and makes tiny, pixel-level changes that are invisible to the human eye, in a process we call image cloaking. You can then use these "cloaked" photos as you normally would, sharing them on social media, sending them to friends, printing them or displaying them on digital devices, the same way you would any other photo. The difference, however, is that if and when someone tries to use these photos to build a facial recognition model, "cloaked" images will teach the model an highly distorted version of what makes you look like you. The cloak effect is not easily detectable by humans or machines and will not cause errors in model training. However, when someone tries to identify you by presenting an unaltered, "uncloaked" image of you (e.g. a photo taken in public) to the model, the model will fail to recognize you.

Fawkes has been tested extensively and proven effective in a variety of environments and is 100% effective against state-of-the-art facial recognition models (Microsoft Azure Face API, Amazon Rekognition, and Face++). We are in the process of adding more material here to explain how and why Fawkes works. For now, please see the link below to our technical paper, which will be presented at the upcoming USENIX Security Symposium, to be held on August 12 to 14.

The Fawkes project is led by two PhD students at SAND Lab, Emily Wenger and Shawn Shan, with important contributions from Jiayun Zhang (SAND Lab visitor and current PhD student at UC San Diego) and Huiying Li, also a SAND Lab PhD student. The faculty advisors are SAND Lab co-directors and Neubauer Professors Ben Zhao and Heather Zheng.

1The Guy Fawkes mask, a la V for Vendetta

In addition to the photos of the team cloaked above, here are a couple more examples of cloaked images and their originals. Can you tell which is the original? (Cloaked image of the Queen courtesy of TheVerge).
Publication & Presentation

Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models.
Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, and Ben Y. Zhao.
In Proceedings of USENIX Security Symposium 2020. ( Download PDF here )
https://people.cs.uchicago.edu/%7Eravenben/publications/abstracts/fawkes-usenix20.html
https://people.cs.uchicago.edu/%7Eravenben/publications/pdf/fawkes-usenix20.pdf

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