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Machine Learning Advances Tool to Fight Cybercrime in the Cloud Purdue University News

Chris Adam
November 5, 2019

Purdue University researchers used machine learning to develop a cloud forensic model that collects digital evidence associated with illegal activities in cloud storage applications. The system deploys deep learning models to classify child exploitation, illegal drug trafficking, and illegal firearms transactions uploaded to cloud storage applications, and to automatically report detection of any such illegal activities via a forensic evidence collection system. The researchers tested the system on more than 1,500 images, and found that the model accurately classified an image about 96% of the time. Said Purdue’s Fahad Salamh, “It is important to automate the process of digital forensic and incident response in order to cope with advanced technology and sophisticated hiding techniques and to reduce the mass storage of digital evidence on cases involving cloud storage applications.”

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China’s Policing Robot: Cattle Prod Meets Supercomputer

Computerworld (10/31/16) Patrick Thibodeau

Chinese researchers have developed AnBot, an “intelligent security robot” deployed in a Shenzhen airport. The backend of AnBot is linked to China’s Tianhe-2 supercomputer, where it has access to cloud services. AnBot uses these technologies to conduct patrols, recognize threats, and identify people with multiple cameras and facial recognition. The cloud services give the robots petascale processing power, well beyond the processing capabilities in the robot itself. The supercomputer connection enhances the intelligent learning capabilities and human-machine interface of the devices, according to a U.S.-China Economic and Security Review report that focuses on China’s autonomous systems development efforts. The report found the ability of robotics to improve depends on the linking of artificial intelligence (AI), data science, and computing technologies. In addition, the report notes simultaneous development of high-performance computing systems and robotic mechanical manipulation give AI the potential to unleash smarter robotic devices that are capable of learning as well as integrating inputs from large databases. The report says the U.S. government should increase its own efforts in developing manufacturing technology in critical areas, as well as monitoring China’s growing investments in robotics and AI companies in the U.S.

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Intelligence Agency Wants an Even More Super Supercomputer

NextGov.com (12/03/14) Frank Konkel

A new computer program of the U.S. Intelligence Advanced Research Projects Activity (IARPA) could fundamentally change the field of supercomputing. The Cryogenic Computer Complexity (C3) program will use recent breakthroughs in superconducting technologies to find a long-term successor to complementary metal-oxide semiconductor technology-based machines, which are becoming unmanageable. “Computers based on superconducting logic integrated with new kinds of cryogenic memory will allow expansion of current computing facilities while staying within space and energy budgets, and may enable supercomputer development beyond the exascale,” says IARPA’s Marc Manheimer. IARPA has awarded research contracts to teams led by IBM, Raytheon-BBN, and Northrop Grumman. C3 will develop critical components for memory and logic subsystems and plan a prototype computer. The goal is to integrate the components into the world’s first superconducting supercomputer. The machine would be smaller, require less physical infrastructure to cool, and would have a smaller energy footprint than current supercomputers.

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