Collaborate Disseminate
It used to be that surveillance cameras were passive. Maybe they just recorded, and no one looked at the video unless they needed to. Maybe a bored guard watched a dozen different screens, scanning for something interesting. In either case, the video was only stored for a few days because storage was expensive. Increasingly, none of that is true. Recent… Continue reading Computers and Video Surveillance
The ACLU’s Jay Stanley has just published a fantastic report: "The Dawn of Robot Surveillance" (blog post here) Basically, it lays out a future of ubiquitous video cameras watched by increasingly sophisticated video analytics software, and discusses the potential harms to society. I’m not going to excerpt a piece, because you really need to read the whole thing…. Continue reading Video Surveillance by Computer
Yesterday, I visited the NSA. It was Cyber Command’s birthday, but that’s not why I was there. I visited as part of the Berklett Cybersecurity Project, run out of the Berkman Klein Center and funded by the Hewlett Foundation. (BERKman hewLETT — get it? We have a web page, but it’s badly out of date.) It was a full day… Continue reading Visiting the NSA
Yesterday, I visited the NSA. It was Cyber Command’s birthday, but that’s not why I was there. I visited as part of the Berklett Cybersecurity Project, run out of the Berkman Klein Center and funded by the Hewlett Foundation. (BERKman hewLETT — get it… Continue reading Visiting the NSA
Nice bit of adversarial machine learning. The image from this news article is most of what you need to know, but here’s the research paper…. Continue reading Fooling Automated Surveillance Cameras with Patchwork Color Printout
In what I am sure is only a first in many similar demonstrations, researchers are able to add or remove cancer signs from CT scans. The results easily fool radiologists. I don’t think the medical device industry has thought at all about data integrity and authentication issues. In a world where sensor data of all kinds is undetectably manipulatable, they’re… Continue reading Maliciously Tampering with Medical Imagery
Researchers have been able to fool Tesla’s autopilot in a variety of ways, including convincing it to drive into oncoming traffic. It requires the placement of stickers on the road. Abstract: Keen Security Lab has maintained the security research work … Continue reading Adversarial Machine Learning against Tesla’s Autopilot
Researchers have been able to fool Tesla’s autopilot in a variety of ways, including convincing it to drive into oncoming traffic. It requires the placement of stickers on the road. Abstract: Keen Security Lab has maintained the security research work on Tesla vehicle and shared our research results on Black Hat USA 2017 and 2018 in a row. Based on… Continue reading Adversarial Machine Learning against Tesla’s Autopilot
No one doubts that artificial intelligence (AI) and machine learning (ML) will transform cybersecurity. We just don’t know how, or when. While the literature generally focuses on the different uses of AI by attackers and defenders and the resultant a… Continue reading Machine Learning to Detect Software Vulnerabilities
No one doubts that artificial intelligence (AI) and machine learning (ML) will transform cybersecurity. We just don’t know how, or when. While the literature generally focuses on the different uses of AI by attackers and defenders and the resultant arms race between the two I want to talk about software vulnerabilities. All software contains bugs. The reason is… Continue reading Machine Learning to Detect Software Vulnerabilities