Collaborating Authors

We're Building a World-Size Robot, and We Don't Even Realize It


Last year, on October 21, your digital video recorder -- or at least a DVR like yours -- knocked Twitter off the internet. Someone used your DVR, along with millions of insecure webcams, routers, and other connected devices, to launch an attack that started a chain reaction, resulting in Twitter, Reddit, Netflix, and many sites going off the internet. You probably didn't realize that your DVR had that kind of power. This has as much to do with the computer market as it does with the technologies. We prefer our software full of features and inexpensive, at the expense of security and reliability. That your computer can affect the security of Twitter is a market failure. The industry is filled with market failures that, until now, have been largely ignorable. As computers continue to permeate our homes, cars, businesses, these market failures will no longer be tolerable. Our only solution will be regulation, and that regulation will be foisted on us by a government desperate to "do something" in the face of disaster. In this article I want to outline the problems, both technical and political, and point to some regulatory solutions. Regulation might be a dirty word in today's political climate, but security is the exception to our small-government bias. And as the threats posed by computers become greater and more catastrophic, regulation will be inevitable. So now's the time to start thinking about it. We also need to reverse the trend to connect everything to the internet. And if we risk harm and even death, we need to think twice about what we connect and what we deliberately leave uncomputerized. If we get this wrong, the computer industry will look like the pharmaceutical industry, or the aircraft industry. But if we get this right, we can maintain the innovative environment of the internet that has given us so much.

Machine Learning in IoT Security: Current Solutions and Future Challenges Machine Learning

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives. The participating nodes in IoT networks are usually resource-constrained, which makes them luring targets for cyber attacks. In this regard, extensive efforts have been made to address the security and privacy issues in IoT networks primarily through traditional cryptographic approaches. However, the unique characteristics of IoT nodes render the existing solutions insufficient to encompass the entire security spectrum of the IoT networks. This is, at least in part, because of the resource constraints, heterogeneity, massive real-time data generated by the IoT devices, and the extensively dynamic behavior of the networks. Therefore, Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, are leveraged to cope with different security problems. In this paper, we systematically review the security requirements, attack vectors, and the current security solutions for the IoT networks. We then shed light on the gaps in these security solutions that call for ML and DL approaches. We also discuss in detail the existing ML and DL solutions for addressing different security problems in IoT networks. At last, based on the detailed investigation of the existing solutions in the literature, we discuss the future research directions for ML- and DL-based IoT security.

Protecting Your Clouds - Research Report


In February 2017, CBS Interactive's Tech Pro Research reached out via email to registered users of ZDNet and TechRepublic in the United States to engage them in a survey about their current cloud security operations and priorities.

100 Best Pluralsight Free Courses and Certification 2020


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Mirai DDoS attack against KrebsOnSecurity cost device owners $300,000


The distributed denial-of-service (DDoS) which knocked KrebsOnSecurity offline for days cost owners of devices unwittingly involved in the attack upwards of $300,000, researchers suggest. The DDoS attack took place in 2016 and was made possible through the Mirai botnet, a network of enslaved Internet of Things (IoT) devices including routers, surveillance cameras, and smart home systems. Non-existent or poor security practices, including the use of hardcoded and factory passwords, allowed the operators of the botnet to scour the web for the means to hook up and enslave these devices, providing the bandwidth necessary to launch an attack able to smash the KrebsOnSecurity domain and prevent legitimate traffic from getting through. The access disruption was an annoyance for visitors and a severe headache for Akamai, which used to host the renowned security expert's blog pro bono. The cost of the attack to the cloud security provider in fending off the 620 Gbps DDoS assault, which could have eventually reached millions of dollars, led to Google's Project Shield offering to take on the blog.