Half of the Largest Companies: Threat Vulnerable
October 24, 2016
Compromised Credentials, a research report by Digital Shadows reveals that around 1,000 companies comprising of Forbes Global 2000 are at risk as credentials of their employees are leaked or compromised.
As reported by Channel EMEA in Digital Shadows Global Study Reveals UAE Tops List in Middle East for…
The report found that 97 percent of those 1000 of the Forbes Global 2000 companies, spanning all businesses sectors and geographical regions, had leaked credentials publicly available online, many of them from third-party breaches.
Owing to large-scale data breaches in recent times, credentials of 5.5 million employees are available in public domain for anyone to see. Social networks like LinkedIN, MySpace and Tumblr were the affliction points of these breaches, the report states.
Analyzed geographically, companies in Middle-East seem to be the most affected:
The report revealed that the most affected country in the Middle East – with over 15,000 leaked credentials was the UAE. Saudi Arabia (3360), Kuwait (203) followed by Qatar (99) made up the rest of the list. This figure is relatively small as compared to the global figure due to the lower percentage of organizations that reside in the Middle East.
Affected organizations may not be able to contain the damages by simply resetting the passwords of the employees. It also needs to be seen if the information available is contemporary, not reposted and is unique. Moreover, mere password resetting can cause lot of friction within the IT departments of the organizations.
Without proper analysis, it will be difficult for the affected companies to gauge the extent of the damage. But considering the PR nightmare it leads to, will these companies come forward and acknowledge the breaches?
Vishal Ingole, October 24, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The State Department Delves into Social Media
October 13, 2015
People and companies that want to increase a form of communication between people create social media platforms. Facebook was invented to take advantage of the digital real-time environment to keep people in contact and form a web of contacts. Twitter was founded for a more quick and instantaneous form of communication based on short one hundred forty character blurbs. Instagram shares pictures and Pinterest connects ideas via pictures and related topics. Using analytics, the social media companies and other organizations collect data on users and use that information to sell products and services as well as understanding the types of users on each platform.
Social media contains a variety of data that can benefit not only private companies, but the government agencies as well. According to GCN, the “State Starts Development On Social Media And Analytics Platform” to collaborate and contribute in real-time to schedule and publish across many social media platforms and it will also be mobile-enabled. The platform will also be used to track analytics on social media:
“For analytics, the system will analyze sentiment, track trending social media topics, aggregate location and demographic information, rank of top multimedia content, identify influencers on social media and produce automated and customizable reports.”
The platform will support twenty users and track thirty million mentions each year. The purpose behind the social media and analytics platform is still vague, but the federal government has proven to be behind in understanding and development of modern technology. This appears to be a step forward to upgrade itself, so it does not get left behind. But a social media platform that analyzes data should have been implemented years ago at the start of this big data phenomenon.
Whitney Grace, October 13, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Is Collaboration the Key to Big Data Progress?
May 22, 2015
The article titled Big Data Must Haves: Capacity, Compute, Collaboration on GCN offers insights into the best areas of focus for big data researchers. The Internet2 Global Summit is in D.C. this year with many exciting panelists who support the emphasis on collaboration in particular. The article mentions the work being presented by several people including Clemson professor Alex Feltus,
“…his research team is leveraging the Internet2 infrastructure, including its Advanced Layer 2 Service high-speed connections and perfSONAR network monitoring, to substantially accelerate genomic big data transfers and transform researcher collaboration…Arizona State University, which recently got 100 gigabit/sec connections to Internet2, has developed the Next Generation Cyber Capability, or NGCC, to respond to big data challenges. The NGCC integrates big data platforms and traditional supercomputing technologies with software-defined networking, high-speed interconnects and visualization for medical research.”
Arizona’s NGCC provides the essence of the article’s claims, stressing capacity with Internet2, several types of computing, and of course collaboration between everyone at work on the system. Feltus commented on the importance of cooperation in Arizona State’s work, suggesting that personal relationships outweigh individual successes. He claims his own teamwork with network and storage researchers helped him find new potential avenues of innovation that might not have occurred to him without thoughtful collaboration.
Chelsea Kerwin, May 22, 2014
Stephen E Arnold, Publisher of CyberOSINT at www.xenky.com
The Elusive Video Recognition
April 22, 2015
Pictures and video still remain a challenge for companies like Google, Facebook, Apple, and more. These companies want to be able to have an algorithm pick up on the video or picture’s content without relying on tags or a description. The reasons are that tags are sometimes vague or downright incorrect about the content. VentureBeat reports that Google has invested a lot of funds and energy in a deep learning AI. The article is called “Watch Google’s Latest Deep Learning System Recognize Sports In YouTube Clips.”
The AI is park of a neural network that is constantly fed data and programmed to make predictions off the received content. Google’s researchers fed their AI consists of a convolutional neural network and it was tasked with watching sports videos to learn how to recognize objects and motions.
The researchers learned something and wrote a paper about it:
“ ‘We conclude by observing that although very different in concept, the max-pooling and the recurrent neural network methods perform similarly when using both images and optical flow,’ Google software engineers George Toderici and Sudheendra Vijayanarasimhan wrote in a blog post today on their work, which will be presented at the Computer Vision and Pattern Recognition conference in Boston in June.”
In short, Google is on its way to making video and images recognizable with neural networks. Can it tell the differences between colors, animals, people, gender, and activities yet?
Whitney Grace, April 22, 2015
Stephen E Arnold, Publisher of CyberOSINT at www.xenky.com
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