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DarkCyber for July 10, 2018, Now Available

This week’s DarkCyber story line up includes… Brave browser introduces Tor tabs… facial recognition accuracy … MalTrail for identifying malicious network traffic… and a list of malware and distribution points.


Louisville, KY, USA – WEBWIRE
CyberOSINT provides an overview of the features and functions of next generation information access systems, tools, and software.
CyberOSINT provides an overview of the features and functions of next generation information access systems, tools, and software.

Stephen E Arnold, author of Dark Web Notebook, said: “Facial recognition systems generate false positives. This means that unless the system generates a high probability match, human investigators and analysts have to examine the matched images. With accuracy rates for the best systems achieving 70 percent, facial recognition is a work in progress.”

DarkCyber for July 10, 2018, is now available at www.arnoldit.com/wordpress and on Vimeo at https://vimeo.com/278891411.

Stephen E Arnold’s DarkCyber is a weekly video news and analysis program about the Dark Web and lesser known Internet services.

This week’s program covers four Dark Web and security related stories.

The first story reports that Brave has introduced Tor tabs. The security-centric browser makes obfuscated Internet access easier to implement. The system is activated with a mouse click. Users do not have to download, install, and configure the Tor software bundle. DarkCyber reveals how to get a beta copy of this Tor-equipped browser.

Second, facial recognition systems captured some space in the news cycle. The Annapolis police were able to identify the Capital Gazette shooter using a commercial facial recognition system. The accuracy of these systems is not usually discussed. DarkCyber reveals the accuracy achieved by systems from Chinese, Russian, and US vendors.

Stephen E Arnold, author of Dark Web Notebook, said: “Facial recognition systems generate false positives. This means that unless the system generates a high probability match, human investigators and analysts have to examine the matched images. With accuracy rates for the best systems achieving 70 percent, facial recognition is a work in progress.”

The third story explains how a person with python and network expertise can configure MalTrail to identify malicious network traffic. The open source solution makes it possible to avoid the costs and contractual work associated with commercial malicious traffic analysis systems. DarkCyber points out the important differences between commercial software and the open source equivalent.

The fourth story points to a free report from the security organization InfoSec. The document includes useful information about weaknesses identified in Tor botnets and sources of malicious software. DarkCyber provides the download information for this free report and recommends that those interested in malware obtain a copy.

About Stephen E Arnold

Stephen E Arnold is the author of “Dark Web Notebook” and “CyberOSINT: Next Generation Information Access.” This book describes some of the technologies used by GSR and Cambridge Analytica to acquire and analyze Facebook user data. He has been named as a technology adviser to the UK based Judicial Commission of Inquiry into Human Trafficking and Child Sex Abuse.” Mr. Arnold also lectures to law enforcement and intelligence professionals attending the Telestrategies ISS conferences in Prague, Washington, DC, and Panama City, Panama. In recent months, he has shared his research with law enforcement and intelligence professionals in the US and Europe. His most recent lectures focus on deanonymizing chat and digital currency transactions. One hour and full day programs are available via webinars and on-site presentations. He publishes the free Web log “Beyond Search,” which is available at www.arnoldit.com/wordpress.

 


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 Stephen E Arnold
 Dark Web
 malware
 facial recognition
 Tor


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