Welcome to our weekly roundup, where we share what you need to know about the cybersecurity news and events that happened over the past few days. This week, learn about an infectious miner-malware and how malware can hide form AV Solutions. Also, understand how to use machine learning to detect malware outbreaks with limited samples.
Current and potential users of the latest edition of Trend Micro Antivirus for Mac will be pleased to know that it achieved MacOS Certification and top scores in all three categories in the recent report.
UK lawmakers have accused Facebook of violating data privacy and competition laws in a report on social media disinformation that also says CEO Mark Zuckerberg showed “contempt” toward parliament by not appearing before them.
This combination becomes a concern for data exfiltration of enterprise assets and information because of the randomly named and seemingly-valid Windows functions that may go undetected.
Australia’s major political parties have been targeted during a cyberattack by a foreign government on the Australian Parliament’s servers, but Prime Minister Scott Morrison said investigations into the recent hack have yet to find any evidence of electoral interference.
Malware can hide from antivirus (AV) software by abusing features in Intel Software Guard Extensions (SGX), recently demonstrated by researchers at Graz University of Technology.
An independent report authored by the US Government Accountability Office (GAO) auditing agency has recommended that Congress develop internet data privacy legislation to enhance consumer protections, similar to the EU’s General Data Protection Regulation (GDPR), with the Federal Trade Commission (FTC) in charge of overseeing internet privacy enforcement.
Trend Micro and researches from the Federation University Australia conducted a study which showed the effectiveness of machine learning analyzing a malware outbreak given a small dataset.
Wendy’s has agreed to pay $50 million to settle negligence claims following its 2015-2016 data breach that affected more than 1,000 of the burger chain’s locations.
Are you surprised that you can use machine learning to detect malware outbreak with a small dataset? Why or why not? Share your thoughts in the comments below or follow me on Twitter to continue the conversation: @JonLClay.