10 Cyber Attacks Machine Learning Can Help Prevent

@machinelearnbot

Not even Cersei Lannister's scheming or Sir Jorah's father-like protectiveness could have prevented attackers from breaching HBO's network and stealing 1.5 terabytes of data (including unreleased Game of Thrones episodes). Machine learning, however, may have offered a more sound defense of HBO's virtual fortress. Artificial intelligence (AI) and machine learning (ML) are the topics of much debate, especially within the cybersecurity community. Is machine learning the next big security frontier? Is AI ready to take on machine learning-driven attacks?


Predictive analytics can stop ransomware dead in its tracks

#artificialintelligence

This past February marks the two-year anniversary when Livingston County, Michigan, was hit by ransomware. The wealthiest county in the state had three years' worth of tax information possibly at the mercy of cybercriminals. As a local government, county CIO Rich C. Malewicz said they have been a target of ransomware, but in this instance they had backups at the ready. He said the most memorable ransomware attack was a result of a watering hole campaign using malvertizing to infect users visiting a local news website. "This attack was very clever in that all you had to do to get infected was visit the website, you didn't even have to click on the page.


How data science fights modern insider threats

#artificialintelligence

Ben Dickson is a software engineer and freelance writer. He writes regularly on business, technology and politics. Insider threats are the biggest cybersecurity threats to firms, organizations and government agencies. This is something you hear a lot at security conference keynotes and read about in data breach reports, white papers and surveys -- and these insider threats are becoming increasingly more difficult to detect and prevent, as well as more frequent. This seemingly unstoppable growth accentuates the problem and shortcomings of current solutions, and warrants the need for new defensive technologies to detect and stop the digital daggers aimed at our backs.


How data science fights modern insider threats

#artificialintelligence

Ben Dickson is a software engineer and the founder of TechTalks. Insider threats are the biggest cybersecurity threats to firms, organizations and government agencies. This is something you hear a lot at security conference keynotes and read about in data breach reports, white papers and surveys -- and these insider threats are becoming increasingly more difficult to detect and prevent, as well as more frequent. This seemingly unstoppable growth accentuates the problem and shortcomings of current solutions, and warrants the need for new defensive technologies to detect and stop the digital daggers aimed at our backs. Data science -- the application of mathematics, big data analytics and machine learning to extract knowledge and detect patterns -- is an emergent, advanced technology area that is proving its effectiveness in the realm of cybersecurity, including fighting insider threats.


Experts predict 2017's biggest cybersecurity threats - TechRepublic

#artificialintelligence

If 2016 was the year hacking went mainstream, 2017 will be the year hackers innovate, said Adam Meyer, chief security strategist at SurfWatch Labs. Meyer analyzes large and diverse piles of data to help companies identify emerging cyber-threat trends. "2017 will be the year of increasingly creative [hacks]," he said. In the past, cybersecurity was considered the realm of IT departments, Meyer explained, but no longer. As smart companies systematically integrate security into their systems, the culture hackers too will evolve.