Collaborate Disseminate
As a professional penetration tester, there’s one thing that rarely if ever gets discussed. Is it that the common image of a hacker, the lone wolf pounding away on a keyboard in a dark room only taking breaks for caffeine and cold pizza and, of … Continue reading Team Pentesting – The Unspoken Reality of Career Ethical Hacking
How many times have you read marketing propaganda for information security products that includes slogans that sound like the following?
“Find out what’s lurking inside your system.”[1]
“With network security, if you’re n… Continue reading Cyber Security FUD – Fear and the Growth of the InfoSec Industry
Let us discuss what defines the profitability of bitcoin mining, what principles for mining speed adaptation were initially embedded into it, and why these principles can lead to the failure of the cryptocurrency in the long run. Continue reading Satoshi Bomb
In pursuit of a high cyberthreat detection rate, the some developers of cybersecurity solutions neglect the subject matter of false positives, and unfairly so. Regretfully, only then does the idea dawn on these developers that high-quality protection from cyberthreats involves not only prevention but also a low false-positive rate. Continue reading False Positives: Why Vendors Should Lower Their Rates and How We Achieved the Best Results
Recently WikiLeaks published a report that, among other things, claims to disclose tools and tactics employed by a state-sponsored organization to break into users’ computers and circumvent installed security solutions. The list of compromised security products includes dozens of vendors and relates to the whole cybersecurity industry. Continue reading The security is still secure
What would happen if we did the same thing that the respected AI experts did? We could come to agreements with other representatives in the cybersecurity area and create a joint project. Meet Rocket AV. Continue reading Rocket AI and the next generation of AV software
At Kaspersky Lab, machine learning can be found in a number of different areas, especially when dealing with the interesting task of spam detection. This particular task is in fact much more challenging than it appears to be at first glance. Continue reading Machine learning versus spam
AV-Comparatives simultaneously conducted two tests of cybersecurity products using one and the same methodology. What’s the difference between them and how to read the reports to see manipulation of figures and recognize biased marketing ‘next-gen’ rhetoric. Continue reading Lost in Translation, or the Peculiarities of Cybersecurity Tests
AV-Comparatives simultaneously conducted two tests of cybersecurity products using one and the same methodology. What’s the difference between them and how to read the reports to see manipulation of figures and recognize biased marketing ‘next-gen’ rhetoric. Continue reading Lost in Translation, or the Peculiarities of Cybersecurity Tests
Machine learning has long permeated all areas of human activity. I would like to warn about, or dispel, some of the misconceptions associated with the use of ML in the field of cybersecurity. Continue reading Five myths about machine learning in cybersecurity