The recent discovery of a backdoor in XZ Utils, a widely used Linux tool, raises concerns about the security of the open-source ecosystem. While the open-source community successfully reacted to remove the malware, this event highlights the presence ...
The value of OSS is undeniable. OSS offers organisations greater flexibility and cost savings. However, it needs to be understood that no software is completely bullet proof and OSS shares the same inherent risks as traditional software.
Adopting open-source software and technology has the potential to improve an organizations' security posture if this technology is properly monitored and maintained. A new report from Synopsys indicates that many organizations are falling down on the job, resulting in serious security issues.
Linux has managed to build a reputation around being one of the most secure operating systems available today. But too many people tend to take its built-in security for granted.
Open-source software isn’t a completely chaotic and breached wasteland of vulnerabilities. It’s a global effort to make the development lifecycle faster.
SaaS and PaaS have become part of the everyday tech lexicon since emerging as delivery models, shifting how enterprises purchase and implement technology. A new “_” as a service model is aspiring to become just as widely adopted based on its potential to drive business outcomes with unmatched efficiency: Artificial intelligence as a service (AIaaS). The emergence of AIaaS will play a critical role in AI adoption.
Machine learning has been trotted out as a trend to watch for many years now. But there’s good reason to talk about it in the context of 2020. And that’s thanks to developments like TensorFlow.js: an end-to-end open source machine learning library that is capable of, among other features, running pre-trained AI directly in a web browser. Learn how true web machine learning is expected to foster AI creativity in an interesting The Next Web article:
So much of the discussion about cybersecurity's relationship with artificial intelligence and machine learning (AI/ML) revolves around how AI and ML can improve security product functionality. However, that is actually only one dimension of a much broader collision between cybersecurity and AI. Learn about the new risks and threats posed by increased use of artificial intelligence:
This was the year when, once and for all, it became clear that the future of technology belongs to Linux and open-source software. Get the details in an interesting ZDNet article:
Did you know that Linux is the least targeted OS by malicious ads, accounting for only 0.3% of all malicious ads recorded in a recent study? Most malvertising campaigns (malicious ads) target Windows users,according to statisticsshared last week by cyber-security firm Devcon.Chrome OS is the second most targeted, while Linux is the least. Learn more:
Everything about IT has changed, but our security measures are still built around how we used to design software and systems. Where does security need to catch up with digital transformation - and how? Learn more:
Social engineering is the art of exploiting human psychology, rather than technical hacking techniques, to gain access to buildings, systems or data. Learn how to spot the signs in a great CSO article:
Does your company utilize AI or ML? Artificial intelligence and machine learning bring new vulnerabilities along with their benefits. Learn how several companies have minimized their risk in this informative CSO article:
