Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Deploying machine learning models in the cyber security industry is complicated - especially with budget and technology limitations. Especially when it comes to anomaly detection, there's been much debate over privacy, balance, budget, robustness, cloud security and reliable implementation. For cyber security companies using machine learning technologies, ensuring clients' safety with trustworthy artificial intelligence (AI) must always be the primary objective.

As we enter into 2023, cybersecurity must be at the forefront of our minds. With hackers becoming increasingly sophisticated in their techniques and the number of endpoints growing exponentially due to the explosion in the number of connected devices, it is critical that over the next 12 months we consolidate our efforts to stay one step ahead of the threats.

Cloud computing has transformed the software industry in recent years. From productivity applications to communications, business intelligence, and CRM systems, cloud-based systems have come to dominate the market. Indeed, Gartner predicts that by 2025, almost two-thirds of enterprise spending on application software will be directed at cloud-based technology.

Financial Services are valuable targets for cybercriminals. As the guardians of our financial information, banks hold a wealth of data that can be used to steal identities and commit other fraud. In this blog post, we'll take a look at the steps banks are taking to protect their customers from financial cybersecurity threats, and see.

Anat Kleinmann, AlgoSec's Sr. Product Manager and IaC expert, discusses how incorporating Infrastructure-as-Code into DevSecOps can allow teams to take a preventive approach to secure application connectivity.

Everyone loves automation, and it can be easy to assume that the more you automate, the better. Indeed, falling short of achieving fully autonomous processes can feel like a defeat. If you don't automate completely, you're the one falling behind, right? Well, not exactly. Although automation is, in general, a good thing, there is such a thing as too much automation. And blindly striving to automate everything under the sun is not necessarily the best strategy. Instead, you should be strategic about what you do and don't automate.

If we were to ask a bunch of people to choose a computer, they would most likely go with a Windows or Mac machine. The possibility of them choosing a Linux machine is slim. This is directly reflected in recent desktop adoption trends as well. Linux accounts for only 2.14% of all desktop operating systems (OSs) while its counterparts, Windows and Mac, occupy about 75.23% and 15.86% respectively.