Altexsoft

JUNE 2, 2020

What Is Machine Learning and How Is it Used in Cybersecurity? Machine learning (ML) is the brain of the AI—a type of algorithm that enables computers to analyze data, learn from past experiences, and make decisions, in a way that resembles human behavior. Some can even automatically respond to threats.

Artificial Inteligence 93

Artificial Inteligence Examples Applications Machine Learning 93

Ivanti

JANUARY 19, 2022

Not only has The Everywhere Workplace extended the cyber risk and threat landscape—especially for data privacy and its protection—but a lot of Agile software developers, many of whom lack any DevSecOps process, are publishing untested or poorly tested software that can be exploited as zero-days by criminal gangs. The most common?

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Artificial Inteligence Malware Artificial Intelligence Spyware 92

Palo Alto Networks

JUNE 29, 2020

Threat hunting requires skills ranging from threat intelligence analysis, malware analysis, penetration testing, data science, machine learning and business analysis, plus knowledge of all the systems and data in place at the organization. Structured hunting should be process-driven but follow an agile methodology.

How To 97

How To Malware Exercises Systems Review 97

Palo Alto Networks

APRIL 26, 2021

Reactive security : Legacy network security solutions still rely on a signature-based approach that requires security analysts to hunt down zero-day attacks in retrospect, rather than placing machine learning (ML) inline for realtime prevention. The latest numbers from Google show that up to 98% of this traffic is being encrypted.

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Network Cloud Data Center Malware 74

The Accidental Successful CIO

SEPTEMBER 13, 2023

The problem with these types of baits is that they allow security teams only to monitor and learn the behavior of bad actors once they attempt to move closer to high-value targets. CIOs have to realize that attackers are both agile and fast. The goal of solutions like this is to keep attackers out of your networks in the first place.

Firewall 52

Firewall Network Study Technology 52

Tenable

OCTOBER 27, 2023

Specifically, 36% of respondents said they haven’t yet used AI and machine learning for cybersecurity, but that they’re currently “seriously exploring” generative AI tools. Fifty-six percent are already working with AI and ML. The update process won’t be limited to the U.S. federal government.

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Artificial Inteligence Artificial Intelligence Technical Review Backup 64

Palo Alto Networks

APRIL 26, 2021

Reactive security : Legacy network security solutions still rely on a signature-based approach that requires security analysts to hunt down zero-day attacks in retrospect, rather than placing machine learning (ML) inline for realtime prevention. The latest numbers from Google show that up to 98% of this traffic is being encrypted.

Network 52

Network Cloud Data Center Malware 52

Palo Alto Networks

APRIL 23, 2020

Any truly complete approach to MDR should rely on technologies providing behavioural threat analysis, using techniques that include machine learning, artificial intelligence and human intelligence. Learn more about our Managed Threat Hunting service. Deploy multilayered prevention as a standard.

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Artificial Inteligence Artificial Intelligence Technical Review Machine Learning 55

CIO

MARCH 10, 2023

Automation, AI, and vocation Automation systems are everywhere—from the simple thermostats in our homes to hospital ventilators—and while automation and AI are not the same things, much has been integrated from AI and machine learning (ML) into security systems, enabling them to learn, sense, and stop cybersecurity threats automatically.

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Altexsoft

OCTOBER 24, 2022

Artificial intelligence (AI) and machine learning technologies enable CloudOps administrators to automate these tasks efficiently. Both CloudOps and DevOps are agile development methodologies. I hope this will be useful as you improve the agility of your cloud development efforts. CloudOps vs. DevOps.

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Organization Disaster Recovery DevOps Artificial Inteligence 40

O'Reilly Media - Ideas

JANUARY 25, 2024

Before that, cloud computing itself took off in roughly 2010 (AWS was founded in 2006); and Agile goes back to 2000 (the Agile Manifesto dates back to 2001, Extreme Programming to 1999). PyTorch, the Python library that has come to dominate programming in machine learning and AI, grew 25%.

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Trends Technical Review Technology Artificial Inteligence 120

Palo Alto Networks

AUGUST 18, 2021

With higher data speeds and latency improvements along with greater agility, efficiency and openness, secure 5G adoption will be a core driver of digital transformation. We also use network telemetry and machine learning to discover each IoT device on a 5G network and classify it by its purpose.

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Openxcell

MARCH 22, 2023

These technologies offer agility to boost healthcare organizations’ operational effectiveness and enhance patients’ overall experiences. Automated drug dispensing systems and machine learning algorithms that can spot anomalous medical data are two further examples of healthcare automation.

Healthcare 52

Healthcare Trends Technical Review VR 52

OTS Solutions

DECEMBER 5, 2019

If there is a missed update on a single computer, well, that’s all a hacker needs to initiate an attack of ransomware or malware. Virtual solutions save time, energy, and deliver results with agility. Virtual reality, augmented reality and machine learning are growing too. Therefore, both must do their part.

Enterprise 42

Enterprise Cloud Data Center Virtualization 42

Palo Alto Networks

NOVEMBER 13, 2019

This all means that you don’t have to be an exclusive Palo Alto Networks shop to take advantage of Cortex XDR’s powerful data-stitching, machine learning and simplified investigation capabilities across your entire network. In addition to firewall logs, Cortex XDR 2.0 A Unified User Interface for Endpoint Protection and XDR.

Firewall 13

Firewall Malware Artificial Inteligence Machine Learning 13

Existek

OCTOBER 7, 2021

Probably the most obvious thing is replacing a whole department of consultants with chatbots built with artificial intelligence and machine learning. There are many development methodologies, like Waterfall, V-shaped, Spiral, but we work with the Agile approach. Curious to know more about methodologies?

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Fintech Development UI/UX Artificial Inteligence 52

O'Reilly Media - Ideas

NOVEMBER 7, 2023

Graphs are becoming increasingly important in data mining and machine learning. The malware is disguised as a WordPress plugin that appears legitimate. While its agility is impressive, what sets it apart is the ability to plan actions to achieve a goal, taking into account the objects that it sees.

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Artificial Inteligence Trends Open Source Authentication 93

Codegiant

NOVEMBER 9, 2020

Ability to plan agile work from project backlog to sprints. User Review “ Perfect Solution for Product Management (Planning work and Tracking progress) ” Codegiant Codegiant is a very powerful and, at the same time, a simple, agile project development tool. Pros Real-time protection against malicious websites and malware.

Software Review 64

Software Review Tools Weak Development Team Development 64

Codegiant

NOVEMBER 9, 2020

Ability to plan agile work from project backlog to sprints. User Review “ Perfect Solution for Product Management (Planning work and Tracking progress) ” Codegiant Codegiant is a very powerful and, at the same time, a simple, agile project development tool. Pros Real-time protection against malicious websites and malware.

Software Review 52

Software Review Weak Development Team Tools Development 52

O'Reilly Media - Ideas

SEPTEMBER 6, 2022

Bruce Schneier on cryptographic agility : We need the ability to swap in cryptographic algorithms quickly, in light of the possibility that quantum computers will soon be able to break current codes. SHARPEXT is malware that installs a browser extension on Chrome or Edge that allows an attacker to read gmail.

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Artificial Inteligence Trends Blockchain Software Review 113