TechCrunch

SEPTEMBER 27, 2021

Mobile spyware is one of the most invasive and targeted kinds of unregulated surveillance, since it can be used to track where you go, who you see and what you talk about. And because of its stealthy nature, mobile spyware can be nearly impossible to detect. “We already know applications that are spyware.

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Ivanti

JANUARY 19, 2022

Ransomware, on the other hand, was responsible for most data breaches caused by malware. machine learning artificial intelligence (AI),?automation, against known and zero-day vulnerabilities, zero-click exploit kits developed by the NSO Group, fileless malware and the adoption of the “as-a-service” business model.

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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. Analyze mobile endpoints.

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Ivanti

SEPTEMBER 9, 2021

Within the initial blog in this series , we discussed ransomware attacks and their remediation on Android mobile devices. Part 2 addresses potential ransomware exploits and their remediation on iOS, iPadOS mobile devices and macOS desktops. Victims would then be coerced to pay money to remove the malware from their devices or laptops.

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Lacework

JANUARY 25, 2023

Whether you’re facing a sophisticated phishing attack or a form of never-before-seen malware (also known as an “unknown threat” or “unknown unknown”), threat detection and response solutions can help you find, address, and remediate the security issues in your environment. If not detected, malware can cause downtime and security breaches.

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Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

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O'Reilly Media - Ideas

AUGUST 2, 2021

There’s a new technique for protecting natural language systems from attack by misinformation and malware bots: using honeypots to capture attackers’ key phrases proactively, and incorporate defenses into the training process. That applies to data and machine learning, too, and is part of incorporating ML into production processes.

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