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The Challenge of Bias in AI – Creating Ethical Guidelines

Thales Cloud Protection & Licensing

Acknowledging that need, this blog post will explain the challenge of taking steps to eliminate bias in AI using ethics. Artificial intelligence (AI) is becoming increasingly integral to information security. All of the findings presented above assume that organizations can implicitly trust the results of their AI-powered security solutions.

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Shaping the Future of AI and Cybersecurity

NetSpi Executives

Chief Information Security Officer Shrav Mehta, Secureframe CEO How do you envision AI enabling the cybersecurity industry? Across industries, we envision AI enabling: Process Optimization: AI can analyze vast amounts of data in real-time, identifying patterns, trends, and anomalies that humans might miss. Systems, Inc.

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10 Personal Finance Lessons for Technology Professionals

Troy Hunt

When you boil it down, what do those three things have in common? This is part of the opening monologue of the Ozark series and when I first heard it, I immediately stopped the show and dropped it into this blog post. I want to start here because this post is very specifically targeted at people working in the same industry as I do.

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The Hacker Mind Podcast: Reverse Engineering Smart Meters

ForAllSecure

And yet, everything we do requires electricity, either AC through the wire or DC in the form of a battery when it's gone. And so I didn't have anything to do with LIDAR before that. I thought I could do this like I could buy it. He joins The Hacker Mind to talk about his journey, about mesh networks, and even glitching.

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What a False Negative is and why it should be your primary criteria for a SAST tool

Security Boulevard

This blog is about a term that is not as popular as False Positive, but is the reason security companies like ShiftLeft exist. It is so central to security that experts take it for granted, but new-comers might miss it due to vendor’s focus on False Positives. False Negative ?—?Incorrectly bandit/injection_shell.py

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Learning Machine Learning Part 1: Introduction and Revoke-Obfuscation

Security Boulevard

At this point I feel like I have a decent enough grasp to start publishing some models and blog posts on the subject. They also have a great writeup on their data science approach in the repo , which is as follows: Prepare a PowerShell Corpus. Obligatory meme. This post from Joost Jansen was also an inspiration for this subject area.

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Game Theory: Why System Security Is Like Poker, Not Chess

ForAllSecure

Or is it the reverse, where the best thing to do is invest in offense? It can be tricky to do informally, what we need are decision and strategy making frameworks. You can model probabilities on how someone else will take action and what you’ll do to counter that action. How do we think through what to do?