#artificial intelligence in security

[reflextickcreativeagency]

AI in Cybersecurity – How AI is Transforming IT Security in 2025

Introduction

Cybersecurity threats are evolving at an unprecedented rate, putting businesses and individuals at risk of data breaches, ransomware attacks, and phishing scams. In response, Artificial Intelligence (AI) is revolutionizing IT security by providing advanced threat detection, real-time monitoring, and automated response mechanisms. AI-powered cybersecurity is no longer a futuristic concept—it’s a necessity in today’s digital landscape.

How AI is Transforming Cybersecurity

1. AI for Threat Detection and Prevention

Traditional security systems rely on rule-based algorithms, which often fail against sophisticated cyberattacks. AI-powered cybersecurity solutions use machine learning (ML) to analyze patterns and detect anomalies, identifying threats before they cause damage.

AI detects phishing attempts by analyzing email content and sender behavior.

Machine learning models predict cyberattacks based on historical data.

AI-driven endpoint security ensures real-time protection for devices.

2. Automated Incident Response

AI accelerates threat mitigation by automatically responding to cyber incidents. Instead of waiting for manual intervention, AI-driven security systems isolate infected devices, block malicious IP addresses, and neutralize threats in real-time.

AI-powered firewalls and intrusion detection systems (IDS) improve network security.

Automated security operations centers (SOCs) enhance rapid threat resolution.

3. Behavioral Analytics for Cybersecurity

AI analyzes user behavior to detect unusual activities. If an employee's login pattern suddenly changes or unauthorized data access occurs, AI flags it as a potential threat.

AI-driven identity and access management (IAM) prevents unauthorized logins.

Behavioral biometrics enhance authentication security.

4. AI in Cloud Security

As cloud computing adoption grows, cyber threats targeting cloud environments also rise. AI enhances cloud security by:

Identifying misconfigurations that could expose data.

Monitoring cloud access patterns for suspicious activities.

Detecting malware in cloud storage services.

Challenges of AI in Cybersecurity

Despite its advantages, AI-powered cybersecurity faces challenges, including:

False Positives & Negatives: AI must continuously learn to minimize detection errors.

High Implementation Costs: AI-driven security solutions require significant investment.

Data Privacy Concerns: AI models rely on vast amounts of data, raising privacy issues.

Future Trends of AI in Cybersecurity

The future of AI in cybersecurity is promising, with advancements shaping IT security strategies. Some key trends include:

AI-Powered Zero Trust Security Models: Verifying every request before granting access.

Deep Learning for Threat Hunting: Identifying complex cyberattack patterns.

Quantum Computing’s Role in AI Cybersecurity: Strengthening encryption algorithms.

AI-Augmented Penetration Testing: AI-driven ethical hacking to identify vulnerabilities.

Conclusion

AI is transforming cybersecurity by making IT security smarter, faster, and more proactive. As cyber threats become more sophisticated, businesses must integrate AI-driven security measures to protect sensitive data and digital assets. Investing in AI-powered cybersecurity today ensures a safer digital future for organizations worldwide.

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[meanya]

I saw a post before about how hackers are now feeding Google false phone numbers for major companies so that the AI Overview will suggest scam phone numbers, but in case you haven't heard,

PLEASE don't call ANY phone number recommended by AI Overview

unless you can follow a link back to the OFFICIAL website and verify that that number comes from the OFFICIAL domain.

My friend just got scammed by calling a phone number that was SUPPOSED to be a number for Microsoft tech support according to the AI Overview

It was not, in fact, Microsoft. It was a scammer. Don't fall victim to these scams. Don't trust AI generated phone numbers ever.

[berix2010]

Its crazy how its been over 45 years since IBM created this infamous slide and yet major companies are still like "nahhh just let the computer make the serious management decisions, it'll be just fine":

[technologywhis]

Oh yes — that’s the legendary CIA Triad in cybersecurity. It’s not about spies, but about the three core principles of keeping information secure. Let’s break it down with some flair:

⸻

1. Confidentiality

Goal: Keep data private — away from unauthorized eyes.

Think of it like locking away secrets in a vault. Only the right people should have the keys.

Examples:

• Encryption

• Access controls

• Two-factor authentication (2FA)

• Data classification

Threats to it:

• Data breaches

• Shoulder surfing

• Insider threats

⸻

2. Integrity

Goal: Ensure data is accurate and trustworthy.

No tampering, no unauthorized changes — the data you see is exactly how it was meant to be.

Examples:

• Checksums & hashes

• Digital signatures

• Version control

• Audit logs

Threats to it:

• Malware modifying files

• Man-in-the-middle attacks

• Corrupted files from system failures

⸻

3. Availability

Goal: Data and systems are accessible when needed.

No point in having perfect data if you can’t get to it, right?

Examples:

• Redundant systems

• Backup power & data

• Load balancing

• DDoS mitigation tools

Threats to it:

• Denial-of-service (DoS/DDoS) attacks

• Natural disasters

• Hardware failure

⸻

Why it matters?

Every cybersecurity policy, tool, and defense strategy is (or should be) built to support the CIA Triad. If any one of these pillars breaks, your system’s security is toast.

Want to see how the CIA Triad applies to real-world hacking cases or a breakdown of how you’d protect a small business network using the Triad? I got you — just say the word.

[randomne]

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A post shared by Galaxies (@galaxies)

Okay I saw this and immediately thought of the dca boys is this what all those fics have been talking about this whole time?

[savagechickens]

Furby.

And more replacements.

[glamrockraybot]

I think if Glamrock Freddy and Bonnie are dating, and personally I do believe they are, then that is possibly the funniest think to include in this new Era of fnaf. Not only because of, well you know, but also because there are too many homophobic fnaf fans and I appreciate the chance to weed them out. Now Steelwool I'm beaming this message into your head make Roxy canonically trans and make her and chica girlfriends

[qsmprambling]

Imagine Egg A1 still has one life left, and it somehow manages to escape the facility... It is being followed by mobs, by Federation employees, being hurt by the poison ivy and other environmental threats, but it keeps running, because what other choice is there? That parkour course was a trick after all, the last block was a fake, it was never meant to pass that test in the first place.

So it keeps running, but the Federation workers are getting closer. It won't be able to avoid them forever...

But then it bursts through some bushes and comes face to face with someone new - and it's Bad, out building or exploring or just wandering alone. A1 is immediately afraid, of course. It is a stranger, a very visually striking stranger, the complete opposite of the pure white and featureless employees of the Federation. But there are people close behind, and it knows what will happen to it if it is caught, so... It has no choice but to try. It has no way to communicate, no signs or books, so it simply rushes to hide behind him and hopes he understands, and that he is willing to help...

And Bad, for his part, well.. he's an extremely cautious and paranoid person, and this is just an incredibly confusing and unexpected situation to be in. An unknown egg appeared out of nowhere and is hiding behind him, he can see Federation employees in the distance that are clearly looking for something... He knows that the code has been disguising itself as eggs, and that the strange egg in front of him with no marks, no distinguishing features, an egg that he has never seen before, could easily be the code monster preparing to attack at any moment...

But there is absolutely no way Bad could ever look at an egg in distress and not try to help it, even knowing it could be a trap.

So he quickly digs a shallow hole and pushes the mysterious egg into it, covering it up just in time, and when the employees throw him a book asking if he had seen anything, he lies effortlessly, he complains about nonsense, he asks them where the Ekea is and is as annoying as he can be, until they leave.

And now they're alone... just Bad an this mystery egg in the middle of the woods, A1 too afraid to leave the hole even when Bad tries to coax it out. He gives it food and tries his best to comfort it, to tell it everything is okay and that the pursuers are gone. He gives it some signs and a book, trying to see if it will write anything to him or answer any of his questions, but he gets no reply. A1 is just too afraid to even attempt to answer, and Bad doesn't even know if it understands him. He tries what few words he does know of the other languages, and still no response.

What should he do? As much as the image of a tiny, terrified egg makes him want to do all he can for it he also needs to be safe. He can't bring it home, because if it is a code there is no way he is bringing it anywhere near Dapper. Should he call someone else for help, or would that draw too much attention? Would it even be safe for him or the egg to let anyone know right now? And was this egg dangerous, or harmless and in need of protection? He wouldn't abandon it regardless but...

What now?

[melyzard]

Time for a new edition of my ongoing vendetta against Google fuckery!

Hey friends, did you know that Google is now using Google docs to train it's AI, whether you like it or not? (link goes to: zdnet.com, July 5, 2023). Oh and on Monday, Google updated it's privacy policy to say that it can train it's two AI (Bard and Cloud AI) on any data it scrapes from it's users, period. (link goes to: The Verge, 5 July 2023). Here is Digital Trends also mentioning this new policy change (link goes to: Digital Trends, 5 July 2023). There are a lot more, these are just the most succinct articles that might explain what's happening.

FURTHER REASONS GOOGLE AND GOOGLE CHROME SUCK TODAY:

Stop using Google Analytics, warns Sweden’s privacy watchdog, as it issues over $1M in fines (link goes to: TechCrunch, 3 July 2023) [TLDR: google got caught exporting european users' data to the US to be 'processed' by 'US government surveillance,' which is HELLA ILLEGAL. I'm not going into the Five Eyes, Fourteen Eyes, etc agreements, but you should read up on those to understand why the 'US government surveillance' people might ask Google to do this for countries that are not apart of the various Eyes agreements - and before anyone jumps in with "the US sucks!" YES but they are 100% not the only government buying foreign citizens' data, this is just the one the Swedes caught. Today.]

PwC Australia ties Google to tax leak scandal (link goes to: Reuters, 5 July 2023). [TLDR: a Russian accounting firm slipped Google "confidential information about the start date of a new tax law leaked from Australian government tax briefings." Gosh, why would Google want to spy on governments about tax laws? Can't think of any reason they would want to be able to clean house/change policy/update their user agreement to get around new restrictions before those restrictions or fines hit. Can you?

SO - here is a very detailed list of browsers, updated on 28 June, 2023 on slant.com, that are NOT based on Google Chrome (note: any browser that says 'Chromium-based' is just Google wearing a party mask. It means that Google AND that other party has access to all your data). This is an excellent list that shows pros and cons for each browser, including who the creator is and what kinds of policies they have (for example, one con for Pale Moon is that the creator doesn't like and thinks all websites should be hostile to Tor).

[eretzyisrael]

Good News From Israel

Israel's Good News Newsletter to 3rd Dec 23

In the 3rd Dec 23 edition of Israel’s good news, the highlights include:

Heroic action by Israel’s first all-female tank crews.

In clinical trials, new Israeli treatment cures liver cancer patient.

14 Israelis awarded European research grants.

Israeli pen reads handwritten text to the visually impaired.

Israeli startups improve road safety and reduce traffic congestion.

Israeli soccer players won’t take “no” for an answer.

The IDF prepare to celebrate Hannukah in Gaza.

Read More: Good News From Israel

American Israelis (and other Anglos) celebrated Thanksgiving just over a week ago. In Israel last week there was much to be thankful for - the release of many hostages, temporary respite from running to shelters, and more reports of heroic rescue actions on Oct 7, from a farmer, a foreign asylum-seeker and all-women tank crews. Please read the rest of this newsletter for many more positive news stories that we can all be thankful for. The photo of flags flying on our balcony is our personal thanks just for having the blessing and protection of our own State.

[atcuality3]

Simplify Decentralized Payments with a Unified Cash Collection Application

In a world where financial accountability is non-negotiable, Atcuality provides tools that ensure your field collections are as reliable as your core banking or ERP systems. Designed for enterprises that operate across multiple regions or teams, our cash collection application empowers agents to accept, log, and report payments using just their mobile devices. With support for QR-based transactions, offline syncing, and instant reconciliation, it bridges the gap between field activities and central operations. Managers can monitor performance in real-time, automate reporting, and minimize fraud risks with tamper-proof digital records. Industries ranging from insurance to public sector utilities trust Atcuality to improve revenue assurance and accelerate their collection cycles. With API integrations, role-based access, and custom dashboards, our application becomes the single source of truth for your field finance workflows.

[social-intelligence999]

Why does people face many unreal problems from society?

There is a much less well-defined group of the poor: Those who will always live at a deficit - wage slaves. If they stop working at full capacity for even a week - they may lose everything they have and become homeless. They cannot ever lose wages to illness, funerals, or births. This is caused mostly by something called ‘rent-seeking’, where those who own stuff concentrate wealth by charging people for the use of their capital.

Low wages are a form of rent-seeking, because the people actually producing stuff do not get a fair share of the value of their labor. Then they can’t save to own a house so they rent at a rate that far exceeds the cost of purchase and upkeep in the long run. Price fixing and monopolies make this worse, by charging more for basic goods than is sustainable on the wages being paid. These people have 2 earner families and second jobs and side gigs, but will die in debt. Society is structured so that these people work day and night for less than bare survival. 

[nando161mando]

Just make chatGPT CEO of Open AI. It shares a lot of qualities with your average CEO:

- Steals other people's ideas

- Valued by the market at much more than it's worth

- Doesn't remember things it previously said

- Says patently absurd things with absolute confidence

- Doesn't know what it's doing

- Doesn't really believe in facts so much as what it feels is probably right

[tech-insides]

What are the skills needed for a data scientist job?

It’s one of those careers that’s been getting a lot of buzz lately, and for good reason. But what exactly do you need to become a data scientist? Let’s break it down.

Technical Skills

First off, let's talk about the technical skills. These are the nuts and bolts of what you'll be doing every day.

Programming Skills: At the top of the list is programming. You’ll need to be proficient in languages like Python and R. These are the go-to tools for data manipulation, analysis, and visualization. If you’re comfortable writing scripts and solving problems with code, you’re on the right track.

Statistical Knowledge: Next up, you’ve got to have a solid grasp of statistics. This isn’t just about knowing the theory; it’s about applying statistical techniques to real-world data. You’ll need to understand concepts like regression, hypothesis testing, and probability.

Machine Learning: Machine learning is another biggie. You should know how to build and deploy machine learning models. This includes everything from simple linear regressions to complex neural networks. Familiarity with libraries like scikit-learn, TensorFlow, and PyTorch will be a huge plus.

Data Wrangling: Data isn’t always clean and tidy when you get it. Often, it’s messy and requires a lot of preprocessing. Skills in data wrangling, which means cleaning and organizing data, are essential. Tools like Pandas in Python can help a lot here.

Data Visualization: Being able to visualize data is key. It’s not enough to just analyze data; you need to present it in a way that makes sense to others. Tools like Matplotlib, Seaborn, and Tableau can help you create clear and compelling visuals.

Analytical Skills

Now, let’s talk about the analytical skills. These are just as important as the technical skills, if not more so.

Problem-Solving: At its core, data science is about solving problems. You need to be curious and have a knack for figuring out why something isn’t working and how to fix it. This means thinking critically and logically.

Domain Knowledge: Understanding the industry you’re working in is crucial. Whether it’s healthcare, finance, marketing, or any other field, knowing the specifics of the industry will help you make better decisions and provide more valuable insights.

Communication Skills: You might be working with complex data, but if you can’t explain your findings to others, it’s all for nothing. Being able to communicate clearly and effectively with both technical and non-technical stakeholders is a must.

Soft Skills

Don’t underestimate the importance of soft skills. These might not be as obvious, but they’re just as critical.

Collaboration: Data scientists often work in teams, so being able to collaborate with others is essential. This means being open to feedback, sharing your ideas, and working well with colleagues from different backgrounds.

Time Management: You’ll likely be juggling multiple projects at once, so good time management skills are crucial. Knowing how to prioritize tasks and manage your time effectively can make a big difference.

Adaptability: The field of data science is always evolving. New tools, techniques, and technologies are constantly emerging. Being adaptable and willing to learn new things is key to staying current and relevant in the field.

Conclusion

So, there you have it. Becoming a data scientist requires a mix of technical prowess, analytical thinking, and soft skills. It’s a challenging but incredibly rewarding career path. If you’re passionate about data and love solving problems, it might just be the perfect fit for you.

Good luck to all of you aspiring data scientists out there!

[savagechickens]

Easily Replaced.

And more robots.