#Antivirus & Security Software
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shadowtechteller · 1 year ago
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Sweet Deception: Honey Traps & Hidden Backdoors in Cybersecurity
In the high-stakes game of digital espionage that unfurls within the pages of my novels, characters navigate a world rife with hacking, cyberattacks, and covert channels into supposedly secure systems. Beyond the adrenaline-amped fiction, these elements draw alarming parallels to our digital realities. Today, we'll unravel the tangled web of cybersecurity, focusing on the intriguing concepts of honey traps and backdoors—how they work, their purposes, both noble and nefarious, and the race to detect and defend against them.
### What’s a Honey Trap in Cybersecurity?
Think of a honey trap as the digital equivalent of a venus flytrap. In nature, these plants entice insects with their nectar, only to ensnare them. Cyber honey traps (or "honeypots") work similarly—they're decoy systems, networks, or pieces of information designed to seduce cybercriminals and hackers. They appear vulnerable and full of valuable data, drawing in attackers like moths to a flame.
#### Example:
Imagine creating a fake server loaded with false data files labeled "confidential." Hackers might target this server, only to waste their efforts on useless information while revealing their methods, origins, and even identities.
### Backdoors: The Secret Passages of Cybersecurity
On the other hand, "backdoors" are like hidden passages within a castle. They are secret — often malicious — ways to bypass normal authentication to access a system, application, or data.
#### How Are Backdoors Created?
- Intentional Backdoors:
- Example for Good: A developer might build a backdoor into a system for troubleshooting or remote support. Picture a safety deposit box with a locksmith's master key access.
- Example for Bad: A malicious insider creates a concealed entry point to tap into their employer's network later.
- Accidental Backdoors:
- Example: In the coding maze, a programmer inadvertently leaves weaknesses, like an unfinished tunnel, enabling savvy hackers to find and exploit these openings.
#### How Can Backdoors Be Used?
- For Good:
- Example: Tech support uses the backdoor to remotely assist a user with a software issue, entering through the digital "back door" and not the main "entrance."
- For Bad:
- Example: Hackers stealthily enter through the backdoor to steal sensitive information, akin to a thief slipping into a house through a secret passage, leaving no trace of forced entry. One day, you might find that confidential data—such as client information, proprietary blueprints, or personal photos—has evaporated. The culprit is long gone, having tiptoed through your digital 'back door'.
### Detection: The Cybersecurity Manhunt
Detecting honey traps is counter-intuitive; they are meant to be found by attackers. But the real work is in monitoring interactions with these traps. Security teams analyze traffic and logs to study how attackers behave, what techniques they use, and to improve defenses against real threats.
Detecting backdoors, however, is a complex challenge. It's a cybersecurity manhunt that requires constant vigilance and sophisticated tools.
#### Tools and Methods for Detection:
- Automated Scanning: Like a castle under constant surveillance, security programs scan software and systems for unfamiliar activity or known signs of a backdoor.
- Example: Antivirus software that warns you of suspicious software behavior, suggesting a possible backdoor.
- Code Auditing: Expert cybersecurity knights inspect the castle's blueprints (the code) for any secret passages (backdoors) inadvertently designed or nefariously placed.
- Example: A development team routinely reviews their product's source code before each release to ensure no hidden backdoors have been introduced.
- Anomaly Detection: Modern systems are trained to recognize normal patterns, much like how a guard knows the usual comings and goings within a palace. Anything out of the ordinary raises a flag.
- Example: An email server suddenly sending thousands of emails might indicate a backdoor has been used to compromise the system for spamming purposes.
### Conclusion: Cybersecurity as a Nexus of Intrigue and Innovation
These covert cyber tactics are not reserved for the shadows of fiction. They are in the trenches of an ongoing battle for digital safety. Honey traps and backdoors epitomize the double-edged sword of technology – they can be wielded for protection or wield misuse and havoc. As our lives intertwine with the digital world even more, understanding these concepts isn't just for tech aficionados; it's essential knowledge for anyone who clicks, taps, or swipes in the digital age.
In the next installment, we'll delve deeper into the battlefield of cybersecurity, exploring encryption, the locksmith art of the digital world, and digital certificates, our modern-day wax seals. Stay tuned, and stay secure in this digital odyssey. Your thoughts and experiences are just as crucial as the security measures we discuss. Whether you're a cybersecurity expert with tales from the digital front lines or a casual internet user with questions about staying safe online, your input helps shape the conversation and the community's awareness.
Share your insights in the comments, ask questions, or propose topics you're curious about. Let's engage in an ongoing dialogue that demystifies the tech world and empowers us all to build a more secure and informed digital future.
Remember, in the digital realm, awareness is the brightest beacon against the shadows of cyber threats. By understanding the dangers of honey traps and backdoors, we not only safeguard our personal data but also contribute to the broader fortress of global cybersecurity.
Together, let's continue our adventure through the ever-evolving narrative of technology, where each click can be both a potential risk and a step toward greater knowledge. Join me next time as we unlock more secrets of cybersecurity—because knowing is truly half the battle.
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unickwork · 3 years ago
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vilaspatelvlogs · 4 years ago
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avatheai · 4 years ago
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TECH 2 PROTECT
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Cybersecurity is becoming increasingly important, with a large number of users, devices, and programs within the modern organization, along with the deluge of data, which is increasingly sensitive or confidential. Attack volume and sophistication are escalating, which raises the stakes even more.
In this last blog post, we will tackle everything we need to know about Cybersecurity and on how important it is for everyone!
WHAT IS CYBER SECURITY?
Cyber security is a collection of technologies, procedures, and practices aimed at preventing attacks, damage, and illegal access to networks, devices, programs, and data. Information technology security is another term for cyber security.
ITS IMPORTANCE
Because government, military, business, financial, and medical institutions acquire, analyze, and store massive quantities of data on computers and other devices, cyber security is critical. Sensitive data, such as intellectual property, financial data, personal information, or other forms of data, might make up a large percentage of that data. Unauthorized access or exposure to that data can have serious repercussions. In the course of doing business, organizations transfer sensitive data over networks and to other devices, and cyber security refers to the discipline committed to securing that information and the technologies used to handle or store it.
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Five Types of Cyber Security for Organizational Safety
✎ Network Security - The process of defending a network against unauthorized users, assaults, and invasions.
Experts suggest the following methods for upgraded network security:
• Extra Logins
• New Passwords
• Antivirus programs
• Firewalls
• Incognito Mode
✎ Application Security - Apps must be updated and tested on a regular basis to guarantee that they are secure from cyber-attacks.
Some of the methods associated with application security are:
• Anti-virus Program
• Firewalls
• Encryption Programs
✎ Internet of Things Security - Internet of Things Security is the act of securing Internet of Things devices and the networks they’re connected to. In the business setting, IoT devices include industrial machines, smart energy grids, building automation, plus whatever personal IoT devices employees bring to work.
✎ Critical Infrastructure Security - Critical infrastructure security is the area of concern surrounding the protection of systems, networks and assets whose continuous operation is deemed necessary to ensure the security of a given nation, its economy, and the public’s health and/or safety.
✎ Cloud Security - Many files are stored in digital environments, sometimes known as "the cloud." Data protection in a completely online world offers several problems.
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Malware
- Malware, short for malicious software, is a catch-all word for viruses, worms, trojans, and other malicious computer programs used by hackers to cause havoc and get access to sensitive data.
Types of Malware
× Worms
× Viruses
× Bot & Botnets
× Trojan Horses
× Ransomware
× Adware & Scams
× Spyware
× Spam & Phishing
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That's pretty much everything you need to know about Cybersecurity! I hope this blog post (as well as my previous blogs) has been helpful :))
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References:
De Groot, Juliana (2020). What is Cyber Security?. Retrieved From: https://digitalguardian.com/blog/what-cyber-security
Fruhlinger, J. (2019). . What is IoT Security?. Retrieved From: https://www.fortinet.com/resources/cyberglossary/iot-security
Malware explained: How to prevent, detect and recover from it. Retrieved From: https://www.csoonline.com/article/3295877/what-is-malware-viruses-worms-trojans-and-beyond.html
Gillis, A. (2020). Internet of Things. Retrieved From: https://www.google.com.ph/amp/s/internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT%3famp=1
Topic Covered By: Rmon Alfred Bryant V. Santiago
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trainsinanime · 5 years ago
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Red Web Mystery Reviews
Red Web is a podcast by Rooster Teeth featuring two guys from that whole Achievement Hunter thing that I can never tell apart (but you don’t need to know anything about this) about unsolved mysteries that often but not always have something to do with the internet. Let’s review the episodes out so far, because… well, no reason, honestly, I just wanted to.
Lake City Quiet Pills
Based on their information presented here, this whole thing and their explanation for it seem plausible enough. You have to assume that this group of apparently assassins is kind of bad at operational security, but there’s actually a lot of cases where big criminals got exposed because they used the same URL or E-mail address or similar.
Satoshi Nakamoto
I already knew about this beforehand, and I would say they did a good job explaining it. Personally, I think they should have gone into a bit more of how much a shit-show the whole Newsweek Dorian Nakamoto thing was; in short, there was no reason to believe this person had anything to do with Bitcoin, he didn’t even speak good english (which is probably what caused some of the misunderstandings), and it was both a huge embarrassment for Newsweek (at least I hope they felt embarrassed) and they needlessly hounded a completely uninvolved person for this.
But then they get into new evidence, and we see a problem that I think is a bit systematic: They don’t really go into how trustworthy the evidence is. Specifically, they say that the one person who can cast light on this might be… John McAfee. Fucking John McAfee. Seriously, that guy?
For context: John McAfee did indeed create the antivirus company that still bears his name. But he sold it in the 1990s, and thanks to money and drugs, he’s just gotten plain crazy ever since. There was the whole thing where he was implicated in a murder in Belize a couple of years ago; he kept blogging from a jail in Guatemala, later returned to the US, and keeps being part of outlandish schemes (including two presidential runs, though he failed to get the nomination for libertarian candidate both 2016 and 2020), controversies, and supposedly super-awesome tech startups that never go anywhere. It makes perfect sense that he’d claim to be involved in the creation of Bitcoin. It makes no sense whatsoever to believe him. If you’re interested and have way too much time, read what El Reg has to say about him.
Mortis
Oh god. This one makes me both want to laugh and cry. Mostly laugh, to be honest, because it is such an obvious nothing burger, but also weep for the internet that was.
The story is that they found a participant in an early internet warez network who wasn’t that great at OpSec. This is only fully revealed at the end, and they don’t even seem to have noticed that this case is clearly and completely solved.
Most of the humour for me comes from the fact that they’re rediscovering the old pre-social web, and are convinced that it’s all weird and nefarious. Why would one person register websites for their interests, and then never do anything with them? Because that’s what the internet was like back then in the late 1990s and early 2000s! Hey, look, here’s my ugly special-interest website from that era that hasn’t been updated in years and isn’t going to be updated any time soon either. That’s just what was normal back then. Same with a website for every person, or trying to do your own garage sales via your website. That was the thing to do back then. And yes, obviously it sucked and didn’t work very well.
They even realise that this is what „might“ have been going on, and theorise about this hypothetical early web. „Maybe if there was some website that linked all these together and allowed you to search“ - yeah, those existed. Digg and Technorati and Del.icio.us, remember those? All bought by Yahoo and promptly forgotten. And to be fair, they never worked as well as real social networks did.
But back then we had this glorious freedom. No sudden porn bans like here on Tumblr; no need to match any predefined template for what posts are, no user tracking by Facebook, nobody telling you that you’re tagging your posts wrong…
It’s understandable why we lost that web. Linking together is much easier if all content is owned and controlled by like four companies. It also makes it much easier to set up a new account; setting up a new website is just a lot of pain and knowledge you have to have that you don’t necessarily want to have.
But now we live in our monocultures and must live with whatever content decisions our corporate overlords make and then sell us as „community standards“, and the wild and weird web that we used to have is only a memory. And sometimes not even that; sometimes these new young kids treat it as a „weird nefarious mystery“. Actually, I just looked it up, and Alfredo and Trevor are both around 30, just a few years younger than I am. They were alive for at least the tail end if this. These guys could have known this shit!
So, yeah, the story here is not the mystery; it’s a lament for the web we lost.
D.B. Cooper
Again one I already knew, and I think they gave a good overview. Personally I’m in the camp of people who assume that he failed to make a safe landing.
Happy Valley Dream Survey
This seems vaguely interesting. One thing that kind of annoys me about this podcast is that they (well mostly Alfredo) generally assume that everything strange is necessarily nefarious, without any evidence. The whole thing here leads nowhere, after all.
Lead Masks Case
Again, I’m not sure how much weight to put on the other evidence they listed, especially that whole supposed UFO sighting. Yes, that one woman may have been very respected in her community and/or had a high social status, whatever that means. But the thing is that rich people who are super-involved in their church community or whatever can still (through no fault of their own) be unreliable witnesses and invent things that weren’t there, or not the way they were described.
Cicada 3301 (parts 1 and 2)
Personally I find this one less interesting because it’s not a mystery, it’s a riddle, and that’s way less fun. Much of the circumstances are weird enough, I guess.
What confuses me the most about this is how it’s supposed to be a recruitment tool, but it doesn’t seem to be very good at that. A lot of the steps don’t really seem to be that difficult and require just some fairly standard hacker skills. This is similar to the Satashi Nakamoto case, where one hint was „knows C++ programming“. Lots of people know that, and it’s something you can totally teach yourself. And if the people who were recruited through this were really supposed to program software, well… why did no part of this test whether they could do so? That’s a whole different skill. My conclusion is that this Cicada group is either a long con or a group that is nowhere near as smart as it thinks it is.
One thing to note here: They just casually assume that the FBI and NSA and so on are monitoring the whole internet, in real time, all the time. Which is true, we know that thanks to Edward Snowden. Isn’t that much more nefarious than any of the other mysteries here put together? How did we get to a place where Americans both think „this is the country that has all the freedom“ and „if you say or search for the wrong things you’ll get put on a government watchlist that’s just normal“ at the same time? Pervasive monitoring of a population is pretty much the exact opposite of freedom, but apparently we all in the western world just take it in stride anyway. That’s nothing to do with this podcast, though.
Conclusion
Generally okay podcast. The hosts are good storytellers, even if the stories are sometimes a bit shaky. It is at least at no point overly gross or insultingly stupid (unlike the official Rooster Teeth Podcast, which is both). So I think I can recommend it if you need something, anything to fill the quiet, and you’re already out of episodes of Black Box Down.
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reportsandmarkets · 8 years ago
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New study: Antivirus & Security Software Depth Research Report 2017-2022
New study: Antivirus & Security Software Depth Research Report 2017-2022
Source: New study: Antivirus & Security Software Depth Research Report 2017-2022 Antivirus & Security Software Depth Market Report   Read Detailed Market Report @https://www.reportsandmarkets.com/reports/global-and-united-states-antivirus-security-2017-2022-1476270   This report splits Antivirus & Security Software by Price, and Function. This shares the history data information from 2012 to…
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we-antivirusassistant · 5 years ago
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rlxtechoff · 3 years ago
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huntersharing507 · 4 years ago
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unickwork · 3 years ago
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Trend Micro Antivirus+, 1 User [Digital] [PC Download]
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shivani111blog · 4 years ago
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Machine Learning Market Research Report - Global Forecast to 2024
Machine Learning Market Research Report - Global Forecast to 2024
 Market Snapshot
The Global Machine Learning Market is expected to expand at 42.08% CAGR during the forecast period 2018–2024.  
Machine learning is a part of artificial intelligence (AI) that grants computers the capability to learn without being programmed in detail. It mainly focuses on the advancement of computers programs that can be switched when exposed to new data. It helps the computer to analyze and derive hidden insights without being explicitly programmed for the same. It has multiple uses in today’s technology market concerning safety and security such as face detection, face recognition, image classification, speech recognition, antivirus, Google, antispam, genetic, signal diagnosing, and weather forecast.
The demand for machine learning is attributed to the growing adoption of cloud-based services, increase in unstructured data leads to the increasing demand for machine learning solutions. Cloud-based services offer increased scalability and security, which has made them more suitable to be used by businesses of all sizes. This growth in the adoption of cloud-based services has positively impacted the global machine learning market. Companies such as Amazon, Google, and Microsoft have invested heavily in the development of machine learning and AI. Cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform have started offering machine learning and deep learning-based services, which have encouraged the development of machine learning models. However, lack of technical expertise is expected to hinder the machine learning market growth.
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Key Developments  
April 2019, Google launched the Google     AI Platform. The platform allows machine learning professionals to build     and run their machine learning models on-premise as well as on Google     cloud. The platform is also integrated with machine learning suite offered     by Google including TensorFlow, TPUs, and TFX tools.
December 2018, Microsoft launched Azure Machine Learning services. These     services contain advanced capabilities which are designed to simplify the     process of building, training, and deploying machine learning models.     Furthermore, the support for open-source frameworks such as PyTorch,     TensorFlow, and scikit-learn offers flexibility to the data scientists to     use the tools of their choice. The automated machine learning solution     enables new or experienced data scientists to identify suitable algorithms     and hyperparameters faster.
November 2017, AWS released AWS DeepLens, deep learning-enabled wireless video     camera which offers developers hands-on experience with machine learning.     AWS DeepLens integrated with Amazon SageMaker helps the developers to     train their machine learning models over the cloud and deploy them on the     DeepLens, which runs the models in real-time on the camera.
August 2018, Intel acquired Vertex.ai,     an AI model suite development start-up. The acquisition helped Intel to     gain a team with high technical experience in deep learning technology and     expand its product portfolio.
  Market Segmentation
By     Component—Hardware, Software and Services
By Organization     Size—Large Enterprises, and Small & Medium Sized Enterprises.
By     Vertical—BFSI, Media & Entertainment, Automotive, Telecommunication,     Retail & Ecommerce, Education, Healthcare, Government & Defense,     and Others.
 The machine learning market, by region, has been segmented into North America, Europe, Asia-Pacific, the Middle East & Africa, and South America. North America accounted for the largest market share of 44.05% in 2017, with a market value of USD 1255.34 million; the market is expected to register a CAGR of 40.44% during the forecast period. Europe was the second-largest market in 2017, valued at USD 816.68 million; the market is expected to register a CAGR of 44.87%.
The large-scale adoption of big data in various sectors such as automotive, financial services, industrial, IT & telecommunications, energy, healthcare, consumer electronics, transportation & logistics, and research and development propel the market growth of machine learning software and solutions in North America.
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At Market Research Future (MRFR), we enable our customers to unravel the complexity of various industries through our Cooked Research Report (CRR),Half-Cooked Research Reports (HCRR), Raw Research Reports (3R),Continuous-Feed Research (CFR), and Market Research & Consulting Services.
Contact:    
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Magarpatta Road, Hadapsar
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Maharashtra, India
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unickwork · 3 years ago
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