When organizations implement Zero Trust and SASE cybersecurity frameworks, the top priority is ensuring those connecting to the network are authenticated with appropriate access privileges. Users often represent the most fertile attack surface as they can go rogue or be phished, inadvertently sharing sensitive information with malicious actors that can cost a business dearly.
Meanwhile, organizations also must manage the flood of “things” entering the network, as in the Internet of Things (IoT). Sure, a wireless thermostat or smart speaker can’t be phished like a person, but each device represents another node that further expands the attack surface area, an area expanding at an exponential rate. Thankfully, recent communication from NIST National Cybersecurity Center of Excellence (NCCoE) have helped to address this issue.
To summarize the findings, network and security teams face significant obstacles in securing IoT devices on the network. Dealing with IoT devices is just as complicated, if not more so, than managing users when tasked with safely and securely onboarding those devices onto the network while also monitoring them for optimal performance and protection.
Network Layer Onboarding and Lifecycle Management 
NIST highlights in its project description how IoT security is difficult for myriad reasons:

• Manufacturers often provide a single set of log-on credentials for the millions of devices these organizations produce. Although sharing the same network credential for every device is often simple, this system lacks the ability to identify each device, nor is there a method to verify each device is connecting to the appropriate network.
• In contrast, manually provisioning a unique network credential for each device drastically increases the complexity of the on-boarding process, let alone that such approaches are resource intensive, error-prone, and insecure.
• Going further, requiring manufacturers to assign a unique network credential to each device as part of the manufacturing process is impractical and inefficient while potentially raising the cost of production.

Continue reading: https://www.networkworld.com/article/3672188/a-secure-network-requires-addressing-iot-security-complexity.html

RALEIGH – We stand at a time when emerging technologies are enabling us to create a digital twin of the world that we live in, one with more accuracy than ever before, maintained up-to-date in real time, and with the ability to experience and interact with that digital simulation in immersive 3D.
Throughout human history, we have aspired to create and document versions of the world we live in.  From the earliest cave paintings, we rendered copies of our activities and the things around us.  As new technologies evolved, we documented our world with painting and sculpture and writing.  In more recent history, we captured our world with photographs and sound recordings and later with video.  And even more recently we create simulations with software.
This ability to document what was happening in the world, as well as to imagine the possibilities of what can happen, spawned massive industries.  Industry today starts by simulating what could be – then making it real.  Engineering and architecture use 3D software renderings in the creation of new products.  Manufacturing and construction rely heavily on drawings and diagrams as a foundation for new infrastructure.  Medical professionals capture imagery with x-ray and MRI to prescribe positive healthcare outcomes.  Banks and financial services simulate markets with software algorithms in the design of new products.
Every industry will be fundamentally different, as we move from the Information Economy into the Data Economy.  Manufacturers have long wanted to build an exact engineering model of their assembly lines, to optimize performance, and then to monitor every single variable to detect anomalies and prevent failures.  Distributors want the same for their supply chains.  Cities aspire to monitor, control and optimize traffic flow.  Farmers want to maximize yield from every plant in the field and everyone wants accurate weather prediction.
THE INTERNET OF THINGS (IOT) HAS BEEN THE PREAMBLE FOR THE DATA ECONOMY.
For the past decade, IoT sensors have been deployed in increasing quantities in our homes, cities and fields as we make everything “Smart”.  This proliferation of sensors lays a foundation for high resolution data capture that can be used to render an accurate digital simulation of the world we live in.  The high bandwidth and low latency of 5G connectivity assures that we can keep that digital copy up to date in real-time.  The power of cloud computing, and new edge cloud technology provides the processing power to visualize this digital version in the most realistic ways yet possible, through the use of augmented and virtual reality and holographics.
The Information Economy was powered by the Internet, and our user interface was a keyboard and a 2D screen.  The Data Economy will be powered by the Metaverse.  The Metaverse provides much more human-like interaction with voice and gesture interfaces and immersive 3D visuals.  The internet provided access to stored information.  The Metaverse will be continually powered with real-time data.
Continue reading: https://wraltechwire.com/2022/09/01/metaverse-is-coming-think-of-it-as-our-real-worlds-digital-twin-with-amazing-tech/

AI and IoT are cutting-edge technologies that will have a huge influence on all sectors of society and industry.
Since most organizations focus their efforts on developing their brand, software, or network, systems have the potential to revolutionize how firms function.
Furthermore, as organizations try to make sense of the massive volumes of data generated by smart devices, the possibility of AI is hastening IoT’s rapid adoption.
Corporations are aggressively investing in digitalization, but they are also infusing AI across their IoT projects, analyzing probable future IoT endeavors, and searching for methods to derive more value from existing IoT installations.
Furthermore, with the assistance of an AI development firm, organizations may minimize unanticipated outages, improve operational effectiveness, develop new products and services, and improve risk management.
Both ordinary people and specialists gain from the mix of these two streams. IoT is concerned with devices talking with one another via the internet, whereas AI is concerned with machines learning from large amounts of data. This blog will explain why IoT and AI must cohabit.
Unlike traditional technology, IoT and machine learning make operational forecasts 20x faster with heightened accuracy. 
Continue reading: https://medium.datadriveninvestor.com/ai-and-iot-how-do-artificial-intelligence-and-internet-of-things-act-together-66e16c9c38ce

Investors have poured billions of dollars into internet of things (IoT) companies in venture capital (VC) financing deals.
So what is IoT? It is an umbrella term for the ability to connect everyday physical objects with other devices over the internet, enabling them to send and receive data. Those everyday devices could be anything from fridges and watches to cars and toilets.
The technology is ubquitus in projects such as the Scottish government’s rollout of a remote transport system for rural roads maintenance.
“IoT is still a fairly new market – but one that has huge potential. It is subject to rapid growth and encompasses extremely diverse technologies,” reported system integration company Reply. “IoT has been labelled as the power behind the fourth Industrial revolution.”
It is hardly surprising, then, that investors are eagerly backing IoT ventures, just like they are injecting money into metaverse companies and fintech startups.
We have dug up the 10 biggest IoT VC funding deals, through looking at data from GlobalData’s Technology Intelligence Centre, to better understand this booming section of the tech industry.
Continue reading: https://www.verdict.co.uk/the-10-biggest-internet-of-things-funding-deals-so-far-in-2022/

These days almost every appliance that you have in your home has some kind of smart setting that allows you to connect it to the internet. Such features are useful because of the fact that this is the sort of thing that could potentially end up allowing you to access your appliances remotely, and that is why so many manufacturers are trying to hop onto the bandwagon with all things having been considered and taken into account. With 5G adoption finally becoming commonplace, we might see a massive growth spurt in the Internet of Things. This refers to the interconnected network of all of your smart appliances, and with all of that having been said and now out of the way it is important to note that this industry is set to double in size by 2026. It is estimated that there were around 2.1 billion connections to the internet of things in 2021, and this number is expected to grow to around 4.3 billion by 2026. The growth of the Internet of Things is closely linked to 5G adoption rates, and whenever a new region gets access to this high speed mobile internet it will most likely see an upsurge in devices that get connected to it. Unsurprisingly, the three regions that will be driving much of the growth in the IoT’s connections are Western Europe, China as well as North America.
Continue reading: https://www.digitalinformationworld.com/2022/08/the-internet-of-things-is-set-to-double.html

Given today’s technological advancements, photogrammetry seems new, but actually, it’s really old. The method of reconstructing measurements is rooted in principles of perspective and projective geometry practiced by artists like Leonardo da Vinci and formalized into a science by German mathematicians in the late 19th century. Yet the photogrammetry field is rapidly evolving through innovations in software and aerial photography.
What Is Photogrammetry?
Photogrammetry involves taking photos of an object or environment from different angles and using these images to generate reliable measurements. Professionals often depend on high-quality cameras to take photos, attaching them to an aerial craft, like a drone, or to a ground-based support system, like a tripod, or simply using a handheld camera.
WHAT IS PHOTOGRAMMETRY?
Photogrammetry is the science of reconstructing objects and environments in the physical world through photographs. The technique involves stitching together large collections of overlapping photographs to create topographical maps, meshes, and lifelike 2D and 3D digital models.
After taking photos from different locations, teams can gather enough visual data to inform drawings, topographical maps, meshes and lifelike 3D models. Advanced software tools have made the last option more prominent since professionals can leverage these technologies to create digital assets with pixel data gathered from photographs. The technique has become essential for various tasks, including surveying construction sites and flood zones, assessing crop health and exploring fossil sites.    
In January of 2021, at a clay mine near Golden, Colorado, Alena Iskanderova made a startling discovery: The tracks of an ancient relative of the crocodile — once preserved for some 100 million years — had been largely erased by erosion.
In the 11 years since paleontologist Martin Lockley, an associate curator at the University of Colorado Museum of Natural History and professor emeritus at the university, first documented the tracksite, the fossilized footprints left by the animal had lost much of their depth — from roughly 7 to 12 millimeters down to 3 to 4 millimeters, Iskanderova said.
That the effects of the elements could visibly diminish the tracks in such a short time points not only to their fragility in the face of climate change and other anthropogenic threats, Iskanderova said, but the importance of photogrammetry as a means of preserving the geologic record.
“Sometimes tracks are the only presence of animals in any paleoenvironment. So [photogrammetry] is very important for us to know what kind of animals were there,” she said. “The tracks also show us their behavior. Sometimes we can tell, for example, that there was a group of dinosaurs migrating from one point to another.”
Continue reading: https://builtin.com/software-engineering-perspectives/photogrammetry

62-year-old Vietnamese farmer Le Thanh Nguyen is one of the earliest farmers in Vietnam to adopt agricultural drones in rice production.
Le Thanh Nguyen grows rice in the Tam Nong District of the Dong Thap Province. Over the past 40 years, he has been farming in the traditional way. Recently however, the Vietnamese grower decided to use drones, spurred on by an ever-increasing labour shortage.
Labour issues
 
Le Thanh Nguyen grows rice in the Tam Nong District of the Dong Thap Province. He recently started using drones. – Photo: XAG
Like many other farmers, Le Thanh Nguyen used to have difficulties hiring workers for manual jobs. During the busy rice season, his workers were supposed to come in the early morning to sow seeds for his rice field, but very often they arrived at the late afternoon. By that time, the seeds had germinated, and the shoots were easily broken during spreading and therefore caused yield loss.
And when his workers did arrive on time, Le was often not satisfied with the results of seeding by hand or spreader. The seeding wasn’t done precise enough and as a result, the plant density was not optimal.
Continue reading: https://www.futurefarming.com/tech-in-focus/drones/vietnamese-farmer-adopts-drones-in-rice-farming/

The rise of the internet made the world feel like a smaller place. Economic globalization allows companies to source talent in all parts of the world, giving billions of people the opportunity to participate in a connected economy for the first time. The blockchain technology provides a global network for cheap and fast transfer of digital assets, built on top of the internet. Creating new ways to earn money and allowing people to be part of a global financial system, without needing a bank account. Are we witnessing the emergence of a new economy?
Global payments are being disrupted before our eyes
Today's banking system is built upon the Bretton Woods Agreement from 1944. In the post-war period, fast and reliable payments between the countries of the “western world” were a top priority. Following this idea, the Bretton Woods system of monetary management established the rules for commercial and financial relations among the United States, Canada, Western European countries, Australia, and Japan. It was a big improvement over the gold-backed monetary system, which was too slow and inefficient for sending money between continents. The fiat monetary system with the US-Dollar as a global reserve currency offered a much faster and cheaper way to send money and trade goods globally.
Nearly 80 years later, we find ourselves in a world, where an emerging work force wants to transact with one another, not just in Europe and northern America, but in all parts of the world. The Bretton Woods system was never designed to handle these kinds of payments, and it shows.
Sending payments should be as easy as sending a text message
Paying a developer in India from a German bank account is usually painful and expensive. An Indian bank does not offer IBAN wire transfers and with the SWIFT system there is a lot of paperwork to do. Payments take days to settle and cost $20 or more, plus a conversion fee that is proportional to the amount sent. The best practice is to use a third party payment system from one of the global fintechs and go through the lengthy KYC process. For payments of more than $1,000 oftentimes the amount gets frozen, and a questionnaire is sent to the recipient of the money. The recipient must justify, why he is getting paid this salary and ultimately relies on the mercy of the authorities to receive his hard-earned income.
Continue reading: https://www.forbes.com/sites/philippsandner/2022/08/31/three-ways-how-blockchain-technology-is-already-changing-the-lives-of-thousands-of-workers-in-emerging-countries/?sh=24237c424f3f

Advocates of Web3, a catch-all term widely used to incorporate concepts of decentralized networks, cryptocurrencies and other blockchain-powered applications, have a grand vision for the future of the Internet and global finance.
One thing that stands in the way: a lack of people to make it happen.
At the end of last year, when bitcoin and a handful of other cryptocurrencies reached their highest values, about 18,500 developers each month were contributing to open-source Web3 projects, according to a report published by crypto-focused investment firm Electric Capital.
That number is “at an all-time high and growing faster than ever”—with roughly 60% of Web3 developers entering the industry in 2021—writes Electric Capital partner Maria Shen, but it is a speck of the global total of software engineers, which stood at 31.1 million in the first quarter of 2022, according to developer analytics company SlashData.
Facebook, Amazon.com and Google—the largest companies of today’s internet, dubbed Web2 by cryptophiles,— have over 20,000 software developers each, according to various estimates. But they’re outnumbered by the staff at companies like JPMorgan and Citigroup, both of which say they employ over 30,000 on projects for their financial-services businesses.
Crypto insiders might shrug at this juxtaposition, replying “we are still early”–one of the industry’s favorite refrains–but some see this chasm as a major impediment to the realization of Web3’s promises.
“When Citigroup reportedly employs 30,000 developers, but there are only several thousand active monthly blockchain developers, this developer gap feels insurmountable,” says Jay McCarthy, cofounder and chief technology officer at blockchain development firm Reach.
"Blockchain has extreme potential, but if we don’t get more developers building out their dreams, that potential will never be realized," echoes Chris Swenor, CEO of Reach and McCarthy’s cofounder.
Continue reading: https://www.forbes.com/sites/ninabambysheva/2022/08/29/web3-growth-stymied-by-scarcity-of-programmers/?sh=10c5ab8b7fa4

Ever since its inception, the internet has been changing constantly. Right now, I think we are witnessing one of the biggest developments yet—the change from Web 2.0 to Web3. Web3 could solve structural problems for users and digital marketers. It could also open up new opportunities for businesses.
The Transition From Web 1.0 To Web3
It may sound unbelievable to some, but the internet is more than 30 years old. According to TechTarget, Web 1.0, the World Wide Web many of us know, was created in 1989 by Tim Berners-Lee. This first iteration of the internet enabled users to access websites and read or download information. To this day, many organizations are offering Web-1.0-type content.
In the early 2000s, the World Wide Web as we knew it went through its first major step change. Rather than being static, content became more interactive. Website users started generating their own content as opposed to simply consuming the information in front of them.
To acknowledge the change, TechTarget explains that Tim O’Reilly helped coin the term Web 2.0. Social media platforms like Facebook and Instagram are among the best-known representatives of Web 2.0 technology.
Web3 is the latest stage in these developments, and it is still evolving. The TechTarget article explains that the early forms of the internet were based on centralized databases that drove the delivery of content and applications, but Web3 could turn the tables.
Continue reading: 
https://www.forbes.com/sites/forbescommunicationscouncil/2022/08/30/entering-a-new-era-what-web3-could-mean-for-digital-marketers/?sh=7dffc0a56f5d

With 15 years of experience in the IT industry, Roberta Aquila works at Digitra.com as a Site Reliability Engineer (SRE). We sat down with Roberta to learn more about her role as well as her advice to people who are interested in getting involved in the crypto and technology space.
Can you tell us a little bit about yourself and your role at Digitra.com?
I have been working in the IT industry for over a decade but I had a passion for computers and technology as a child. In high school, I took IT classes so I could start working with software development at an early age. After gaining a technology foundation in high school, I went on to FIAP where I majored in Computer Engineering.
At Digitra.com I'm part of the SRE (Site Reliability Engineering) team, where I am responsible for automating our cloud infrastructure and keeping our systems healthy and reliable by applying modern techniques of monitoring and observability.
How did you become involved in the crypto space?
My first contact with crypto was about five years ago. I was working with my current manager at another company, and he was leaving to start a new opportunity at a crypto startup. I had already heard about it but I didn't go deeper into this subject because, at that time, I was not aware of how big crypto's world was becoming. Right after, I started working at a bank and got interested in investments and started to understand the cryptocurrency universe and its projection.
Continue reading: https://www.nasdaq.com/articles/women-in-technology%3A-roberta-aquila-it-specialist-digitra.com

Artificial Intelligence (AI) is transforming our way of life from new forms of social organization and scientific discovery to defense and intelligence. This explosive progress is especially apparent in the subfield of machine learning (ML), where AI systems learn autonomously by identifying patterns in large volumes of data.[1] Indeed, over the last five years, the fields of AI and ML have witnessed stunning advancements in computer vision (e.g., object recognition), speech recognition, and scientific discovery.[2], [3], [4], [5]  However, these advances are not without risk as transformative technologies are generally accompanied by a significant risk profile, with notable examples including the discovery of nuclear energy, the Internet, and synthetic biology. Experts are increasingly voicing concerns over AI risk from misuse by state and non-state actors, principally in the areas of cybersecurity and disinformation propagation. However, issues of control – for example, how advanced AI decision-making aligns with human goals – are not as prominent in the discussion of risk and could ultimately be equally or more dangerous than threats from nefarious actors. Modern ML systems are not programmed (as programming is typically understood), but rather independently developed strategies to complete objectives, which can be mis-specified, learned incorrectly, or executed in unexpected ways. This issue becomes more pronounced as AI becomes more ubiquitous and we become more reliant on AI decision-making. Thus, as AI is increasingly entwined through tightly coupled critical systems, the focus must expand beyond accidents and misuse to the autonomous decision processes themselves.
The principal mid- to long-term risks from AI systems fall into three broad categories: risks of misuse or accidents, structural risks, and misaligned objectives. The misuse or accident category includes things such as AI-enabled cyber-attacks with increased speed and effectiveness or the generation and distribution of disinformation at scale.[6] In critical infrastructures, AI accidents could manifest as system failures with potential secondary and tertiary effects across connected networks. A contemporary example of an AI accident is the New York Stock Exchange (NYSE) “Flash Crash” of 2010, which drove the market down 600 points in 5 minutes.[7] Such rapid and unexpected operations from algorithmic trading platforms will only increase in destructive potential as systems increase in complexity, interconnectedness, and autonomy.
The structural risks category is concerned with how AI technologies shape the social and geopolitical environment in which they are deployed. Important contemporary examples include the impact of social media content selection algorithms on political polarization or uncertainty in nuclear deterrence and the offense-to-defense balance.[8],[9]  For example, the integration of AI into critical systems, including peripheral processes (e.g., command and control, targeting, supply chain, and logistics), can degrade multilateral trust in deterrence.[10] Indeed, increasing autonomy in all links of the national defense chain, from decision support to offensive weapons deployment, compounds the uncertainty already under discussion with autonomous weapons.[11]
Continue reading: https://www.hstoday.us/featured/artificial-intelligence-critical-systems-and-the-control-problem/

Artificial intelligence is already affecting nearly every workplace in the country. Here's how the future of AI may shape the workplace of tomorrow.
When most people think of artificial intelligence (AI), they think of smarty-pants robots that can service our every whim. While real robots may be in the cards, the future of AI will also revolutionize the way we work (in real life and in the metaverse). In fact, AI is already in your workplace: You use AI when you use Google Maps to find your way to an off-site meeting (perhaps in a self-driving car?), or when you use spell-check for a report.
The current state of AI and the future of AI goes far beyond simplifying mundane tasks, however. Artificial intelligence, or computers that are taught to “think” like humans, can make us healthier, less stressed and happier through advancements in medicine, manufacturing and more. It’s not without its downsides, though. So let’s take a look at what the future of AI holds for the workplace, including some drawbacks and benefits you might see in your lifetime.
Examples of AI in the workplace today
Artificial intelligence is all around you. Applying for a job? There’s a good chance AI is screening resumes before they reach a human. Use a voice assistant on your phone to help you with workplace tasks? Alexa, Google Assistant and Siri all use AI to answer your questions and perform functions.
When you use Google or another search engine to look up information, you’re using AI. When your company car prevents you from swerving off the road when you’re drowsy, it uses AI.
Manufacturers use AI to find simpler and more affordable ways to produce better-quality products. AI can also review the history of manufacturing equipment to determine the best times to maintain the machinery.
In the medical industry, AI can find tumors with a better success rate than radiologists. It can also diagnose other illnesses and determine the best way to proceed with medical trials.
And though Web3, the next evolution of the internet, is in its infancy, we can already see how it and AI may combine for a work experience unlike today’s norm. Some companies are already starting to hold meetings in the metaverse, and experts expect that to occur more often in the future.
Continue reading: https://www.rd.com/article/future-of-ai/

When it comes to machine learning (ML), sometimes every problem looks like it needs a neural net, when in fact it just needs some statistics. This is especially true when it comes to running algorithms on microcontrollers and for industrial use cases such as predictive maintenance, according to Bernard Burg, director of AI and data science at Infineon.
I focus a lot on using machine learning at the edge — specifically the idea of running machine learning models on microcontrollers, known as TinyML — because there are clear benefits for the IoT. By analyzing incoming data where that data is created, engineers can reduce latency, lower bandwidth costs, and increase privacy while also saving on energy consumption. But one doesn’t always need TinyML. Sometimes using linear regression or anomaly detection will do.
Burg told me that so far he’s seen three broad use cases where local data analysis needs to take place, and not all of them require a neural net or true machine learning.
The first use case is handling time series data. Time series data is simply a time stamp and the measurement of something, be that temperature, humidity, light levels, or whatever. Sure, companies can build a neural net to analyze that data, but it’s not necessary and oftentimes isn’t accepted because it can be hard to explain how a neural net makes a decision.
“Those models are in competition with control systems, and people have been building those models for 50-60 years,” said Burg. “So when we come in as AI guys we have to be able to explain why they do what they do.” In that case, Burg argues that a linear regression is probably a better option because it’s both simple and explicable.
The second use case is focused on sound detection. As the incoming data usually looks like a wave pattern, the goal is to match that wave pattern to a wake word, or the noise of, say, glass breaking to the same sound in the environment.
Continue reading: https://staceyoniot.com/when-is-tinyml-too-much/

CIOs globally are adopting Internet of Things (IoT) ecosystems into their IT infrastructure to modernize their tech stack.
Many organizations that are early adopters of IoT are reaping the benefits of Enterprise of Things (EoT) to scale their business. Industry veterans are embracing an innovation-first approach to explore more opportunities of IoT and its positive influence on business outcomes. However, what hinders the adoption Internet of Things into the IT infrastructure is the inherent challenges that it imposes.
Here are a few challenges of an enterprise-wide IoT ecosystem:
IoT generates a huge amount of unstructured data
One of the significant challenges in the Internet of Things adoption is the need for highly structured data. The systems need precisely defined categories to segment data collection. Enterprises that fail to define clear categories to process data will end up in a data mess. It can be challenging to evaluate Unstructured data and get actionable insights. Data scientists should consider analyzing data based on its quantity, type, and speed. Moreover, it is crucial to ingest clean data into the data lakehouse for efficient data analysis.
But the challenge is many places, the data entry points are manual, and there is a potential risk of human error. This degrades the ability of machines to read the data accurately. Hence, CIOs should consider data quantity, type, and speed as their primary consideration while integrating the Internet of Things into their IT infrastructure. Enterprises can hire skilled data scientists or outsource the data management to providers to model the data.
The need for real-time data analysis
Modern enterprises need devices that are able to process the data in real-time even when there is connection loss for the businesses to scale. This is another significant challenge while adopting the Internet of Things into the IT infrastructure.

Integrating edge computing into the tech stack is an effective way to overcome IoT challenges by bridging the gap between data processing and analysis for the information that is generated by the Internet of Things devices.

Click to expand...

CIOs can prioritize and reroute the device data as per the business requirements. Rather than ingesting all device data, enterprises can ingest just a small amount of data into the core site, which they use for the long term or for further analysis.
Integrating advanced Artificial Intelligence (AI) and Machine Learning (ML) tools in the IT infrastructure will help businesses to predict potential roadblocks to designing a response plan. This approach enables enterprises to improve product quality and set predictive maintenance to minimize data flow disruptions. DataOps can consider designing, testing, and deploying ML models for the Internet of Things predictive maintenance. CIOs should consider implementing the best workflows and tools based on containers, Kubernetes, agile development, AI/ML, and automation to effectively leverage the Internet of Things into the IT infrastructure.
Continue reading: https://enterprisetalk.com/featured/overcoming-top-3-barriers-of-enterprise-wide-internet-of-things-iot-applications/

With implementation of the metaverse meaning ever-increasing amounts of connected technology, there are many technological challenges still to overcome
Metaverse implementations will require a huge quantity of data from motion and environmental sensors to track the human participants, and similarly a large number and variety of actuators,  transducers and display screens to provide physical (e.g. haptic), audio and visual feedback to users.
Just like other Internet of Things (IoT) devices, every one of these sensor and feedback devices will be connected, almost all wirelessly, to the control systems for the Metaverse, which will almost certainly be based in the cloud. 
All of these cloud connections present a huge potential attack surface that a bad actor could use to leverage vulnerabilities and potentially take control of the Metaverse. Would you want to enter a Metaverse that might have been hacked? While it would quite inconvenient if a fleet of smart home light switches were hacked, and got used to initiate a Denial of Service (DoS) attack, or were simply turned on and off when they shouldn’t be, the consequences would be much worse, potentially fatal, if a fleet of Metaverse sensors and actuators were compromised. 
Technical challenges to overcome to realise potential of the metaverse
There are many technological challenges that must be overcome before the vision of ubiquitous Metaverses can be realised, as we have seen in the Ready Player One series of books and movies, but the need for absolute security of all the required physical devices probably may not be the top priority of Metaverse developers today. This is a mistake. Users are going to be reluctant to enter a Metaverse if they have concerns about their personal safety. The first inevitable hack of an early, and not fully secured, Metaverse implementation will certainly be widely publicised, fueling such concerns. Unfortunately, security isn’t something that can be bolted on as an afterthought. Security needs to be part of the design specifications for hardware and especially software from day 1. In particular, software needs to be updatable, because the latest software is always going to be the most secure. It is inevitable over time that critical vulnerabilities and exposures (CVEs) will be identified in any software (usually the reason why we have software updates pushed to our phones seemingly every month). 
It is essential that these CVEs are fixed as soon as possible before they become exploited by bad actors. Fixing CVEs requires updating the software for the devices, first in the lab, and then deploying the updated software to the device fleets in the field. Most IoT devices are built using some form of open source software, such as Linux. This has many benefits, including the power of the open source community to quickly address bugs and CVEs as they are identified.  
Continue reading: https://technologymagazine.com/articles/technological-challenges-to-security-of-the-metaverse

Ransomware and phishing attacks continue to climb in Singapore, hitting small and midsize businesses (SMBs) and social media platforms. Cybercriminals also are expected to turn their attention to Internet of Things (IoT) devices and crypto-based transactions, leveraging the lack of security safeguards on these platforms. 
Some 55,000 local-hosted phishing URLs were identified last year, up 17% from 2020, with social media companies accounting for more than half of spoofed targets. This might have been due to threat actors looking to exploit public interest in WhatsApp's announcement to update its privacy policy, said Singapore's Cyber Security Agency (CSA) on Monday, when it released its Singapore Cyber Landscape 2021 report. 
Social networking sites were the most commonly spoofed sector, followed by financial services and the online and cloud services sector. WhatsApp, Facebook, Lloyds, Chase Bank, and Microsoft were the most commonly spoofed brands, according to CSA. 
The government agency noted that scammers also spoofed government websites in late-2021, amidst heightened interest in the Omicron subvariant outbreak here. 
The number of ransomware cases reported to CSA totalled 137 last year, up 54% from 2020, with SMBs from sectors such as manufacturing and IT mostly falling victims to such attacks. These industries typically operated 24 by 7, leaving little time for organisations to patch their systems and potentially enabling ransomware groups to exploit vulnerabilities, CSA said. 
It noted that ransomware groups targeting SMBs in Singapore tapped the ransomware-as-a-service model, which made it easier for amateur hackers to use existing infrastructure to push out ransomware payloads. 
CSA also identified 3,300 malicious command and control (C&C) servers hosted in Singapore last year, more than triple the number in 2020 and the largest figure registered since 2017. The significant climb was attributed to the number of servers distributing Cobalt Strike malware, accounting for almost 30% of all C&C servers. 
Continue reading: https://www.zdnet.com/article/singapore-clocks-higher-ransomware-attacks-warns-of-iot-risks/

The Federal Aviation Administration (FAA) will soon rule on Beyond Visual Line of Sight (BVLOS) drones, which are capable of flying while its operator (pilot) is far away. While these types of drones might offer benefits to society—think of deliveries, infrastructure inspection, and precision agriculture—they also pose serious threats to our privacy. The FAA and the BVLOS industry need to meaningfully address the privacy issues that these types of operations pose to people. Do we want a future with private industry flying drones over our heads with no transparency or protections for our privacy?
What Are BVLOS Drones?
Drones are uncrewed aircraft that can either fly autonomously or are remotely operated. Sometimes they are called unmanned aircraft systems (UAS). You have probably seen people flying small drones to take photos or videos of landscapes or events. In the last few years, drones have become very popular among hobbyists for drone racing, video, and photography. In 2016, the FAA published rules as Part 107 and later RemoteID which cover many of these small drones. However, the operator must be within visual line of sight of the drone—that is, you need to be able to see with your own eyes where your drone is.
BVLOS is when operators are not within visual distance of the drone, allowing the drones to fly much longer distances. The pilots could be over the horizon or even on the other side of the world.
BVLOS drones bring new challenges to operations. For example, since BVLOS drones fly longer distances, maintaining communication and control of the drone is even more important. Also, because you are not there to see where it is and have a full view of the airspace around the drone, maintaining awareness of the surrounding airspace becomes more challenging.  For these and many other reasons, BVLOS drones require their own rules, and will be flown mostly by industry.
Continue reading: https://www.eff.org/deeplinks/2022/08/over-horizon-drones-lineup-privacy-not-sight

Los Angeles International Airport, the federal government is rolling out new tech that could better detect objects entering restricted airspace.
The project, called the Unmanned Aircraft Systems Test Bed Program, is the second of its kind nationwide and will begin testing technology designed to detect, track and identify drones entering the airspace of LAX.
"If a drone was to enter the space as you see with the aircraft taking off and landing, and a pilot having to make a quick decision and divert from that flight path that he or she is on -- that could be a huge issue for both the safety of the passengers, the safety of the folks on the ground, it just creates all types of challenges," Keith Jefferies, the federal security director for the Transportation Security Administration at LAX, told ABC-owned station KABC.
Since 2021, TSA has reported 90 visual sightings of drones and 5,200 technical detections within three miles of the perimeter at LAX. This year alone there have been approximately 38 drones visually detected at the airport – including a drone that was reported within 700 feet of an aircraft just before Super Bowl LVI.
Continue reading: https://abcnews.go.com/Politics/tsa-rolls-program-lax-detect-drones-airports/story?id=88859087

Crypto markets are cyclical. They generally follow a pattern of highs and lows. The price of a coin tends to rise when demand outweighs supply. However, interest begins to weaken after a while, and the price starts to fall. This rise and fall constitute one cycle.
After each cycle ends, a new one begins, forming a recurring pattern over time. Moreover, after each cycle, prices generally establish higher highs and lows. This is one of the reasons why experts suggest holding onto or buying more coins during a market crash. The hope is that owing to the cyclical nature of cryptocurrencies, prices will rise to new highs in time.
Further, after examining historical data, four distinct stages emerged within a crypto market cycle. Each stage has certain characteristics and pinpointing these stages can help you make better investment decisions. So, tag along as we describe the stages of a market cycle and how to identify them.
1. Accumulation phase
The accumulation phase refers to the period where a new low has been reached, and the prices have begun to flatten out. At this stage, panicked investors continue to sell their coins, fearing further price drops. However, seasoned investors and traders will see the accumulation phase as an indicator of a bull run.
This stage is characterized by marginally lesser volatility in the market. Therefore, it is the ideal time to jump into the market and buy the dip. The traders who purchase coins in the accumulation phase have plenty to look forward to in the next stage, the markup stage.
Continue reading: https://www.cnbctv18.com/cryptocurrency/understanding-the-four-stages-of-a-crypto-market-cycle-14612411.htm

In the simplest terms, blockchain technology is a virtual ledger that keeps track of all cryptocurrency transactions. But what makes it so special? Unlike traditional banking systems, there is no central authority controlling the blockchain.
There are various blockchain certification training courses available for you to explore. This revolutionary technology has drawn the attention of businesses and investors around the world, who see its potential for revolutionizing a wide range of industries.
So, what is blockchain technology, and why is it causing such a buzz? Read this article to learn more.
What is Blockchain Technology?
Blockchain technology is a distributed automated ledger that allows transaction data to be recorded and shared publicly. Each “block” of data is stored on a decentralized network of computers, making it nearly impossible to alter or delete.
This is why blockchain is an ideal medium for recording financial transactions or supply chain data. Because it is tamper-proof, blockchain can help to ensure the accuracy and integrity of data. Additionally, blockchain technology can help in reducing costs by eliminating the need for middlemen or third-party intermediaries.
As a result, blockchain is being used in a variety of industries, from banking to healthcare. With its potential to streamline processes and reduce costs, blockchain is said to have a major impact on the way businesses operate.
Continue reading: https://roboticsandautomationnews.com/2022/08/30/what-are-the-uses-of-blockchain-technology/54352/

The crypto market is ripe with lucrative investment prospects, but fraud and other security flaws continue to plague the sector. Therefore, learning ways to avoid crypto fraud is now imperative. 
How can you protect yourself from falling victim to cryptocurrency fraud? How do you keep your personal crypto information uncompromised? See the following tips:
Determine the validity of an initial coin offering (ICO)
Investment and trading are two distinct activities. However, ICOs veer into the trading realm since they are marketed to those with low crypto experience. 
It’s hard to resist the allure of a promising  ICO. However, this is where many inexperienced traders (and investors) fall victim to con artists. 
Ways to spot phoney ICOs include:

• Looking into the people behind the website 
• Reading more about the company’s history
• Going through their social media pages for clues
• Verifying the ICO has sufficient resources, a workable implementation plan, and an accurate financial model
• Inquiring about code or examples that have been posted to a hosting service like GitHub
• Verifying that the ICO’s creators have established an actual escrow service to handle investor funds
• Investigating before acting on a deal that sounds too good to be true

Use a program to cover your tracks on the internet
You can also avoid crypto fraud by cleaning up your internet tracks. A person’s online activities leave a trail known as a digital footprint. In other words, almost everything you publish or enter on the internet is on record. 
Continue reading: https://techcabal.com/2022/08/30/security-tips-to-avoid-crypto-fraud/

Blockchain technology has tremendous potential to facilitate sustainable action. Various companies try their hand at creating a more sustainable planet and rely on distributed ledgers to secure funding. Interestingly, these efforts are more varied than one may think, resulting in varying degrees of success.
Why Blockchain Matters In Funding Sustainable Projects
There is no shortage of projects trying to do social good these days. Most people are familiar with efforts like Red Cross and UNICEF, which have been around for decades. Moreover, every country has more local initiatives that aim to bring financial relief to those in need, either domestically or abroad.
One flaw all of these projects have in common is their lack of transparency. More specifically, users never know where their money ends up or how funds are spent precisely. That became rather apparent when the Red Cross collected billions of dollars in support for Haiti years ago, yet only a few shacks were built, and the rest of the money somehow disappeared. In addition, having too many intermediaries in the chain to handle funds means less cash makes its way to those who need it. 
The demand for more transparency has become much louder in recent years. Especially with sustainable planet-oriented ventures, as they attract a lot of money. That makes the transparency of funds all the more crucial. Blockchain technology seems like an obvious solution, as it provides public and immutable records of all transactions. Several projects have begun experimenting with this approach, all the while trying to build a more sustainable future for future generations.
Continue reading: https://www.nasdaq.com/articles/how-blockchain-can-provide-funding-to-sustainable-projects

In 2023, the Web3.0 blockchain technology sector will be worth more than six trillion dollars, according to Market Research Future, and Web3.0 will continue to grow at a CAGR of 44.6% from 2023 to 2030.
Because Web3.0 relies heavily on blockchain, many wrongly believe that its fate is inevitably linked to the volatile cryptocurrency market. However, cryptos are just one part of the new sector. Gartner explains that while cryptocurrencies crashed in the first half of 2022, decision-makers should not assume that the value of Web3.0 technology is affected. According to the research and consulting firm, Web3.0 tech will soon reach its adoption tipping point and industries from aircraft maintenance to food safety will tokenize their applications.
What drives the growth of Web3.0?
The Web3.0 Blockchain Market Research Report reveals the business, technical and security reasons driving Web3.0 growth. While the COVID-19 pandemic devastated industries like hospitality, automobile, aviation and retail, the IT industry revenue increased steadily. IT also saw new market opportunities as users demanded 5G tech, virtual and augmented reality, blockchain applications, AI and machine learning. These technologies are the pillars on which Web3.0 is being built.
SEE: Metaverse cheat sheet: Everything you need to know (free PDF) (TechRepublic)
“Blockchain has been a proven technology that ensured the security of the crypto and NFTs to the next level — now, it is ready to ultimately transform the next generation of web technologies,” Aarti Dhapte, senior research analyst at Market Research Future told TechRepublic. “Web3 blockchain will completely transform the existing conventional processes of the different sectors.”
From financial services to retail and e-commerce, media and entertainment, healthcare, IT, government and energy: Almost every sector is expected to adopt Web3.0 blockchain.
Top executives and decision-makers see potential in the highly transparent nature of a decentralized Web3.0, where all transactions are recorded and registered and can be easily traced. On the other hand, developers and IT teams invest in Web3.0 due to the strengths of its rapidly developing technology.
Continue reading: https://www.techrepublic.com/article/web-blockchain-technology-market/

Experts have said females are under-represented in the global tech space because of a myriad of reasons. They have also suggest ways on how to increase female representation in the ecosystem.
According to them, this is not an issue of an imbalanced global society but also a workforce problem, given the critical shortage of skilled tech professionals.
In an email interview with our correspondent, an investor at Techstar, Alisha Golden, said, “The pay gap between women and men, gender bias based on workplace roles, and a shortage of female role models in executive and leadership positions are the primary barriers faced by women looking to break into tech, according to a survey by the global technology association ISACA.
“Women are vastly under-represented in the global tech workforce, which is not only an issue of an imbalanced global society but also a workforce problem, given the critical shortage of skilled tech professionals. More opportunities, including job exposure, training, boot camps, and career advancement programs are needed in order to make long overdue progress in ensuring that women are more equitably represented in the tech workforce.”
Explaining how firms should prioritize the gender gap, she stated that firms need to invest in more women and create pathways for more women to enter the tech space and thrive.
Using her firm as an example, she said, “We have clear KPIs on diversity in our portfolios, meaning our performance as a firm is measured based on this. This is an intentional approach to playing a major role in being a part of the change we want to see in a vastly male-centric industry.”
Continue reading: https://punchng.com/how-tech-can-attract-more-female-professionals-experts/