Encrypted Client Hello didn't solve censorship, but still may have a role to play
In November 2024, Russia began blocking Cloudflare’s implementation of Encrypted Client Hello (ECH), a privacy-focused extension of the TLS protocol.“This technology is a means of circumventing restrictions on access to information banned in Russia. Its use violates Russian law and is restricted by the Technical Measure to Combat Threats (TSPU),” the statement by the Russian Internet regulator read.
Russia, known for its tight control over internet access, views ECH as a tool for bypassing geo-restrictions, though that was never its intended purpose. This move follows a broader pattern of censorship and surveillance. Over the past few years, Russia has been cracking down on VPNs, making it harder for users to circumvent government-imposed restrictions.
How the Disney insider threat case breaks the security binary illusion
Security is always a bit like a game of whack-a-mole in that you never quite know where the next incident is going to pop up. On the face of it, this shouldn’t be too hard. Everyone knows to secure your PII, PHI, customer financials, production environments, and other resources that are clearly highly sensitive. But sometimes the question of what is sensitive is less black and white, filled with plenty of gray areas.
This uncertainty can lead to organizations failing to properly secure their resources, as we saw in the recent incident over at Disney.
The quantum revolution: Five ways quantum will transform everyday life
Our world is gripped by uncertainty. From economic volatility to the climate crisis, businesses and individuals alike are navigating a landscape marred by unpredictability. As the World Economic Forum warns in its most recent global risk report, our outdated digital infrastructure and subsequent services are struggling to keep pace with the growing demands of the modern world.
As emerging technologies like AI, Blockchain and even 5G hit everyday life like a tidal wave, we need something that can not only help us navigate our way but also handle the waves. Think of it like trying to cross an ocean on a rowboat, without a compass. What we need is a modern cruise ship.
The hypervisor world is shifting -- is this the end of the VMware era?
Broadcom’s acquisition of VMware late last year created fear and uncertainty among vendors and partners alike. The subsequent overhaul of VMware’s product offering and consumption model have only served to fuel this disquiet.
In parallel with the restructuring and consolidation of VMware’s most popular and prominent product offerings, Broadcom’s takeover has seen VMware transition from a perpetual licensing structure to compulsory subscriptions. As a result, many VMware customers face significant cost increases.
AI and hiring
The advent of artificial intelligence inspired a great deal of fear in the workplace, especially regarding job displacement. As AI's potential became more apparent, workers in virtually every industry feared they would be replaced by an AI-driven alternative that could work faster and for less pay.
To date, those fears have been mostly unfounded. In fact, a recent study of nearly 3,000 different workplace skills determined none of them were “very likely” to be replaced by generative AI.
Is AI a double-edged sword for lawyers?
The legal industry is not traditionally recognized as one that is quick to embrace change, but recently, some professionals have been embracing emerging technology maybe a little too quickly, leading to all kinds of problems. The use of generative AI tools has exploded in popularity since OpenAI’s ChatGPT debuted in late 2022, and some lawyers have turned to this generative AI (GenAI) technology to help them with everything from legal research to contract drafting.
However, these GenAI models aren’t foolproof. In fact, they’re likely to “hallucinate” information that seems accurate but is actually entirely made up. If lawyers using this tech don’t take the time to double-check their outputs, they run the risk of working with factually incorrect information, which is embarrassing at best and grounds for legal repercussions at worst.
The coming of 6G poses new IoT security vulnerabilities
A growing challenge for 6G wireless development involves the potential for unexpected cybersecurity vulnerabilities. This is especially true given the growing set of Internet of Things (IoT) use cases with complexities such as connected cars, smart cities, and even satellite-based (non-terrestrial networks (NTN) IoT. The expanding security threat surface is particularly concerning due to its novelty and the lack of thorough testing by researchers.
IoT vulnerabilities themselves are nothing new. We have seen the hacking of home doorbell cameras since the advent of 4G. However, that problem has less to do with wireless standards than with homeowners making poor decisions about how to manage device passwords.
Navigating the future: Cloud migration journeys and data security
For years, businesses have been chasing innovation with cloud platforms, moving beyond the limitations of legacy technology for greater speed and agility, and sharpening their competitive edge. However, all businesses often face challenges that complicate cloud migration, driving up costs and timelines while exposing the business to data security risks. Ultimately, these challenges block businesses from experiencing the true benefits of cloud integration, and in some cases, lead to significant breaches and regulatory fines.
The speed of cloud migration is most commonly hindered by data security concerns, budget overruns, fragmented implementations, and operational friction. These challenges -- affecting the three key stakeholders within the cloud migration strategy of Data and Analytics Leaders, Security Leaders, and IT Leaders -- often cause projects to run well beyond their planned timelines and budgets. In many cases, these migrations fail to deliver value because data utilization is restricted by inadequate security, and extended timelines erode the business’s first-mover advantage.
Addressing data governance in a hybrid cloud world
As more organizations look to deploy AI and LLMs across their operations to drive a competitive edge, ensuring the data being used to power these innovations is of high enough quality is becoming business critical. To give these AI and LLM innovations the best chance of success, many organizations are turning to hybrid cloud infrastructures, making use of both on-premises and cloud to ensure they can tap into valuable data.
But hybrid cloud infrastructure comes with its own set of challenges, particularly when it comes to data governance. Inherently, a hybrid infrastructure allows data to move between environments, which can make that data vulnerable to not only security risks but also growing regulatory compliance considerations. With so many regulations surrounding data firmly in place, such as the EU’s GDPR and the US HIPAA, compliance is crucial to business operations. GDPR fines alone can reach 2 percent of global turnover. A penalty of this magnitude would have a huge impact on the entire organization.
Developers' guide: 8 ways to fast-track AI integration
AI empowers developers to co-create the software that powers our world with greater efficiency and improved security. That’s why businesses are already making significant investments in AI. According to GitLab’s 2024 DevSecOps report, 98 percent of UK respondents said they are currently using AI in software development or plan to use it. It’s therefore no surprise that today, many companies are shipping software at least twice as fast as last year.
Here are eight ways developers can tap into AI’s potential:
Sleek, chic, but unsustainable: Why OEMs must rethink laptop design for a greener future
The evolution of computers from the bulky, desktop-bound machines of the 1970s to the ultra-portable laptops of today is nothing short of remarkable. Over the past few decades, consumer demand has driven Original Equipment Manufacturers (OEMs) to create lightweight devices that pack serious processing power and are thin enough to slide easily inside a rucksack.
Today's laptops, some coming in at under a kilogram, are a completely different animal to the first portable computers, like the Osborne 1, which weighed more than ten times as much. As our devices become sleeker and easier on the eye, however, aesthetic choices run the risk of glossing over sustainability goals.
Beyond point solutions: Building a cohesive fintech ecosystem through vendor optimization
In the financial services industry, competition has never been steeper. As fintechs and neobanks accelerate the pace of innovation and digital banking demand soars, financial institutions (FIs) can't afford to postpone digital transformation initiatives. However, despite the widespread recognition of its importance, many FIs find themselves stuck in the initial phases of their digital transformation journeys. Research shows that a staggering 70 percent of FIs are unable to move beyond the planning stages of migration.
One of the primary reasons for this sluggish progress is the burden of tech debt and fragmented processes. Over the years, FIs have accumulated a complex web of systems and applications that hinder seamless operations and impede transformation efforts. The proliferation of disparate systems and applications across departments has left most organizations with a hybrid operating environment full of systems that don’t integrate well -- if at all. On average, a typical FI manages more than 200 applications, resulting in a fragmented infrastructure that consumes a significant portion of the IT budget -- 90 percent dedicated to maintenance alone.
Apps, analytics and AI: 4 common mistakes
The app economy is big business. Apple’s App Store ecosystem alone generated a staggering $1.1 trillion in total billings and sales for developers in 2022. But as users demand more relevant and immediate experiences, often driven by AI, developers increasingly need competitive advantages to stand out.
Real-time analytics, supercharged by generative AI, can provide a critical edge by allowing developers to extract key insights and quickly adapt their apps to reflect changing user expectations. But only 17 percent of enterprises today have the ability to perform real-time analysis on large volumes of data, and adoption remains slow. Meanwhile, even when companies are able to perform real-time analytics, there are several common mistakes that can prevent them from reaping its full benefits:
How to thrive in the era of minimal data deletion
According to the latest global estimates, up to 400 million terabytes of data are created every single day. However, unlike the past, where users were happy to delete data once they felt it was no longer required, today’s data rarely gets deleted anymore, which is creating a growing number of issues.
It has become a cliché to say, “data is the new oil”, but its value has never been higher. Companies across all industries now collect as much as they can from every customer and process, so it can be mined for valuable insights and/or sold to generate new revenue streams. But to extract greater value from data, you need to keep it. To keep it, you need space, security, and money. Consequently, organizations are increasingly looking for the best ways to store their data without breaking the bank (or damaging the environment, if they can help it). The question is, what’s the best way to go about doing this?
Will AI change the makeup of software development teams?
With the increased popularity of artificial intelligence technology, many human workers have expressed concern that AI models will replace them or make their positions obsolete. This is particularly the case with occupations like coding and software design, where artificial intelligence has the opportunity to automate several essential processes. Although AI is a powerful tool that has the potential to revolutionize the coding process, the role of human workers is still invaluable, as this technology is still in its infancy.
Software development teams are among the ranks of workers most profoundly affected by the AI revolution. Some of the ways in which software development teams have begun to use artificial intelligence include:
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