The Deep Tech revolution -- Part 1: White papers
Artificial Intelligence, Internet of Things, Cybersecurity, Blockchain: these words have become common terms we hear everyday, dominating the news and business landscapes worldwide under what we have come to know as Deep Tech. According to recent research, in 2021 the deep tech market registered a total revenue of US$431.1 Million, and is expected to grow by 21 percent between 2022 and 2032 for a value of US$ 3,733.8.
Start-ups and companies within the Deep Tech space are all about innovation and advancing technologies, often diving into niche parts of already narrow fields. They run the business side differently, they bring revolutionary approaches to traditional dynamics in the work environment, and even create new roles and job titles not seen in other companies. Staying true to their nature where science and innovation plays an important role, these companies engage in specific activities that best compliment their primary immediate goal of research and development, whether this is about technology, sharing knowledge or growing their community.
Achieving cybersecurity excellence: The art of balancing automation and human expertise
In an era marked by continuously evolving cyberthreats, the significance of automation in the realm of cybersecurity cannot be overstated. Automation has emerged as a potent tool that enables security leaders to effectively address the challenges presented by today's digital environment. It offers numerous advantages, including swift and consistent responses to threats, the mitigation of potential human errors and a reduction in incident response times.
However, while automation is a vital asset, striking the right balance between automation and human involvement is essential to ensure optimal cybersecurity outcomes. In this article, we will explore how organizations can achieve a harmonious partnership between humans and automation to enhance threat detection, response and decision-making.
Looking to 2024: Data, AI and security will be top priorities for businesses
The technology landscape has evolved significantly over the last year with the introduction of technologies such as ChatGPT and other generative AI tools taking the market by storm, while raising concerns about data security and more.
As we move forward into 2024, we anticipate that the impact these new technologies have made this year means they will continue to pave the way forward, with AI remaining a hot topic in the industry, while data security concerns rise around it.
If your data isn't real-time, your AI isn't intelligent
From governments, to entrepreneurs, to enterprises, organizations are looking to understand and exploit Artificial Intelligence to support data-driven decision making. At the heart of this is knowing how AI, and particularly generative AI, operates. Like so much other technology, effective AI is a matter of data analysis.
Put simply, the more data an AI is fed, and the higher quality, the better its analysis will be. This means that the age-old problem of Garbage In, Garbage Out (GIGO) will always be an issue. But there is another, equally crucial issue to consider -- timeliness.
What's in a name -- why you should care what open source is
"We really should stop getting hung up about what open source means," a statement repeatedly made by those for whom a lack of understanding of open source is advantageous. Generally those who don’t want to meet the standards that are set out in the Open Source Definition (OSD) which all Open Source Initiative approved license must meet, including the requirement that open source software must be usable by anyone for any purpose. And usually they are in denial of the requirement for open source licenses to be usable for any purpose, which includes commercialization. This really sits at the heart of open source.
In a commercial context open source means enabling your competitors with your own innovation. In a world where companies are driven by shareholder value this simply would not happen if it did not come with clear and measurable advantages, like collaboration, creating a defacto standard or building an ecosystem around it, and where equivalent or greater value than the proprietary royalty model is generated.
Beyond phishing: The top employee security risks you're probably not measuring
While we all know email is a big target for attackers, it’s important to remember that email is not the only risk vector. As companies use more tools and features, the risks grow too. Email is just one piece of the puzzle, which is why it is crucial to consider a wide range of employee security behaviors to get a holistic view of your risks. By doing so, you can focus resources more efficiently.
Human Risk Management (HRM) is a vital part of cyber security. Even if you have technological safeguards in place, HRM plays a substantial role in your overall security stance. Here I highlight some of the employee cyber risks that often get overlooked and how we can better keep an eye on them in real time.
Three methods to improve organizational data quality today
Our modern business landscape transforms constantly, yet the value of data endures. However, thriving companies don’t merely amass data -- they cultivate meaningful data.
Leaders must have trustworthy data to unlock organizational insights, but inaccurate data is still rampant in most organizations. This data costs leaders far more than missed opportunities. According to industry research, bad data costs U.S. enterprises $3.1 trillion annually. Still need convincing about the benefits of data quality? Let’s discuss the benefits of high-quality data and explain how leaders can adopt a leading data management strategy today.
The coming AI economic revolution: Can artificial intelligence reverse the productivity slowdown?
The artificial intelligence revolution is here to stay, and a large part of the reason is the massive economic impact of the technology on the industries it has touched. Effectively implementing AI into a business’s operation requires an incredible amount of planning and precision, as well as consideration of all of the ethical and regulatory challenges associated with the use of the technology.
One of the primary reasons AI has become such an exciting and dominant technology is its ability to process data faster than human workers. In many industries, we have seen efficiency increase by allowing AI and automation to take over simpler and more labor-intensive tasks, enabling human workers to spend more time on tasks that require a more human quality.
Balancing AI with insider risk management
AI has officially taken off, yet organizations are squarely divided on their use in the workplace. Organizations that encourage the use of AI and Large Language Model (LLM) tools for productivity are willing to accept the security risk but often lack the policies, education, and controls required to mitigate potential security risks, including those posed by insiders.
On the other hand, companies that take a hard line against the tools by implementing strict rules against any installation or use of AI-LLMs may cause their employees to be less productive. Fortunately, there is a middle ground that balances productivity with security and, importantly, with insider risk management.
Advanced authentication: 5 steps to enhance security and user experience
With the development of new technologies, cyber threats are becoming more sophisticated, and personal data remains one of the most desirable targets. The Verizon Data Breach Investigations Report states that 49 percent of hacks use credentials.
Traditional authentication methods, such as username and password with standard Multi-Factor Authentication (MFA), are no longer sufficient to protect sensitive information and systems from unauthorized access. According to Microsoft, there are 1287 password attacks every second. Consequently, businesses must adopt more sophisticated and layered methods of user authentication. One of these methods is Advanced Authentication.
How to stop digital twins from being used against you
Digital twins are growing in leaps and bounds. These virtual representations of real-world devices are essentially digital proxies for enterprises -- delivering insights into an asset’s data, processes, operation states, and lifecycle. This is particularly beneficial in achieving better visibility in smart factories, or accurately predicting how devices might perform in connected healthcare.
In creating digital twin simulations and running models, however, there’s a problem. Doubling the data and doubling the digital assets of any company is, in effect, doubling the cybersecurity surface area. This increases the chances of exposure and sensitive company information falling into the wrong hands. Without proper safeguards, the risk is that digital twins can be turned against their owners. Amidst a landscape of record growth in the Internet of Things (IoT), let’s look at how to safely leverage the power of digital twins.
Generative AI: Approaching the crossroads of innovation and ethics
As the recent hype and excitement around Generative AI (GenAI) begins to settle somewhat, we are entering a critical phase where innovation must be more closely aligned with ethical considerations. The impact of AI is already evident in various aspects of life, pointing to a future where, ideally, its use is not only widespread but also guided by principled decision-making. In this context, the emphasis should be on using AI to address appropriate problems, not just any problem.
In particular, the early iterations of GenAI platforms have demonstrated their potential but also the need for careful application. In many organizations, GenAI has already improved both customer and employee experiences, with advanced chatbots capable of mimicking human interaction taking automated customer service to a whole new level by providing quick and relevant responses. In an ideal world, this use case highlights AI’s dual purpose: to enhance human capabilities while maintaining a focus on human-centred experiences.
Insider threats: Don't underestimate the dangers within
As we look ahead to the coming year, Trellix Advanced Research Centre recently shared its predictions for 2024. Among them, it highlighted that as connected devices continue to proliferate, and hybrid and remote workforces persist, insider threats will only continue to grow.
This expected increase is especially worrying as research has already shown that breaches caused by employees have seen a 47 percent increase over the last two years, whether accidental or malicious. Annually, 34 percent of all businesses will suffer an insider threat incident, costing an estimated eye-watering $15.38m per occurrence, so the predicted increase is particularly frightening.
Multicloud by design: Making a cloud environment that truly works
We all know the saying: you can’t have it all. The same applies to the cloud providers -- a single one cannot give and be everything you need.
Increasingly we are seeing customers demand higher standards from their cloud services in an effort to reduce savings and security risks, as well as enhance their flexibility. In a landscape that is always changing, many sectors are feeling the need to keep up with technology or even try to be one step ahead of it. To meet these complex requirements, companies may want to look a little wider than their single cloud provider set-up and into the world of multicloud.
How to protect your organization against SEO poisoning and malvertising
Alongside traditional approaches like software vulnerabilities and misconfigurations in applications, hackers are constantly looking for new ways to get into devices and corporate networks. Two of the biggest growing threats are Search Engine Optimization (SEO) poisoning and Malvertising.
SEO Poisoning is where hackers lure victims to legitimate websites by populating them with content on topics of interest to potential victims. For example, Gootloader, an Initial-Access-as-a-Service operation, targets law professionals because they handle sensitive business data that can be extremely valuable. Hackers use Gootloader to get a foothold into an organization’s IT environment and then spread laterally through the entity’s IT network to implant ransomware or exfiltrate data.
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