How shifting information left can empower developers and accelerate innovation
Development teams are increasingly seen as the engine room of the modern digital enterprise, tasked with building the new services and capabilities that the business needs to thrive. However, with resources stretched to their limit, organizations must find a way to empower their developers to work more productively, so they can deliver newer, better digital capabilities faster and more reliably. If they fail to do so, it will be more difficult to keep pace with market demands, and many will see their competitors gain the advantage.
In response, organizations are increasingly adopting a shift left approach, to ensure that new code is tested earlier in the software development lifecycle (SDLC). This reduces the risk that code could contain errors or vulnerabilities that lead to delayed innovation, as applications or features are rolled back to be reworked by developers. But shift left should not be about moving extra work “left” in the SDLC, or demanding developers assume extra responsibilities. It should be about empowering developers to work smarter, by shifting all relevant information left. Developers should have all the insight they need, when they require it, to make better decisions.
Redefining security in mobile networks with clientless SASE
As organizations adapt their IT ecosystems to incorporate IoT devices and expand remote working opportunities allowing employees to use personal mobile devices, enterprise mobility has become indispensable in modern business operations. Nonetheless, this shift presents numerous security challenges and lifecycle management considerations, especially given that mobile devices connecting to networks frequently lack compatibility with traditional security solutions such as Virtual Private Networks (VPNs) or endpoint tools.
Mobile Network Operators (MNOs) and Mobile Virtual Network Operators (MVNOs) are at the forefront of this challenge. These service providers are tasked with the dual responsibility of ensuring optimal connectivity while safeguarding data privacy and user experience. As the market for basic connectivity services becomes increasingly commoditized, these operators are compelled to explore new avenues for revenue through value-added services. Among these, security services stand out as a promising opportunity.
It's not all artificial: The 4 types of intelligence CTOs need to get the most out of AI
Enterprises plan to spend roughly $35.5 million on IT modernization in 2024, with over a third going to AI to boost productivity. But it’s not all sunshine and rainbows. At the same time, 64 percent of IT leaders worry about rushing to adopt generative AI without understanding what's needed to use it effectively and safely. And while 75 percent of organizations have experimented with generative AI, only 9 percent have adopted the technology widely. There’s so much more potential to tap into.
To get the best out of AI to supercharge operations it all comes down to intelligence. Afterall, AI is only as intelligent as those using it. There are the four types of intelligence that CTOs need to build, and it’s nothing to do with coding or super complicated technology. It’s about cultivating soft skills and human talent to control AI in a responsible way.
Unlocking cybersecurity success: The need for board and CISO alignment
The C-Suite’s perception of cybersecurity has evolved dramatically over the past decade. It’s gone from being an afterthought for technology departments to worry about, to a cornerstone for business survival and operational strategy. The heightened awareness of cybersecurity stems from a deeper grasp of the legal, reputational and financial implications of data breaches. This, combined with regulatory pressures such as the original NIS directive, has forced leaders to enhance their organizations’ cybersecurity measures.
The result is that 75 percent of organizations now report that cybersecurity is a high priority for their senior management team. While on the surface this should be celebrated, when digging deeper, conversations between CISOs and the wider C-Suite often just revolve around high-profile or user-centric security risks. More technical and advanced threats such as those related to application security are overlooked. The race to embrace AI and increasingly complicated cloud infrastructures have also made communicating cybersecurity priorities even more difficult for CISOs.
Out of the shadows and into the light: Embracing responsible AI practices amid bias and hallucinations
The path to widespread AI is a bumpy one. While its potential to enhance consumer experiences and streamline business operations through personalization, autonomy, and decentralized reasoning is evident, the technology comes with inherent risks.
AI can produce conclusions that aren’t true, spread misinformation and in some cases, perpetuate existing biases. This -- the darker side of AI’s impact -- can leave business leaders facing financial, legal, and reputational damage.
Balancing security and autonomy: Strategies for CISOs in the cloud era
Maintaining a secure cloud environment is one of the most important responsibilities of any CISO today, given that over 50 percent of all cyberattacks now originate in the cloud. However, this is a daunting task, as security must now be balanced against other priorities such as maintaining agile operations and the need to innovate.
Organizations today are racing to accelerate their cloud adoption due to the need for greater scalability and cost-efficiency. It has, therefore, become a critical business strategy to ensure efficiency, accessibility, and sustainability in operations. As a result, cloud investments are soaring across the board. Gartner predicts that end-user spending on public cloud services will reach $679 billion by the end of this year and exceed $1 trillion by 2027.
Six steps to safeguarding your digital identity
We lose a bit of our digital privacy with every data breach that occurs. A breach like the one at AT&T -- which exposed Social Security numbers and other personal information needed for identity theft -- is particularly serious in the landscape of data breaches. The percentage of users with Social Security numbers exposed in our data bases following the AT&T breach increased from less than 1 percent to almost 15 percent. Sensitive personal information getting out -- especially when it's easily accessible on the public internet, not just the dark web, which requires special software to be accessed -- opens you up to a huge risk of abuse.
The most notable threat users face is the potential for identity theft, where malicious actors access email, bank, and credit card accounts to impersonate victims. This can also include gaining unauthorized access to accounts by resetting passwords and even taking control of your phone number to bypass text message confirmations. What’s more, if a thief has access to your personal details, they might go as far as taking out loans or credit cards in your name -- a tactic that remains one of the most common types of identity theft.
Why a zero trust approach is essential to mitigate the threat of unsecured APIs
With the move to hybrid working, the rapid adoption of cloud, increased use of mobile and IoT devices, combined with the ongoing drive to modernize and transform IT operations, the attack surface of every organization has -- and continues to -- expand.
Traditional boundaries have been blurred between businesses, suppliers, partners, customers, workers, and even home-life, with this ecosystem continuing to grow. Here, APIs are providing the connective tissue for modern applications and legacy infrastructure to co-exist.
Artificial Intelligence: What are 4 major cyber threats for 2024?
AI is one of the most powerful innovations of the decade, if not the most powerful. Yet with that power also comes the risk of abuse.
Whenever any new, disruptive technology is introduced to society, if there is a way for it to be abused for the nefarious gain of others, wrongdoers will find it. Thus, the threat of AI is not inherent to the technology itself, but rather an unintended consequence of bad actors using it for purposes that wreak havoc and cause harm. If we do not do something about these cyber threats posed by the misuse of AI, the legitimate, beneficial uses of the technology will be undermined.
Seven crucial dos and don'ts for cyber-attack survival
Think you’ve been hit by a cyber-attack? You need to move fast, but what immediate actions should you take, or should you not take? Here’s a Cyber Incident Responder’s guide to steer you through the turmoil. The actions your team takes -- or doesn’t take -- can greatly impact the overall duration of recovery, cost, and the potential to uncover vital evidence left by threat actors within your infrastructure.
Identifying a cyber security incident can be challenging. Many threat actors have mastered the art of quietly infiltrating IT systems and hiding their digital footprints. Not all cyber-attacks are as overt as encryption-based ransomware or mandate fraud. The rise of encryption-less ransomware and corporate and state-level espionage is concerning. These silent intruders can lead to data and intellectual property (IP) loss, diminished competitive edge or market share, potential regulatory fines, and reputational damage. All of which can be just as devastating, if not more so, to an organization, its employees, and investors, than a single ransomware incident.
Move over Google, LLMs are taking over!
When Google was founded in 1998, it ushered in a new era of access to information. The groundbreaking search engine wasn’t the first to debut (that was World Wide Web Wanderer in 1993), but it was the one that caught on. By 2004, Google was fielding over 200 million searches per day; by 2011, that number had exploded to about three billion daily searches. By that time, the word “Google” had morphed from just the name of the search engine to a verb that meant “to use an internet search engine.” Twenty years later, Google still dominates the market with an almost 84 percent share as of late 2023.
Though Google is still the most popular search engine, new technology has emerged that could threaten its supremacy -- LLMs. The use of this technology is growing at an astonishing rate. In fact, in February 2024, ChatGPT generated over 1.6 billion visits.
Top priorities for digital transformation strategy implementation
A digital transformation strategy requires a focus on its business value and ability to support key company initiatives. These initiatives are often tied to transformative changes in the business that are connected to customer experience, operational efficiency, and productivity gains. Too often, digital transformation projects are technology driven and lack understanding of business objectives, and do not engage the right stakeholders or clearly detail the needed business / technology roadmap for strategy implementation over a multi-year period.
There are several key actions that should take priority when implementing a digital transformation strategy. These are:
Poisoning the data well for Generative AI
The secret to generative AI’s success is data. Vast volumes of data that are used to train the large language models (LLMs) that underpin generative AI’s ability to answer complex questions and find and create new content. Good quality data leads to good outcomes. Bad, deliberately poisoned, or otherwise distorted data leads to bad outcomes.
As ever more organizations implement generative AI tools into their business systems, it’s important to reflect on what attackers can do to the data on which generative AI tools are trained.
The role of APIs within Large Language Models and the shift towards a multi-LLM world
With the arrival of Large Language Models (LLMs) such as ChatGPT, BERT, Llama, and Granite, the operational dynamics within the enterprise sector have significantly changed. LLMs introduce unique efficiencies, paving the way for innovative business solutions. LLMs currently stand at the forefront of technological advancement, offering enterprises the tools to automate complex processes, enhance customer experiences, and obtain actionable insights from large datasets.
The integration of these models into business operations marks a new chapter in digital transformation and therefore requires a closer look at their development and deployment.
Navigating the Cyber Trust Mark: A roadmap for IoT device manufacturers
There are more than 15 billion IoT devices worldwide, and that number is expected to reach 29 million by 2030, with consumer products like baby monitors, smartwatches, and fridges accounting for more than half. However, connectivity comes at a cost. Data usage, privacy concerns, and cyberattacks pose a serious threat to users and manufacturers. To address this, the government has implemented a Cyber Trust Mark Program to help people easily identify products that meet security standards. The initiative provides manufacturers with a roadmap to improve security and prepare for future requirements.
A key part of The Cyber Trust Mark program is that devices must pass tests designed to ensure security and data privacy. Securing connected solutions poses a unique challenge for manufacturers. While patching a network configuration issue is simple, software is often separated from connected device design workflows. This means security testing occurs in the final stages of product design, making it harder to build security from the ground up.
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