The increasing sophistication of synthetic identity fraud
Synthetic identity fraud is most commonly associated with fraud in banking or against credit unions but is often mistakenly overlooked in digital commerce. With fraudsters becoming cleverer about how they use synthetic identities, it’s a tactic that fraud fighters need to watch out for and guard against.
Synthetic identity fraud is when a fraudster takes a piece of real identifying information belonging to a legitimate individual and combines it with other identifying information that is either fake or real but belongs to someone else.
The NIST/NVD situation and vulnerability management programs
In the infosec world we continually preach about “defense in depth,” or layered security. The idea is that if a defensive measure at one layer fails, there are additional layers behind it that serve as a safety net. An interesting application of these concepts comes in examining the data feeds that provide information to our security tools. If one of the feeds goes down, will our security tooling continue to work as expected?
This recently came to light when the National Institute of Standards and Technology (NIST) announced that it cannot keep up with the number of software bugs being submitted to the National Vulnerability Database (NVD). According to NIST itself, it has only analyzed roughly one-third of the Common Vulnerabilities and Exposures (CVEs) submitted this year. Since many organizations rely on NVD information in their vulnerability management programs, this is distressing news. For organizations in this situation, the question then becomes: How do we minimize the impact of the NIST backlog?
How AI will shape the future of the legal industry
The Department for Science, Innovation and Technology (DSIT) announced a £6.4 million grant for small and medium-sized enterprises (SMEs) to invest in AI-technology skills-based training. This development is the latest in a string of AI funding initiatives across the UK corporate sector, indicating that 2024 is the year emerging technologies will revolutionize the workplace in all aspects.
AI technology is transforming business functions across industries. However, the legal sector, in particular, has demonstrated tremendous progress. Often portrayed as laggards when it comes to embracing innovation, legal’s cautious, conservative approach to tech adoption has become a thing of the past in the age of AI. A recent survey from the Legal Services Board (LSB) discusses how over 95 percent of legal businesses found that implementing new technologies has made them more responsive to clients’ needs. Moreover, 60 percent of surveyed legal businesses found their clients expect them to power their legal services through tech innovation.
Why the financial services industry has to start future-proofing their operations
The digital revolution continues at pace. Yet, whilst many industries are looking to harness the transformative impact of AI and other innovative tech, there are many firms in financial services that are simply unprepared and unable to capitalize on the latest advancements.
A reliance on legacy systems and the use of paper-based forms of communication and record-keeping is holding the sector back. Now is the time for the industry to fully embrace digital transformation strategies or risk being left behind. The benefits of going digital for businesses in the financial services industry are huge, encompassing benefits from streamlining operations and cutting costs, to improving customer experience and overall functionality. Whilst adopting new technologies undoubtedly comes with risks, the sector can ill-afford to stand still in the face of such a rapidly changing world.
We're not going to deal with today's IT admin issues with yesterday's technology
If I were to put you in a time machine and transport you five years into the future, do you know what you’d find in IT administration? Even more complexity, heterogeneity, and increased use of novel new platforms and technologies. And yet IT admins would still be worried and stressed about their security gaps, whilst still managing all user authentication, device management, and access to resources via a piece of legacy, on-premise, software first launched in the year 2000: Active Directory.
You read that right. That’s 24 years ago. Don’t get me wrong; just because something wasn’t created yesterday doesn’t mean it’s not useful. But what is concerning is that, for all the incredible digital transformation initiatives that SMEs (small to medium enterprises) have initiated in the last few years -- we somehow think that the default option is best.
AI-powered data management: Navigating data complexity in clinical trials
The data flood gates have opened wide for clinical trial research. In fact, the amount of data gathered may be more akin to a tsunami or a monsoon. For decades, researchers struggled with a lack of data available in clinical trials; however, they may have received more than they asked for. Research shows that the biopharmaceutical industry generates up to a trillion gigabytes of data annually and clinical trials, one of the principal contributors to these data points, generate an average of up to 3 million data points per trial. This influx of sources can make it challenging to discern relevant from superfluous information, complicating analysis and delaying critical decision-making.
An increase in decentralization paired with expanded collection methods in clinical trials have increased access to and accumulation of data. Information gathered from remote monitoring devices, electronic health records (EHRs), laboratory tests, surveys and questionnaires and third-party databases, all contribute to the data challenge in clinical trials. In reality, the number of touchpoints across clinical trials, from sponsors to clinical research organizations (CROs) to site staff, combined with the complexity and disparity of data sources leads to challenges in ensuring data quality.
Workforces need the skills to defend against AI-enabled threats
It’s no secret that artificial intelligence (AI) is transforming software development. From automating routine tasks to enhancing code efficiency and optimizing testing processes, AI is helping developers save time, money, and resources. It can also analyze code to detect bugs, security vulnerabilities, and quality issues more effectively than traditional models. If you’re thinking there’s a "but" coming, you’re right.
The downside to the benefits of leveraging AI technologies in software development is that it can also enhance the capabilities of malware developers. As such, the proliferation of AI is not necessarily fueling new cyberattacks, it is simply creating an even distribution of enhanced proficiency for both legitimate and malicious actors.
Overcoming real-time data integration challenges to optimize for surgical capacity and better care
In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only useful if the pieces fit together, solving a puzzle of coordinating schedules, operating room availability, and resource allocation, while ensuring immediate access to patient data for perioperative teams.
Data management demands are significant, complex, and dynamic. Because each patient is unique, anything can happen in an operating room (OR) at any moment. As such, real-time data capture is crucial for surgical workflows. When surgical teams have all the information they need in real time, they can make rapid decisions that not only maximize OR utilization and minimize delays but also enhance overall patient care and safety.
Stop sideloading headaches on Apple devices: Why EU admins need MDMs now more than ever
Apple just went full Android in the EU. While sideloading, the act of installing apps from sources other than the OS's official app store, is a familiar practice for Android users, it marks a departure from the tightly integrated ecosystem that has long characterized Apple's approach.
While the option to pick and choose the apps on their devices holds appeal for certain enterprises, EU admins might not agree. Maintaining a delicate equilibrium between user privacy and strong endpoint security has always been a challenge, one that is bound to escalate with the EU's latest regulatory changes.
The unseen ethical considerations in AI practices: A guide for the CEO
Artificial Intelligence (AI) is only accelerating its adoption among global corporate enterprises, thus CEOs and business leaders are positioned at the confluence of innovation and ethics, as it relates to implementing AI projects, in their businesses.
While technical prowess and business potential are usually the focus of conversations around AI, the ethical considerations are sometimes overlooked, especially those not immediately obvious. From a perspective that straddles the line of business leadership and technical acumen, there are five critical, yet often missed, ethical considerations in AI practices that should be part of your due diligence in starting any AI projects:
The rise of the outsmarted insider
Malware, ransomware, and phishing. These are just a few examples of software disruptors that can wreak havoc on a business and cause major personal and financial loss.
Most recently, organizations and vendors have gotten good at protecting their business from malware and infiltrations from the outside. Their security has gone up, so it's now more difficult and expensive for an outside attacker to attack this traditional way. Additionally, organizations have gotten smarter about preventing ransomware and not falling for the ransomware attack by paying the ransom. Most organizations won't pay the ransom anymore because governments don't want them to.
Ransomware, meet DRaaS: The future of disaster mitigation
Picture this: It’s 2031, and you’re chief information security officer (CISO) at a Fortune 500 company. Alongside many other innovative and emerging threats, you’re constantly battling AI-empowered bad actors. In fact, you spend the majority of your working hours combating emerging forms of ransomware. These dangerous incursions occur once every two seconds -- more than 43,000 attacks every day -- and all organizations are extremely vulnerable.
Although harsh, this scenario may soon become a reality. Threat actors are learning to use more refined tactics to infiltrate valuable consumer data, and it’s paying dividends. In 2023 alone, ransomware attacks increased by 68 percent.
8 steps to secure your business during employee offboarding
Imagine this: every year, up to 17 employees leave your 100-person company. Within a half-decade, you could be replacing your entire workforce. That's the reality facing businesses today, with the average employee turnover rate for U.S. businesses reaching 17.3 percent, Canada at 15.5 percent, and Australia at 14 percent in 2023.
Despite these turnover rates, 71 percent of organizations lack a structured offboarding process. This lack of planning can have serious security consequences, as 20 percent of businesses have experienced data breaches linked to former employees. This oversight highlights why 76 percent of IT leaders consider offboarding a significant security threat.
Microsoft is modernizing the workplace -- but where does Copilot fit in?
Whether it’s the company’s commitment to the cloud, to developing its Office suite or being a lead player in the artificial intelligence (AI) revolution, Microsoft remains the top provider of enterprise workplace tools. Despite no shortage of competition, Microsoft passed Apple earlier this year as the largest company in the world with a market capitalization of more than three trillion dollars.
Over the last few years, much has been made of Microsoft’s investment in AI. It is the lead investor in ChatGPT and has now rolled out Copilot, its own AI offering for the workforce. Copilot is an awesome tool, which leverages and trains publicly available code to provide users with suggestions and solutions to work challenges. Used properly, Copilot offers enhanced productivity and streamlined software development processes to users.
The AI advantage: Navigating the future of procurement with Generative AI
Generative AI (Gen AI) is no doubt the new “white hot” technology, with tremendous potential for transforming Source-to-Pay processes. In fact, AI can deliver cost savings of up to 40 percent according to research by Oxford College of Procurement & Supply. With its widespread adoption and inclusion in digital transformation initiatives across every industry, Gen AI has become a must-learn technology. It has the potential to improve productivity of Procurement teams tremendously to eliminate time consuming and repetitive tasks and free up time for more strategic thinking. In fact, Gen AI can reduce time spent on some procurement processes by up to 60 percent.
This enables Procurement teams to elevate their strategic impact and spend time on more creative aspects of the function that have a bigger impact.
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