The global annual cost of cyber crime is estimated to be $6 trillion per year, or 1% of the Global GDP. At the same time, cloud computing is rapidly becoming the dominant model used by business to host data and applications, and to develop new services. Cloud computing dominates, but security is a challenge. "As organizations continue to increase their reliance on the cloud to centralize their operations, cloud security solutions are seeing tremendous growth and adoption. In addition, the need to strengthen defenses in advance of macroeconomic changes that could result in an increase in financially motivated attacks, boosts the demand for cybersecurity software, especially for cloud environments that hackers may find more convenient to penetrate", according to Erkang Zheng, founder and CEO of JupiterOne.
As multiple industries shift more into the world of cloud computing, talks of Artificial Intelligence (AI) integration in order to enhance cloud performance has continued at a dramatic pace. Combining both AI and cloud technology together, is beneficial to varying degrees, nevertheless, there is still some further progress to be made across the substantial challenges that technical developers are facing for a more cohesive integration. Cloud computing alone allows companies to be more flexible whilst simultaneously providing economic value when hosting data and applications on the cloud. AI-powered analytical data insights plays an essential role in its enhanced capabilities in data management However, it begs the question, can AI and cloud unification streamline data efficiently and what other benefits can arise from this integration? Due to the financial and personal sensitivity in which organizations carry, thoughts also turn to the important question of integration effectiveness and more specifically how well it can protect privacy whilst companies are continually at risk of a potentially serious cybersecurity breach, especially because an increased rate of workforces are now working from home remotely.
You might think it foolhardy to make predictions about something that changes as furiously fast as emerging technology. Driven by massive investments, competing for a market that appears limitless, thousands of companies innovate constantly, sometimes at cross purposes. Yet we are human, after all, so we can't resist peering into the unknowable future and proclaiming, "Yes, this is what's ahead." Plus it's that time of year: in January we are (we hope) imbued with a fresh energy that allows us to accurately assess the year ahead. Not that all annual predictions are mere guesses. Clearly, the tech forecasters below are top practitioners who are close to their respective sectors. They're the experts who have long labored in cloud, AI, security, edge, data analytics, digital transformation, accruing years of deep market experience. If anyone can foresee the future, it's these seasoned thought leaders.
As a result, all major cloud providers are either offering or promising to offer Kubernetes options that run on-premises and in multiple clouds. While Kubernetes is making the cloud more open, cloud providers are trying to become "stickier" with more vertical integration. From database-as-a-service (DBaaS) to AI/ML services, the cloud providers are offering options that make it easier and faster to code. Organizations should not take a "one size fits all" approach to the cloud. For applications and environments that can scale quickly, Kubernetes may be the right option. For stable applications, leveraging DBaaS and built-in AI/ML could be the perfect solution. For infrastructure services, SaaS offerings may be the optimal approach. The number of options will increase, so create basic business guidelines for your teams.
It is a near-future tech boon that is impossible to overstate as 5G's impact on the ability to create, store, use, and share data will be felt across most business sectors, especially those using the Internet of Things (IoT), AI, and machine learning. Over the past ten years, cloud computing has been an integral part of maintaining healthy IT infrastructures as businesses demand better, quicker collaboration and productivity from their distributed workforce. Increasingly safer and scalable, the cloud has been a remarkable workaround for universally slow network speeds -- allowing the easy transfer and sharing of large files between devices while also providing backup and recovery services to safeguard that data in case of a cybersecurity attack or natural disaster. To meet new demand pressures, Furiom suggests that edge computing's infrastructure will need enhancements in concert with data centers, virtualization providers, and network integration companies. As consumer and enterprise bandwidth needs grow, networks are harnessing 5G to rapidly move toward this software-defined architecture to meet operational and application demands. It is a near-future tech boon that is impossible to overstate as 5G's impact on the ability to create, store, use, and share data will be felt across most business sectors, especially those using the Internet of Things (IoT), AI, and machine learning.
The advent of technology has revolutionized how the world functions. People and businesses alike have adopted modern technology to enhance their prospects and lifestyle. The business that is yet to adopt technology in its functions does not get favor from customers. Hence, they are overtaken by their competitors who have already adopted it. Advanced technologies like IoT (Internet of Things), Machine Learning, Artificial Intelligence, etc. have managed to overpower outdated systems. However, it is the current Covid-19 pandemic that has compelled almost all businesses to go online and adopt the top technology trends.
Antigena Network is the world's leading Autonomous Response technology for the enterprise. Powered by self-learning cyber AI, Antigena Network instantly interrupts attacks across cloud services, IoT and the corporate network with surgical precision, even if the threat is novel or highly targeted. This tool marks Darktrace's active self-defense tool. Intercept X is the industry's most comprehensive endpoint protection built to stop the widest range of threats. Intercept X Advanced combines the capabilities of Intercept X and Central Endpoint into a single solution and single agent.
According to IDG's 2020 Cloud Computing Study, 92% of organizations have at least some sort of cloud footprint in regard to their IT environment. Therefore, traditional cloud security approaches must evolve to keep up with the dynamic infrastructure and challenges that cloud environments present – most notably, the inundation of data insights generated within the cloud. More than one-third of IT security managers and security analysts ignore threat alerts when the queue is full. This is a common issue that is driving the high demand for machine learning-based analytics, as it helps security teams sift through massive amounts of data to prioritize risks and vulnerabilities and make more informed decisions. However, a word of caution when using machine learning-based technology: the age-old garbage-in, garbage-out applies to security-focused machine learning engines.
International Business Machines (IBM) - Get Report and Advanced Micro Devices (AMD) - Get Report said they began a development program focused on cybersecurity and artificial intelligence. The development agreement will build on "open-source software, open standards, and open system architectures to drive confidential computing in hybrid cloud environments," the companies said in a statement. The agreement also will "support a broad range of accelerators across high-performance computing and enterprise critical capabilities, such as virtualization and encryption," they said. AMD, Santa Clara, Calif., is one of the world's biggest chipmakers and is thriving. IBM, the storied Armonk, N.Y., technology services company, has struggled to regain the glory of its past, when it led the computer-making industry.
Las Vegas's search for an adaptive security solution led it to deploy Darktrace AI across its enterprise, cloud and industrial networks. Background In recent years, Las Vegas has become a prototypical Smart City. As riders glide down the Strip aboard the first completely autonomous shuttle ever deployed on a public roadway, they are unlikely to notice much trash on the sidewalk – the city's surveillance cameras stream to an AI service that directs clean-up crews towards concentrations of litter. And when rush hour approaches, its passengers can rest assured that an array of connected sensors are helping officials anticipate gridlock at busy intersections. But while smart infrastructure enables Las Vegas to achieve new heights of efficiency, conventional security tools are largely ill-equipped to defend the hybrid cloud and industrial networks that power this infrastructure.