Sophos has announced Sophos X-Ops, a new cross-operational unit linking SophosLabs, Sophos SecOps and Sophos AI, three established teams of cybersecurity experts at Sophos, to help organisations better defend against constantly changing and increasingly complex cyber attacks.

Sophos X-Ops leverages the predictive, real-time, real-world and researched threat intelligence from each group, which, in turn, collaborate to deliver stronger, more innovative protection, detection and response capabilities.

In addition to this announcement, Sophos is issuing 'OODA: Sophos X-Ops Takes on Burgeoning SQL Server Attacks', research about increased attacks against unpatched Microsoft SQL servers, and how attackers used a fake downloading site and grey-market remote access tools to distribute multiple ransomware families.

Sophos X-Ops identified and thwarted the attacks because the Sophos X-Ops teams combined their respective knowledge of the incidents, jointly analysed them, and took action to quickly contain and neutralise the adversaries, the company states.

Joe Levy, chief technology and product officer at Sophos, says, Modern cybersecurity is becoming a highly interactive team sport, and as the industry has matured, necessary analysis, engineering and investigative specialisations have emerged.

"Scalable end-to-end operations now need to include software developers, automation engineers, malware analysts, reverse engineers, cloud infrastructure engineers, incident responders, data engineers and scientists, and numerous other experts, and they need an organisational structure that avoids silos.

"Weve unified three globally recognised and mature teams within Sophos to provide this breadth of critical, subject matter and process expertise. Joined together as Sophos X-Ops, they can leverage the strengths of each other, including analysis of worldwide telemetry from more than 500,000 customers, industry-leading threat hunting, response and remediation capabilities, and rigorous artificial intelligence to measurably improve threat detection and response.

"Attackers are often too organised and too advanced to combat without the unique combined expertise and operational efficiency of a joint task force like Sophos X-Ops.

Speaking in March 2022 to the Detroit Economic Club about the FBI partnering with the private sector to counter the cyber threat, FBI Director Christopher Wray said, "We're disrupting three things: the threat actors, their infrastructure and their money. And we have the most durable impact when we work with all of our partners to disrupt all three together.

"Sophos X-Ops is taking a similar approach: gathering and operating on threat intelligence from its own multidisciplinary groups to help stop attackers earlier, preventing or minimising the harms of ransomware, espionage or other cyber crimes that can befall organisations of all types and sizes, and working with law enforcement to neutralise attacker infrastructure.

"While Sophos internal teams already share information as a matter of course, the formal creation of Sophos X-Ops drives forward a faster, more streamlined process necessary to counter equally fast-moving adversaries."

Michael Daniel, president and CEO Cyber Threat Alliance, comments, Effective cybersecurity requires robust collaboration at all levels, both internally and externally; it is the only way to discover, analyse and counter malicious cyber actors at speed at scale. Combining these separate teams into Sophos X-Ops shows that Sophos understands this principle and is acting on it.

Sophos X-Ops also provides a stronger cross-operational foundation for innovation, an essential component of cybersecurity due to the aggressive advancements in organised cyber crime, the company states.

By intertwining the expertise of each group, Sophos states the company is pioneering the concept of an artificial intelligence (AI) assisted Security Operations Centre (SOC), which anticipates the intentions of security analysts and provides relevant defensive actions. In the SOC of the future, Sophos states this approach can dramatically accelerate security workflows and the ability to more quickly detect and respond to novel and priority indicators of compromise.

Craig Robinson, IDC research vice president, Security Services, says, The adversary community has figured out how to work together to commoditise certain parts of attacks while simultaneously creating new ways to evade detection and taking advantage of weaknesses in any software to mass exploit it.

"The Sophos X-Ops umbrella is a noted example of stealing a page from the cyber miscreants tactics by allowing cross-collaboration amongst different internal threat intelligence groups. Combining the ability to cut across a wide breadth of threat intelligence expertise with AI assisted features in the SOC allows organisations to better predict and prepare for imminent and future attacks.

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Sophos links three expert security teams together with X-Ops - SecurityBrief Australia

The Cloud has become a must for traditional financial institutions, who are increasingly viewing it a key tool for innovating and achieving business goals.

While legacy core banking systems once provided the backbone on which the worlds financial infrastructure is built , the processing demands of digitalization and heightened customer expectations require more agility, so banks are turning to cloud-native technologies to provide next-generation customer experience, whilst enjoying lower cost, easy maintenance, flexibility, speed of deployment and security.

At 33%, Amazon Web Services (AWS) has the largest share of the cloud market and is, according to a 2017 report by the World Economic Forum, forming the backbone of the financial services ecosystem. From capital markets and insurance organizations to global investment banks, payments, retail, corporate banks, fintech and startups, AWS helps customers to unlock a wide variety of benefits enabling them to scale business models and transform product offerings.

Rowan Taylor, head of Financial Services Industry Business Development, EMEA, Amazon Web Services says financial services institutions are using AWS to optimize all aspects of their businessfrom customer-service delivery models to risk managementin order to build a foundation for long-term growth, and product differentiation.

AWS does this by helping customers to modernize and transform their organizations through access to technologies like compute, storage, and databases, through to machine learning (ML) and artificial intelligence (AI), application programme interfaces (APIs), microservices, data lakes, Internet of Things (IoT), and fully-managed data management and analytics services like Amazon FinSpacepurpose-built for the financial services industry to facilitate the storage, cataloguing, and preparation of financial industry data at scale, states Taylor. This makes it faster, easier, and more cost effective for customers to move their applications to the cloud, to accelerate innovation, and build nearly anything imaginable to transform their businesses.

Enhancing Cloud Security

Concerns over security, data residency, and privacy left financial institutions behind other sectors in moving to the cloud. A survey of 100 global banks by Accenture in 2021 found that just 8% of workloads run in the cloud. This figure is expected to double within two years, however, as banks weigh speed of execution against security and resiliency.

To assuage such fears, cloud service providers (CSPs) have invested heavily in best-in-class security, privacy, and compliance to meet the very strict levels required by financial institutions. AWS is architected to be the most flexible and secure cloud computing environment available today, Taylor says. Our core infrastructure is built to satisfy the security requirements for the military, global banks, and other high-sensitivity organizations.

To fine tune its financial services offering, AWS has poached talent from banks. Prestigious banking hires include former JPMorgan executive director in trade surveillance John Kain, now leading AWS Worldwide Business & Market Development for Banking and Capital Markets. A bevy of hires from Goldman Sachs include machine-learning wizard Roger Li Zheng, Jeff Savio, softward engineer Ishan Guru; Ranjeet Dayama, a former vice president of data engineering at Marcus [Goldman's digital consumer bank] and principal solutions architect John Butler.

AWS is not alone in viewing banks as fertile recruitment grounds: Microsoft VP of Worldwide Financial Services Bill Borden joined from Bank of America Merrill Lynch, while Howard Boville, senior VP of IBM Hybrid Cloud, was Bank of Americas former CTO.

Advanced Analytics

Last November, AWS and Goldman Sachs announced the launch of the Goldman Sachs Financial Cloud for Data. This new suite of cloud-based data and analytics solutions for financial institutions redefines how customers can discover, organize, and analyze data in the cloud, allowing them to gain rapid insights and drive more informed investment decisions, Taylor says, explaining that the collaboration with Goldman Sachs reduces the need for investment firms to develop and maintain foundational data-integration technology and lowers the barriers to entry for accessing advanced quantitative analytics across global markets. This means Goldman Sachs institutional clients will be able to accelerate time to market for financial applications, optimize their resources to focus on portfolio returns, and innovate faster.

To help financial institutions and other data-heavy clients achieve performance gains and cost savings AWS launched Graviton3 processors in December 2021. These provide up to 25% better compute performance compared to the previous generation and use 60% less power for the same performance than comparable Amazon Elastic Compute Cloud (Amazon EC2) instances, the company says. This means it is more energy and cost efficient to operate cloud services, which can help customers to be more sustainable, explains Taylor.

Looking ahead, Taylor believes open banking has the potential to transform the competitive landscape and consumer experience of the banking industry by providing third-party financial services providers with open access to consumer banking, transaction, and other financial data from banks and non-bank financial institutions using APIs. Open banking is slowly becoming a major source of innovation allowing financial services customers to build unified APIs across multiple microservices that can interact with third parties faster.

Similarly, AWS expects open banking to have an impact on corporate banking because it integrates transactional services into the Enterprise Resource Planning (ERP) systems. Treasurers can make executing transactions out of the ERP system easier, reducing the complexity of linking and exchanging data between siloed systems, Taylor says.

He predicts more financial organizations to leverage their data and use ML and AI to optimize nearly every aspect of the financial value chain, from front-of-house customer service to back-of-house processes like risk and fraud mitigation.

For example, NuData Security, a Mastercard company, leverages billions of anonymous data points and ML to identify and block account takeover attacks. NuData helps customers fight fraud and protect consumers online, and uses the ML services to improve detection of fraudulent attacks, and AWS servers to provide real-time device intelligence.

In March 2022 NatWest Group said it was seeking to leverage machine learning to become a data-driven bank. By working with AWS and applying our ML and data analytics services, NatWest Group will have the ability to derive new insights, Taylor says.

For financial institutions of all sizes, the cloud has gone way beyond commodity IT and cost savings. It now provides transformational tools to modernize quickly and stay abreast of the innovations brought by challenger banks.

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Beyond The Cloud - Global Finance

The hyperscalers and cloud builders are not the only ones having fun with the CXL protocol and its ability to create tiered, disaggregated, and composable main memory for systems. HPC centers are getting in on the action, too, and in this case, we are specifically talking about the Korea Advanced Institute of Science and Technology.

Researchers at KAISTs CAMELab have joined the ranks of Meta Platforms (Facebook), with its Transparent Page Placement protocol and Chameleon memory tracking, and Microsoft with its zNUMA memory project, is creating actual hardware and software to do memory disaggregation and composition using the CXL 2.0 protocol atop the PCI-Express bus and a PCI-Express switching complex in what amounts to a memory server that it calls DirectCXL. The DirectCXL proof of concept was talked about it in a paper that was presented at the USENIX Annual Technical Conference last week, in a brochure that you can browse through here, and in a short video you can watch here. (This sure looks like startup potential to us.)

We expect to see many more such prototypes and POCs in the coming weeks and months, and it is exciting to see people experimenting with the possibilities of CXL memory pooling. Back in March, we reported on the research into CXL memory that Pacific Northwest National Laboratory and memory maker Micron Technology are undertaking to accelerate HPC and AI workloads, and Intel and Marvell are both keen on seeing CXL memory break open the memory hierarchy in systems and across clusters to drive up memory utilization and therefore drive down aggregate memory costs in systems. There is a lot of stranded memory out there, and Microsoft did a great job quantifying what we all know to be true instinctively with its zNUMA research, which was done in conjunction with Carnegie Mellon University. Facebook is working with the University of Michigan, as it often does on memory and storage research.

Given the HPC roots of KAIST, the researchers who put together the DirectCXL prototype focused on comparing the CXL memory pooling to direct memory access across systems using the Remote Direct Memory Access (RDMA) protocol. They used a pretty vintage Mellanox SwitchX FDR InfiniBand and ConnectX-3 interconnect running at 56 Gb/sec as a benchmark against the CXL effort, and the latencies did get lower for InfiniBand. But they have certainly stopped getting lower in the past several generations and the expectation is that PCI-Express latencies have the potential to go lower and, we think, even surpass RDMA over InfiniBand or Ethernet in the long run. The more protocol you can eliminate, the better.

RDMA, of course, is best known as the means by which InfiniBand networking originally got its legendary low latency, allowing machines to directly put data into each others main memory over the network without going through operating system kernels and drivers. RDMA has been part of the InfiniBand protocol for so long that it was virtually synonymous with InfiniBand until the protocol was ported to Ethernet with the RDMA over Converged Ethernet (RoCE) protocol. Interesting fact: RDMA is actually is based on work done in 1995 by researchers at Cornell University (including Verner Vogels, long-time chief technology officer at Amazon Web Services) and Thorsten von Eicken (best known to our readers as the founder and chief technology officer at RightScale) that predates the creation of InfiniBand by about four years.

Here is what the DirectCXL memory cluster looks like:

On the right hand side, and shown in greater detail in the feature image at the top of this story, are four memory boards, which have FPGAs creating the PCI-Express links and running the CXL.memory protocol for load/store memory addressing between the memory server and hosts attached to it over PCI-Express links. In the middle of the system are four server hosts and on the far right is a PCI-Express switch that links the four CXL memory servers to these hosts.

To put the DirectCXL memory to the test, KAIST employed Facebooks Deep Learning Recommendation Model (DLRM) for personalization on the server nodes using just RDMA over InfiniBand and then using the DirectCXL memory as extra capacity to store memory and share it over the PCI-Express bus. On this test, the CXL memory approach was quite a bit faster than RDMA, as you can see:

On this baby cluster, the tensor initialization phase of the DLRM application was 2.71X faster on the DirectCXL memory than using RDMA over the FDR InfiniBand interconnect, the inference phase where the recommender actually comes up with recommendations based on user profiles ran 2.83X faster, and the overall performance of the recommender from first to last was 3.32X faster.

This chart shows how local DRAM, DirectCXL, and RDMA over InfiniBand stack up, and the performance of CXL versus RDMA for various workloads:

Heres the neat bit about the KAIST work at CAMELab. No operating systems currently support CXL memory addressing and by no operating systems, we mean neither commercial-grade Linux or Windows Server do, and so KAIST created the DirectCXL software stack to allow hosts to reach out and directly address the remote CXL memory using load/store operations. There is no moving data to the hosts for processing data is processed from that remote location, just as would happen in a multi-socket system with the NUMA protocol. And there is a whole lot less complexity to this DirectCXL driver than Intel created with its Optane persistent memory.

Direct access of CXL devices, which is a similar concept to the memory-mapped file management of the Persistent Memory Development Toolkit (PMDK), the KAIST researchers write in the paper. However, it is much simpler and more flexible for namespace management than PMDK. For example, PMDKs namespace is very much the same idea as NVMe namespace, managed by file systems or DAX with a fixed size. In contrast, our cxl-namespace is more similar to the conventional memory segment, which is directly exposed to the application without a file system employment.

We are not sure what is happening with research papers these days, but people are cramming a lot of small charts across two columns, and it makes it tough to read. But this set of charts, which we have enlarged, shows some salient differences between the DirectCXL and RDMA approaches:

The top left chart is the interesting one as far as we are concerned. To read 64 bytes of data, RDMA needs to do two direct memory operations, which means it has twice the PCI-Express transfer and memory latency, and then the InfiniBand protocol takes up 2,129 cycles of a total of 2,705 processor cycles during the RDMA. The DirectCXL read of the 64 bytes of data takes only 328 cycles, and one reason it can do this is that the DirectCXL protocol converts load/store requests from the last level cache in the processor to CXL flits, while RDMA has to use the DMA protocol to read and write data to memory.

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KAIST Shows Off DirectCXL Disaggregated Memory Prototype - The Next Platform

How Does VDI Compare To Desktop as a Service?

Like desktop virtualization, Desktop as a Service grants workers remote access to a virtual iteration of a desktop that lives elsewhere. A notable difference is that with DaaS, virtual desktops are made available through the cloud by a third-party service provider not a companys self-managed servers supported by virtualization technology from providers such as Citrix, VMware, Avaya and others.

The first requirement of VDI is to ensure that the infrastructure is in place to create the servers and data centers that will host virtual machines. The VMs then live on the servers with a businesss chosen operating system and apps. All of this is the responsibility of the organization deploying desktop virtualization, and should be overseen by a skilled IT department, which will manage hardware, software, security updates and patches.

Remote employees can connect to a virtual desktop using a tablet, smartphone, desktop or laptop that has access to the companys network. Often, thin clients or zero clients computers that have no onboard operating system or storage are used because of their cost-effectiveness and suitability for remote work.

Virtual desktops come in two forms: A persistent virtual desktop is a singular instance that preserves an employees personalized applications, data and settings from login to login. A nonpersistent virtual desktop gives users a clean slate each time they log in for work.

DaaS shares some commonalities with desktop virtualization. Employees still access the virtual iteration of a persistent or nonpersistent desktop using a device of their choice, but the virtual machines are not hosted on on-premises servers. Instead, they are managed offsite by a third-party cloud-service provider such as Microsoft Azure, Google Cloud or Amazon Web Services and accessed through an application or web browser.

After companies choose a provider, partner and subscription plan, the setup process is quick. We can be up and running in a matter of minutes or hours compared with the days or weeks that it could take if you had to procure hardware so that you could install that software on-premises, says Sachin Sharma, director of product marketing for VMware Horizon, the companys virtual desktop and DaaS offering.

Spinning VMs up or down is quick and easy, and has proved especially helpful for companies with seasonal workers or contractors who require temporary access, or companies that experience fluctuations in their workforce. Once a company is up and running with DaaS, its third-party provider oversees all maintenance, security, storage and upgrades.

LEARN MORE: Discover how VMware is making virtualization easy for businesses.

VDI and DaaS share some clear benefits.

They both offer workers a consistent user experience, from any location, that replicates the one they would have in a headquarters or branch office. It can restore your work environment, and you can have that be consistent regardless of location, device or connectivity, says Lotz. As more companies or employees migrate to hybrid models, that consistency will prove helpful.

VDI and DaaS also both offer security benefits. The increased endpoints that result from further adoption of hybrid work also increases a companys vulnerability to cyberattacks and phishing. But with a virtualized infrastructure, a server is the only entry point for an attack and is typically well protected. Your data lives inside the firewall instead of being scattered in somebody's end-user access device, says Sharma.

Another bonus for those adopting virtualized desktop experiences is a lighter load for IT staff. Whether its within the company or through a third-party provider, managing everything within one place, instead of in a distributed fashion, really helps IT reduce the time they spend in deploying patches, updating machines and updating VMs, says Sharma.

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How VDI and DaaS Help Companies Thrive in a World of Hybrid Work - BizTech Magazine

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