Daily Tech Digest - January 31, 2022

Driving digital transformation: The power of blockchain

While the BFSI sector is at the forefront of blockchain adoption, industries like healthcare can also benefit from DLT. Tech Mahindra recently partnered with StaTwig to manage the traceability of the global COVID-19 vaccine supply through blockchain technology. In addition to improving transparency across the supply chain, the VaccineLedger solution also helps prevent issues such as expired vaccines being mistakenly distributed and used. With blockchain technology, health institutions have complete traceability of the vaccination’s journey from sourcing to the hospital floor. ... Sectors like manufacturing are also finding value in blockchain technology. With blockchain, manufacturers and suppliers can trace components and raw materials through the entire remanufacturing process, ensuring that parts can be traced back to a point of origin in case of a product recall or malfunction. TradeLens, for example, a blockchain network for global shipments, has been adopted by dozens of global carriers, customs authorities, freight forwarders, and port authorities. 

Meet Cadence: Workflow Engine for Taming Complex Processes

Cadence is an open source fault-oblivious stateful code platform and workflow engine specifically designed to solve this development challenge. Originally developed and open-sourced by Uber — and now adopted and developed by an increasing number of companies including Uber and Instaclustr — Cadence can abstract away the most difficult complexities associated with developing high-scale distributed applications. Cadence preserves the entire state of an application in durable virtual memory not associated with any specific process. The stored application state includes all call parameters and returned results for user-defined activities. It then uses that information to catch up and replay workflows that get interrupted. Cadence has libraries that enable developers to create and coordinate workflows using popular languages such as Java, Go, Python and Ruby. Cadence services, such as workers, are largely stateless and leverage a data store for task/workflow persistence. Supported storage options include open source Cassandra and MySQL/PostgreSQL, and an adapter is available for any database featuring multi-row single shard transactions. 

Extracting value from unstructured data with intelligent data management

The explosion of data is predicted to reach 175 zettabytes by 2025 and is increasingly stored across disparate, hard-to-access, silos. Visibility in the current ecosystem is poor. This growth of data has been fueled by market forces that look to capitalise on the value that can be extracted from the valuable resource. This is mirrored by the dramatic shift to the cloud and edge. An estimated 90% of this data is unstructured information, like text, video, audio, web server logs, social media and more. And, all this data can’t be moved to a central data store or processed in its entirety. Now, unstructured data management, for data-heavy organisations, is an enterprise IT priority. They need to identify, index, tag and monetise this information. Komprise, an intelligent data management and mobility company, says it’s offering can solve this challenge: “We dramatically save our customers money by tiering cold data to the cloud, in a transparent, native AI/ML ready solution that doesn’t sit in front of the hot data,” said Kumar Goswami, CEO and co-founder.

How to Create a Network Proxy Using Stream Processor Pipy

Every pipeline gets access to the same set of variables across a Pipy instance. In other words, contexts have the same shape. When you start a Pipy instance, the first thing you do is to define the shape of the context by defining variable(s) and their initial values. Every root pipeline clones the initial context you define at the start. When a sub-pipeline starts, it either shares or clones its parent’s context, depending on which joint filter you use. For instance, a link filter shares its parent’s context while a demux filter clones it. To the scripts embedded in a pipeline, these context variables are their global variables, which means that these variables are always accessible to scripts from anywhere as long as they live in the same script file. This might seem odd to a seasoned programmer because global variables usually mean they are globally unique. You have only one set of these variables, whereas in Pipy we can have many sets of them (aka contexts) depending on how many root pipelines are open for incoming network connections and how many sub-pipelines clone their parents’ contexts.


More Security Flaws Found in Apple's OS Technologies

Apple said it has implemented an improved validation mechanism in macOS Monterey 12.2 to address the issue. The company has credited two other researchers — one from Trend Micro and another anonymous individual — for reporting the flaw to the company. Meanwhile, one of the two zero-day flaws (CVE-2022-22587) that Apple fixed this week involved IOMobileFrameBuffer, a kernel extension related to a device's frame buffer. The memory corruption bug allows attackers to run arbitrary code at the kernel level and is likely being actively exploited in the wild already, Apple said. The bug impacts macOS Monterey, iPhone 6 and later, all iPad Pro models, and several other Apple mobile devices. "CVE-2022-22587 targets the macOS kernel, and compromising it can give the attacker root privileges," Levin says. "However, SIP comes into play exactly for this kind of exploit." The flaw is one of several serious vulnerabilities that researchers have uncovered in IOMobileFrameBuffer recently. Other examples include CVE-2021-30883, a zero-day code execution bug that Apple patched last October amid active exploit activity, and CVE-2021-30807, which Apple fixed last July.

Why vulnerability scanners aren’t enough to prevent a ransomware attack on your business

Vulnerability scanners are needed in most security toolkits. However, reactively detecting and alerting organizations to the presence of vulnerabilities means companies cannot keep up. Vulnerability scanners are akin to equipping security teams with an alarm system that’s constantly flashing lights and sounding sirens everywhere – so many alerts at once that it overwhelms security operations. Given the significant transitions many organizations’ digital infrastructures are undergoing, along with the complex and quickly evolving threat landscape, a scan-and-patch approach reliant on vulnerability scanners as a first line of defense is simply insufficient to protect organizations from current and future threats. As such, relying on vulnerability scanners is a dangerous strategy in the modern era, when vulnerabilities are actively and regularly weaponized for successful ransomware attacks. The dynamic shift in the threat landscape requires an equally dynamic shift in how organizations approach their cybersecurity programs.

Shipment-Delivery Scams Become the Favored Way to Spread Malware

Researchers attributed a couple of factors behind the ramp-up in scams related to package delivery. Spoofing DHL certainly made sense in the fourth quarter of last year during the busy holiday-shopping season, noted Jeremey Fuchs, cybersecurity researcher and analyst from Avanan, in a report on the latest DHL-related scam, published Thursday. “Now, hackers are taking advantage of this, by attaching malware to a DHL spoof,” which will likely attract attention from a recipient in part because of its use of a trusted company, he wrote in the report. Moreover, shipping delays and supply-chain issues have become commonplace during the pandemic, which also has spurred a massive increase in people working remotely from home. Attaching a malicious invoice link to a fake USPS missed-delivery notification, then – as threat actors did in the recently discovered Trickbot campaign – would be an attractive lure for potential victims accustomed to receiving these types of emails, according to Cofense. “With the supply-chain delays, receiving a notification that a delivery attempt was missed can lead to frustration and entice the recipient to open the invoice link to further investigate,” Cofense PDC researchers Andy Mann and Schyler Gallant wrote in the report.

Do machines feel pain?

“Do machines feel pain?” is a very philosophical question, says Anuj Gupta, Head of AI, Vahan. “Some robots react when hit. Does it mean they ‘feel’ pain – no. Their reaction is a combination of sensors and software. It is like a toy that reacts to one’s hand gestures. Currently, machines can’t feel anything. They can be programmed to trick humans by simulating human emotions, including pain.” Few years ago, scientists from Nanyang Technological University, Singapore, developed ‘mini-brains’ to help robots recognise pain and activate self-repair. The approach embeds AI into the sensor nodes, connected to multiple small, less-powerful processing units that act like ‘mini-brains’ on the robotic skin. Then, combining the system with self-healing ion gel material, robots, when damaged, can recover their mechanical functions without human intervention. Explaining the ‘mini-brains’, co-author of the study, Associate Professor Arindam Basu, from the School of Electrical & Electronic Engineering of the university, says, “If robots have to work with humans, there is a concern if they would interact safely. To ensure a safe environment, scientists worldwide have been finding ways to bring a sense of awareness to robots, including feeling pain, reacting to it, and withstanding harsh operating conditions.

AI storage: a new requirement for the shift in computing and analytics

Traditionally, DDN Storage has focused on traditional data storage for unstructured data and big data in enterprise, government and academic sectors. Now, it is redefining the imperatives that are driving it as a company, focusing on AI storage, with its solution, AI, which is at the heart of its growth strategy. In action, over the last two years DDN has acted as the core backend storage system for NVIDIA to increase performance & scale and flexibility to drive innovation. NVIDIA commands “nearly 100%” of the market for training AI algorithms and has multiple AI clusters, according to Karl Freund, analyst at Cambrian AI Research. Following this success, DDN is powering the UK’s most powerful supercomputer, Cambridge 1, which went live in 2021 and is focused on transforming AI-based healthcare research. The AI storage vendor is also working with Recursion, the drug discovery company. “Our at-scale data needs require fast ingest, optimised processing and reduced application run times,” said Kris Howard, Systems Engineer at Recursion. Working with DDN, the drug discovery company achieved up to 20x less costs and raised the possibilities for accelerating the drug discovery pipeline with new levels of AI capability.

Chaos Engineering Has Evolved Since Netflix's Chaos Monkey Days

Chaos engineering or failure injection does not necessarily need to kill things or break services. Jason mentioned introducing latency and seeing how your application will behave. It's a normal situation when the database becomes slow because either there may be saturation of network because someone else all of a sudden starts using the same channel to your database. Or maybe it becomes slower because the indexes in this database are not optimized and things like that. When we develop a certain feature, we often think under the condition that everything will be, you know, nice and green and that it would be sunny with unicorns and things like that. However, simply looking at how your system will behave by increasing the latency between components already would be like a big eye-opener. This is especially true regarding how certain things are configured in your system or some of the requests you think need to be synchronous. And when you're testing this on a unit or integration test, you see the response time would be very quick.

Quote for the day:

"Leaders must see the dream in their mind before they will accomplish the dream with their team." -- Orrin Woodward

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