The malware uses the infected computer to replicate itself in a network and then uses the contacts from the victim's Microsoft Outlook account to send additional spam emails to more potential victims, the report notes. "People are more likely to trust messages from people they know than from random internet accounts," Rajesh Nataraj, a researcher with Sophos Labs, notes. The malware contains code that generates email messages with dynamically added malicious files and subject lines pulled up from its database with phrases such as: "The Truth of COVID-19," "COVID-19 nCov Special info WHO" or "HEALTH ADVISORY: CORONA VIRUS," according to the report. Researchers found that Lemon Duck malware exploits the SMBGhost vulnerability found in versions 1902 and 1909 of the Windows 10 operating system. Exploiting this vulnerability allows for remote code execution. Microsoft fixed this bug in March, but unpatched systems remain at risk. The code used in Lemon Duck also leverages the EternalBlue vulnerability in Windows to help the malware spread laterally through enterprise networks.
While the concept of AI-enabled automated urban planning is appealing, the researchers quickly encountered three challenges: how to quantify a land-use configuration plan, how to develop a machine learning framework that can learn the good and the bad of existing urban communities in terms of land-use configuration policies, and how to evaluate the quality of the system’s generated land-use configurations. The researchers began by formulating the automated urban planning problem as a learning task on the configuration of land-use given surrounding spatial contexts. They defined land-use configuration as a longitude-latitude-channel tensor with the goal of developing a framework that could automatically generate such tensors for unplanned areas. The team developed an adversarial learning framework called LUCGAN to generate effective land-use configurations by drawing on urban geography, human mobility, and socioeconomic data. LUCGAN is designed to first learn representations of the contexts of a virgin area and then generate an ideal land-use configuration solution for the area.
As enterprises increasingly shift to a hybrid-cloud model, IBM is working with AT&T and other operators to allow businesses to deploy applications or workloads wherever they see fit, Canepa said. “That includes now what we’re highlighting here, the mobile edge environment that comes with this, the emerging 5G world.” Because enterprises are no longer restricted to a single cloud architecture on premises, they’re gaining access to a larger pool of potential innovation sources, he explained. This extends to mobile network operators’ infrastructure as well. “Up until this point, the networks inside the telcos were very kind of structured environments, hardwired, specialized equipment that was really good at what it did, but did a fairly limited set of things,” Canepa said. “What we’re evolving to now is truly a hybrid-cloud environment where that network itself becomes a platform. And then the ability to extend that platform to the edge creates a whole new opportunity to create new insights as a service, new applications, and solutions that can be deployed in that environment.”
The most challenging was the lack of database like transactions in Big Data frameworks. To cover for this missing functionality we had to develop several routines the performed the necessary checks and measures. However, the process was cumbersome, time-consuming and frankly error-prone. Another issue that use to keep me awake at night was the dreaded Change Data Capture (CDC). Databases have a convenient way of updating records and showing the latest state of the record to the user. On the other hand in Big Data we ingest data and store them as files. Therefore, the daily delta ingestion may contain a combination of newly inserted, updated or deleted data. This means we end up storing the same row multiple times in the Data Lake. ... Developed by Databricks, Delta Lake brings ACID transaction support for your data lakes for both batch and streaming operations. Delta Lake is an open-source storage layer for big data workloads over HDFS, AWS S3, Azure Data Lake Storage or Google Cloud Storage. Delta Lake packs in a lot of cool features useful for Data Engineers.
“One of the most often overlooked or under budgeted issues of IoT scaling is not the initial build out of the system which is typically well planned for, but the long-term maintenance and support of what can quickly become a huge network of devices that are often deployed in difficult to reach locations,” he said. “That complexity requires a resilient network to ensure that all of these IoT devices, connected via an aggregation point, can be securely managed and updated to extend their lifespan. Where edge compute is necessary due to the density of connected IoT devices, it is also advisable to provide scalable, secure and highly reliable remote management for all the IoT network infrastructure that provides a fast and predictable way to recover from failures. “An independent management network should provide a secure alternate access path, including the ability to quickly re-deploy any software and or configs automatically onto connected equipment if they need to be re-built, ideally without having to send an engineer to site. In general networking terms, it is very important to ensure that the IoT gateways and edge compute equipment stack is actively monitored and that it is designed with resiliency in mind.”
The first step in every successful data governance effort is the establishment of a common vision and mission for data and its governance across the enterprise. The vision articulates the state the organization wishes to achieve with data, and how data governance will foster reaching that state. Through the skills of a specialist in data governance and using the techniques of facilitation, the senior business team develops the enterprise’s vision for data and its governance. All of the subsequent activities of any data governance effort should be formed by this vision. Visioning offers the widest possible participation for developing a long-range plan, especially in enterprise-oriented areas such as data governance. It is democratic in its search for disparate opinions from all stakeholders and directly involves a cross-section of constituents from the enterprise. Developing a vision helps avoid piecemeal and reactionary approaches to addressing problems. It accounts for the relationship between issues, and how one problem’s solution may generate other problems or have an impact on another area of the enterprise. Developing a vision at the enterprise level allows the organization to create a holistic approach to setting goals that will enable the it to realize the vision.
Runner V2 has a more efficient and portable worker architecture rewritten in C++, which is based on Apache Beam's new portability framework. Moreover, Google packaged this framework together with Dataflow Shuffle for batch jobs and Streaming Engine for streaming jobs, allowing them to provide a standard feature set from now on across all language-specific SDKs, as well as share bug fixes and performance improvements. The critical component in the architecture is the worker Virtual Machines (VM), which run the entire pipeline and have access to the various SDKs.... If features or transforms are missing for a given language, they must be duplicated across various SDKs to ensure parity; otherwise, there will be gaps in feature coverage and newer SDKs like Apache Beam Go SDK will support fewer features and exhibit inferior performance characteristics for some scenarios. Currently, Dataflow Runner v2 is available with Python streaming pipelines and Google recommends developers to test the new Runner out with current non-production workloads before enabling it by default on all new pipelines.
The cryptocurrency stolen from the two exchanges was later traded for other types of virtual currency, such as bitcoin and tether, to launder the funds and obscure its transaction path, the Justice Department says. The civil lawsuit relates to a criminal case that the Justice Department brought against two Chinese nationals for their alleged role in laundering $100 million in cryptocurrency stolen from exchanges by North Korean hackers in 2018. The two suspects, Tian Yinyin, and Li Jiadong, are each charged with money laundering conspiracy and operating an unlicensed money transmitting business. The two also face sanctions from the U.S. Treasury Department. U.S. law enforcement officials and intelligence agencies, including the Cybersecurity and Infrastructure Security Agency, believe these types of crypto heists are carried out by the Lazarus Group, a hacking group collective also known as Hidden Cobra. Earlier this week, CISA, the FBI and the U.S. Cyber Command warned of an uptick in bank heists and cryptocurrency thefts since February by a subgroup of the Lazarus Group called BeagleBoyz
The goal of data management is to facilitate a holistic view of data and enable users to access and derive optimal value from it—both data in motion and at rest. Along with other data management solutions, DataOps leads to measurably better business outcomes: boosted customer loyalty, revenue, profit, and other benefits. The trouble with achieving these goals lies in part in businesses not understanding how to translate the information they hold into actionable outcomes. Once a business has toiled all the information it holds to unearth valuable insights, they can then enact changes or implement efficiencies to yield returns. ... Data security is consistently rated among the highest concerns and priorities of IT management and business leaders alike. But we can’t say that technology is always the answer in ensuring that data is securely and safely stored. A key challenge is getting alignment across organizations on the classification of data by risk and on how data should be stored and protected. That makes security a human issue; the tech is often easy. Two thirds of survey respondents report insufficient data security, making data security an essential element of any discussion of efficient data management.
More boards are assigning cybersecurity oversight responsibilities to a committee. Eighty-seven percent of companies this year have charged at least one board-level committee with cybersecurity oversight, up from 82% last year and 74% in 2018. Audit committees remain the primary choice for those responsibilities. This year 67% of boards assigned cybersecurity oversight to the audit committee, up from 62% in 2019 and 59% in 2018. Last year we observed a significant increase in boards assigning cybersecurity oversight to non-audit committees, most often risk or technology committees, (28% in 2019 up from 20% in 2018), but that percentage dropped this year (26% in 2020). A minority of boards, 7% overall, assigned cyber responsibilities to both the audit and a non-audit committee. Among the boards assigning cybersecurity oversight responsibilities to the audit committee, nearly two-thirds (65%) formalize those responsibilities in the audit committee charter. Among the boards assigning such responsibilities to non-audit committees, most (85%) include those responsibilities in the charter.
Identification of director skills and expertise
Identification of director skills and expertise
Quote for the day:
"For true success ask yourself these four questions: Why? Why not? Why not me? Why not now?" -- James Allen