The rise of graph-structured data has driven interest in graph learning and synthetic data generation. While successful in text and image domains, synthetic graph generation remains challenging -- especially for real-world graphs with complex, heterogeneous schemas. Existing research has focused mostly on homogeneous structures with simple attributes, limiting their usefulness and relevance for application domains requiring semantic fidelity. In this research, we introduce ProvCreator, a synthetic graph framework designed for complex heterogeneous graphs with high-dimensional node and edge attributes. ProvCreator formulates graph synthesis as a sequence generation task, enabling the use of transformer-based large language models. It features a versatile graph-to-sequence encoder-decoder that 1. losslessly encodes graph structure and attributes, 2. efficiently compresses large graphs for contextual modeling, and 3. supports end-to-end, learnable graph generation. To validate our research, we evaluate ProvCreator on two challenging domains: system provenance graphs in cybersecurity and knowledge graphs from IntelliGraph Benchmark Dataset. In both cases, ProvCreator captures intricate dependencies between structure and semantics, enabling the generation of realistic and privacy-aware synthetic datasets.

Less than a month ago, OpenAI released its Windows app for ChatGPT, allowing you to use the AI chatbot on a desktop PC without running it in a browser tab. But it was an "early version" reserved for paid subscribers, so many users were left out in the cold. Fortunately, there is a way to use ChatGPT on Windows without paying for a premium plan -- if you get the nightly version of Windows Terminal. Windows Terminal is a free app provided by Microsoft that's basically a faster, more modern, more powerful, and more efficient alternative to Command Prompt but still more accessible and easier to use than the built-for-power-users PowerShell. The regular version of Windows Terminal is available on the Microsoft Store, but the nightly version -- which you'll need to access the newly implemented support for both ChatGPT and GitHub Copilot -- can only be downloaded on the project's GitHub page.

As technology continues to evolve, so do cyber threats. In 2021 alone, cybercrime caused losses of around $1 trillion worldwide and is expected to grow to 10.5 trillion annually by 2025. To stay ahead of attackers and strengthen defenses against them, cybersecurity companies are seeking ways to enhance technology. One promising technology that's becoming increasingly popular in this space is ChatGPT – an emerging standard that promises improved efficiency when handling sensitive data. ChatGPT has the potential to revolutionize cybersecurity by providing a faster and more efficient method for analyzing data, detecting threats, and responding to incidents.

In recent months, we observed an increase in the number of malicious campaigns that use Google Advertising as a means of distributing and delivering malware. At least two different stealers, Rhadamanthys and RedLine, were abusing the search engine promotion plan in order to deliver malicious payloads to victims' machines. They seem to use the same technique of mimicking a website associated with well-known software like Notepad and Blender 3D. The treat actors create copies of legit software websites while employing typosquatting (exploiting incorrectly spelled popular brands and company names as URLs) or combosquatting (using popular brands and company names combined with arbitrary words as URLs) to make the sites look like the real thing to the end user--the domain names allude to the original software or vendor. The design and the content of the fake web pages look the same as those of the original ones.

Protecting sensitive data is an essential part of security in cloud computing. However, only specific privileged individuals have access to view or interact with this data; therefore, it is unscalable to depend on these individuals also to maintain the software. A solution to this is to allow non-privileged individuals access to maintain these systems but mask sensitive information from egressing. To this end, we have created a machine-learning model to predict and redact fields with sensitive data. This work concentrates on Azure PowerShell, showing how it applies to other command-line interfaces and APIs. Using the F5-score as a weighted metric, we demonstrate different transformation techniques to map this problem from an unknown field to the well-researched area of natural language processing.

The more a feature decreases the impurity, the more important the feature is. In random forests, the impurity decrease from each feature can be averaged across trees to determine the final importance of the variable.

Cortana may have stopped offering consumer services, but that doesn't mean that Microsoft's virtual assistant is pushing up the virtual daisies in some corner of the metaverse. Instead, she's got a new job, offering a natural language interface into Microsoft 365 services. One of those services is ideal for the new world of hybrid work, where we spend much of our time trying to schedule both physical and online meetings. With meetings needing to be coordinated across internal and external calendars, setting up the average meeting now takes anything up to 30 minutes. Each meeting you're trying to organize adds up to quite a bite out of the workday, a hefty distraction that takes you out of your workflow.

Pro PowerShell for Database Developers helps you master PowerShell application development by continuing where other books leave off. There are no "Hello World" functions here, just real-world examples that get down to business. Develop and deploy database and ETL applications in a reusable framework. Read from any data source and write to any destination. Pro PowerShell for Database Developers shows how to dive into the PowerShell environment and customize it to your needs.

Update, 05/27/2020: Microsoft launched the May 2020 update on May 27, through manual download first, or you can just wait for Microsoft to push it to your PC. Our review of Microsoft's Windows 10 20H1 update--also known as version 2004, or the Windows 10 May 2020 Update--shows an OS focused primarily on building out existing features, rather than launching new ones. Some scaffolding is still apparent in tweaks to Your Phone, and especially Cortana. Microsoft has further polished Task Manager, Settings, and Game Bar, however, and isn't afraid to serve niche audiences with upgrades to the Windows Subsystem for Linux and the related Terminal app. As in the past, we've based our review on the Insider builds of the Windows 10 May 2020 Update, beginning with the major features and working through to its minor additions.

PowerShell, first and foremost, is a scripting language. It's a powerful tool to create and run scripts, but it can assist in data analysis. One of PowerShell's greatest capabilities is to convert all sorts of data into a common framework: objects. Whether it is a CSV file, a REST API or SQL, all data types are converted into PowerShell objects, which then can be analyzed by a common method. When admins connect PowerShell to data sources such as SQL databases, they can use the tool to orchestrate data manipulation, and even some machine learning algorithms.