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Will cryptocurrency mining soon saturate AWS, Microsoft Azure and Google Cloud?

The Last Watchdog

On the face, the damage caused by cryptojacking may appear to be mostly limited to consumers and website publishers who are getting their computing resources diverted to mining fresh units of Monero, Ethereum and Bytecoin on behalf of leeching attackers. Usually people would pay maybe a thousand dollars for the data. Bilogorskiy.

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How process mining improves IT service management to save your business time and money

IBM Big Data Hub

Auto-discovery tools like process mining — a tool gaining popularity with organizations — does just that. 36% of respondents polled primarily use automated discovery tools like process mining, which improve their ability to analyze processes objectively and at scale.

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Cryptominer ELFs Using MSR to Boost Mining Process

Security Affairs

The Uptycs Threat Research Team recently observed Golang-based worm dropping cryptominer binaries which use the MSR (Model Specific Register) driver to disable hardware prefetchers and increase the speed of the mining process by 15%. This is done to boost the miner execution performance, thereby increasing the speed of the mining process.

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Microsoft Defender uses Intel TDT technology against crypto-mining malware

Security Affairs

Cryptojacking malware allows threat actors to secretly mine for cryptocurrency abusing computational resources of the infected devices. The Intel TDT technology allows sharing heuristics and telemetry with security software that could use this data to detect the activity associated with a malicious code. Pierluigi Paganini.

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Using Data De-Identification to Protect Companies

Data Matters

Many companies hope to benefit from amassing large amounts of data by mining it for market insights, creating internal business models, and supporting strategic, data-driven decisions. One way that businesses can mitigate these risks is to de-identify the data they collect and store. litigation discovery obligations.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Accelerating your transition from traditional BI to advanced analytics with data intelligence

Collibra

The term “advanced analytics” gained widespread recognition in the fields of data analysis and business intelligence (BI) during the early 2000s. Today, advanced analytics encompasses a broad array of techniques and methodologies used to extract deep insights from data. Data quality scores are displayed in Collibra.