Data Doomsday, Cyberattack, Data Mesh, Geospatial Data, Personal Data, AI-ML & Automobile

This week, we begin with an article about the EU’s decision impacting a large number of businesses and organizations in Europe and the U.S. over data transfers. Next is a piece that talks about the lazy nature of fraudsters, that they can sign up for a free email account but will not spend the time to create a complete online profile. Then, we have a story outlining the benefits of data mesh over data lake & data warehouse in producing and consuming data sets. Following that, we have an essay exploring how businesses can reap the potential benefits of geospatial data. Next is an article describing the project based on threshold computing causing the information leakage to be random, thus preventing the reveal of any actual side-channel information. Lastly, we have a piece tracing the use of AI & ML in minimizing and resolving various issues, particularly in the areas of EV adoption and producing environmentally friendly automotive technology.

Meta, Google Face Data Doomsday As Key EU Decision Looms

Meta Platforms Inc.’s stark warning of a retreat from Europe may just be the start, as one of the region’s top privacy watchdogs prepares a decision that could paralyze transatlantic data flows and risk billions in revenue for tech giants. The Irish data protection authority, which polices the Silicon Valley tech giants that have flocked to the nation, is soon to weigh in on the legality of so-called standard contractual clauses used by Meta.

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How Assuming Fraudsters Are Lazy Can Help Prevent Cyberattacks

In 2022, online fraud is projected to be a huge industry. Just in the U.K., over $187 billion is lost to fraud every year. Globally, it cost $5.38 trillion in 2021 per Crowe and University of Portsmouth research, while cybercrime overall is projected to rise to $10.5 trillion by 2025, per Cybersecurity Ventures. Further, it is estimated that in the 12 years from 2008 to 2020, average losses to fraud globally have increased by 88%.

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Data Mesh Requires A Change In Organizational Mindsets

The data demands of an organization have changed substantially over the years. While initially it may have been simple to serve all use cases from a single monolith, the vast explosion of data over the past decades has made this no longer tenable. Though big data solutions and service-oriented architecture both emerged as solutions for handling large amounts of data, both fall short of the ultimate goal: providing data as first-class building blocks to any service that needs it. 

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Embrace Geospatial Data To Better Visualize Your Business

Geospatial data re-contextualizes our entire world. Whether you’re following your maps app to a new place or tracking a parcel, geospatial data helps us to see not just the location of something but its status, travel and any related events — often in real-time. A simple detour made by your Uber driver gets you to your destination that much quicker, but it’s the geospatial analytics behind the scenes that work to divert you from a path of building work and tedious traffic. 

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Toward A Stronger Defense Of Personal Data

A heart attack patient, recently discharged from the hospital, is using a smartwatch to help monitor his electrocardiogram signals. The smartwatch may seem secure, but the neural network processing that health information is using private data that could still be stolen by a malicious agent through a side-channel attack. A side-channel attack seeks to gather secret information by indirectly exploiting a system or its hardware.

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What Does 2022 Hold For AI And ML In The Automobile Sector?

Artificial Intelligence, a revolution that has taken the world by storm. Spanning various industries and an extensive spectrum of applications, we live and breathe AI. An industry greatly influenced and benefited by this massive phenomenon is the Automobile Industry. From self-driving cars, electric vehicles to driver and vehicle health monitoring systems, AI and ML have sunk their roots deep into the mobility ecosystem. 

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