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'Privacy is at stake': what would you do if you controlled your own data?

The Guardian

The trick of Refik Anadol's Machine Hallucinations, a three-day public art installation at The Shed in New York City, is to transform the processing of data into surreal hypnosis. The immersive audiovisual exhibit towers over a cavernous 17,000 sq ft gallery in Hudson Yards, an outer ring of screens features a shimmering and chameleonic display of what looks like pixelated sand. But each square is a narrative of data: a familiar image – tree, building, lamppost, over 130m publicly available images of New York City searched and collected by Anadol and his team's algorithms – morphed into a single-colored square and then silenced by a single question: what would you do if you owned your data? The free exhibit, part of a $250m project to shift data ownership from private mega-corporations to individual users called Project Liberty, makes a tactile, sensory, emotional argument for data dignity and decentralization of internet power – concepts often so bogged down in technicality, abstraction and vagueness as to be inaccessible. The overarching aim of Project Liberty is to imagine an internet future not governed by tech CEOs, the forfeit of your data for participation, surveillance capitalism and the whims of social media companies aiming for infinite scale.


Artificial Intelligence (AI) in Cybersecurity Market Worth $46.3 Billion by 2027- Market Size, Share, Forecasts, & Trends Analysis Report with COVID-19 Impact by Meticulous Research

#artificialintelligence

Artificial intelligence is changing the game for cybersecurity across several industries by providing cutting-edge security technologies that analyze massive quantities of data. AI technology uses its ability to improve network security over time. Today, several organizations are increasingly implementing AI-powered intelligent security solutions & services to understand and reuse threat patterns to identify new coercions. AI technology provides wider security solutions and simplifies complete recognition and acknowledgment procedures related to cyberattacks. Thus, there is a growing demand for AI-based solutions in the end-use industry for cybersecurity.


Top Snowflake Interview Questions

#artificialintelligence

Snowflake is a cloud data warehouse provided as a software-as-a-service (SaaS). It consists of unique architecture to handle multiple aspects of data and analytics. Snowflake sets itself apart from all other traditional data warehouse solutions with advanced capabilities like improved performance, simplicity, high concurrency and cost-effectiveness. Snowflake's shared data architecture physically separates the computation and storage which is not possible by the traditional offerings. It streamlines the process for businesses to store and analyze massive volumes of data using cloud-based tools.


Cybersecurity can be made agile with zero-shot AI

#artificialintelligence

Modern security information and event management and intrusion detection systems leverage ML to correlate network features, identify patterns in data and highlight anomalies corresponding to attacks. Security researchers spend many hours understanding these attacks and trying to classify them into known kinds like port sweep, password guess, teardrop, etc. However, due to the constantly changing attack landscape and the emergence of advanced persistent threats (APTs), hackers are continuously finding new ways to attack systems. A static list of classification of attacks will not be able to adapt to new and novel tactics adopted by adversaries. Also, due to the constant flow of alarms generated by multiple sources in the network, it becomes difficult to distinguish and prioritize particular types of attacks--the classic alarm flooding problem.


Scammers Are Using Deepfake Videos Now

Slate

Highly realistic deepfake videos didn't quite make the splash some feared they would during the 2020 presidential election. Nevertheless, deepfakes are causing trouble--for regular people. In March, the Federal Bureau of Investigation warned that it expected fraudsters to leverage "synthetic content for cyber … operations in the next 12-18 months." In deepfake videos, which first appeared in 2017, a computer-generated face (often of a real person) is superimposed on someone else. After the swap, the fraudsters can make the target person say or do just about anything.


FTC warns of extortionists targeting LGBTQ+ community on dating apps

#artificialintelligence

The US Federal Trade Commission (FTC) warns of extortion scammers targeting the LGBTQ community via online dating apps such as Grindr and Feeld. As the FTC revealed, the fraudsters would pose as potential romantic partners on LGBTQ dating apps, sending explicit photos and asking their targets to reciprocate. If they fall for the scammers' tricks, the victims will be blackmailed to pay a ransom, usually in gift cards, under the threat of leaking the shared sexual imagery with their family, friends, or employers. "To make their threats more credible, these scammers will tell you the names of exactly who they plan to contact if you don't pay up. This is information scammers can find online by using your phone number or your social media profile," the FTC said.


Your voiceprint could be your new password as companies look to increase security for remote workers

#artificialintelligence

As working from home moves from a temporary solution to the new normal, companies need new ways to secure data and protect internal networks . Banks are most likely to use voiceprints to authenticate users but more companies are considering this approach. Nuance Communications uses a voiceprint algorithm powered by a deep neural network to analyze 1,000 parameters of an individual's voice, including tone, pitch, pacing and fluctuations in the sound. The engine determines which parameters are most relevant for each individual and weights the appropriate elements accordingly. Simon Marchand, chief fraud prevention officer at Nuance, worked in fraud prevention for 10 years in the financial and telecom industries.


Becoming Future Flexible - 4 Key Tech Investments for Retail Banking in 2021

#artificialintelligence

These are the 3 pillars behind the 4 key technology investments that can catalyse retail banking today – and in so doing, provide the foundation to build for digital agility well into the future. This piece considers the role of Artificial Intelligence and Machine Learning, Cyber Security, 5G and Edge Computing (MEC) and Safety Technology. And the integrative array of benefits afforded is vast, including real-time personalised consumer insights, 360 degree data visibility, embedded zero trust security, enhanced organisational and network efficiency, and enhanced safety. As a result, this builds consumer (and employee) trust, confidence, experience and loyalty. But what has sparked the need for transformation?


WhatsApp faces $267 million EU fine over Facebook data sharing transparency

Engadget

The Financial Times reports the Irish Data Protection Commission has fined WhatsApp €225 million ($266.8 million) for not sharing enough details of how it shares European Union users' data with Facebook. The messaging service allegedly failed to live up to its General Data Protection Regulation (GDPR) transparency obligations. The Commission also said the data sharing itself violated GDPR. WhatsApp was merely storing "pseudonymous" phone number data, for instance, rather than truly anonymizing it. While the numbers were stored using lossy hashes, WhatsApp had the hash key needed to decrypt that info -- it could tie that number to a specific person if it wanted. The ruling asked WhatsApp to both improve its transparency and bring the data sharing in line with the GDPR.


#iiot_2021-08-21_13-52-01.xlsx

#artificialintelligence

The graph represents a network of 1,365 Twitter users whose tweets in the requested range contained "#iiot", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 21 August 2021 at 20:59 UTC. The requested start date was Tuesday, 17 August 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 3-day, 6-hour, 15-minute period from Friday, 13 August 2021 at 17:43 UTC to Monday, 16 August 2021 at 23:59 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.