MIT Professor: Blockchain Is Good on Its Own but Not Good for Voting

MIT Professor: Blockchain Is Good on Its Own but Not Good for Voting

Computer scientist Ronald Rivest has said that blockchain is not the right technology for voting, although it can find proper application in a number of other areas.

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Computer scientist Ronald Rivest has said that blockchain is not the right technology for voting, although it can find proper application in a number of other areas.

Rivest delivered his opinion at the RSA Security Conference, held in San Francisco earlier this week, technology-focused news outlet ITWire reported on Feb. 28. Rivest — who is a cryptography expert and a professor at the Massachusetts Institute of Technology — called voting an interesting problem that requires a more stricter approach compared to many existing security applications. He said:

“Blockchain is the wrong security technology for voting. I like to think of it as bringing a combination lock to a kitchen fire or something like that. It’s good on its own for certain things but it’s not good for voting.“

“We need software independence”

According to Rivest, voting is an area that does not require hi-tech to work, and anonymity and secret ballots only complicate the process of audit. „Blockchain technology really doesn’t fit for a couple of reasons. One is that we have learned we need software independence,” Rivest said and further added:

„And if you do use some technology, use the paper ballots to check on it and you can do very well. We call this software independence, so you don’t need to trust the results because you trust some software. That’s a dangerous path to go down if you don’t need to go down that path and with voting we really don’t need to.“

Elaborating further on the matter, Rivest compared blockchain with garbage stored in forever. “Once they’ve had the chance to manipulate your vote, it goes on the blockchain and never gets changed again,“ he concluded.

E-voting comes under criticism

Rivest’s speech came on the heels of the Iowa Democratic Caucus scandal, when a mobile software application that had been devised to help calculate the total number of votes in the voting reportedly malfunctioned, resulting in the Democratic Party having to delay its public reporting of the results.

Following the event, blockchain-based applications were heavily criticised by regulators, with many political commentators and media analysts speaking out against mobile- and blockchain-based voting technology.

In the meantime, companies on the forefront of blockchain technology realize the potential of the products they are developing to not only transform the global economy, but also the way voters cast their ballots. Most recently, cybersecurity firm Kaspersky Lab unveiled a new type of a blockchain-based voting machine using Polys, the system released back in November 2017 designed to be an effective and secure way to vote online.

Earlier in February, India’s Chief Election Commissioner Sunil Arora said that the country will soon be able to cast votes from outside their city of registration thanks to a blockchain-based system. With this move, the government hopes to increase voter turnout.


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Computer scientist Ronald Rivest has said that blockchain is not the right technology for voting, although it can find proper application in a number of other areas.

Data Scientist Uses Deep Learning to Predict BTC Price in Real-Time

Data Scientist Uses Deep Learning to Predict BTC Price in Real-Time

LSTM neural networks can purportedly be used to predict crypto prices in real-time, demonstrates data scientist

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A data scientist at India’s prestigious Vellore Institute of Technology has outlined a method for how to purportedly predict crypto prices in real-time using a Long Short-Term Memory (LSTM) neural network.

In a blog post published on Dec. 2, researcher Abinhav Sagar demonstrated a four-step process for how to use machine learning technology to forecast prices in a sector he purported is “relatively unpredictable” as compared with traditional markets. 

Machine learning for crypto price prediction has been “restricted”

Sagar prefaced his demonstration by noting that while machine learning has achieved some success in predicting stock market prices, its application in the cryptocurrency field has been restricted. In support of this claim, he argued that cryptocurrency prices fluctuate in accordance with fast-paced technological developments, as well as economic, security and political factors.

Sagar’s four-step proposed method involves 1) collecting real-time cryptocurrency data; 2) preparing the data for neural network training; 3) testing the prediction using the LSTM neural network; 4) visualizing the results of the prediction.

As software developer Aditi Mittal has outlined, LSTM is an acronym for “Long Short-Term Memory” — a type of neural network that is designed to classify, process and predict time series given time lags of unknown duration. 

To train his network, Sagar used a dataset from CryptoCompare, making use of features such as price, volume and open, high and low values.

He provides a link to the code for the complete project on GitHub and outlines the functions he used to normalize data values in preparation for machine learning.

Before plotting and visualizing the results of the network’s predictions, Sagar notes he used Mean Absolute Error as an evaluation metric, which, he notes, measures the average magnitude of the errors in a set of predictions, without considering their direction.

Sagar’s visualization of his cryptocurrency predictions in real-time using an LSTM neural network

Sagar’s visualization of his cryptocurrency predictions in real-time using an LSTM neural network. Source: towardsdatascience.com

From the markets to outer space

Beyond market predictions, the convergence of new decentralized technologies such as blockchain with machine learning has been gaining ever more traction.

As reported this fall, NASA recently published a listing for a data scientist role, singling out cryptocurrency and blockchain expertise as “a plus.” 

The agency — whose primary function is the construction and operation of planetary robotic spacecraft and conducting Earth-orbit missions — further required qualifications in one or more related fields including machine learning, big data, Internet of Things, analytics, statistics and cloud computing.


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LSTM neural networks can purportedly be used to predict crypto prices in real-time, demonstrates data scientist

Final Russian Nuclear Scientist Jailed For Mining Bitcoin At Work

Final Russian Nuclear Scientist Jailed For Mining Bitcoin At Work

Third Russian nuclear scientist sentenced for role in Bitcoin mining scheme

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A Russian scientist and former employee at the nation’s premier nuclear research facility was jailed on Oct. 24, for his part in a scheme to secretly mine Bitcoin using the facility’s supercomputers. 

Stealing energy and computing power from your employer

According to an Oct. 25 report by RT, former employee Andrey Rybkin was sentenced to 3 years and three months in prison, for the “unauthorized use of computer capabilities.” Two of his colleagues were previously fined for their roles in the plot, with one also receiving a suspended prison sentence.

He was also ordered to pay a fine of 200,000 roubles ($3,130), after trying to use a new supercomputer at the facility to mine Bitcoin.

The centre is located in the Russian city of Sarov, 370km from Moscow. Sarov is a “closed city”, meaning foreigners and tourists are prohibited, and even non-resident Russians must get a special permit to visit.

Best of three

As Cointelegraph reported last month, one of Rybkin’s collaborators was fined 450,000 roubles (US$7000) but escaped jail.

The other employee involved reportedly received a fine and a four year suspended prison sentence.


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Third Russian nuclear scientist sentenced for role in Bitcoin mining scheme

NASA Looks to Hire Data Scientist With Crypto and DLT Background

NASA Looks to Hire Data Scientist With Crypto and DLT Background

NASA looks to hire a data scientist with crypto and blockchain-related background, new job listing says

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The United States’ National Aeronautics and Space Administration (NASA) is looking to hire a data scientist with crypto and blockchain expertise.

Crypto and blockchain considered a plus

According to a LinkedIn job listing posted on Sept. 20, NASA is looking to employ a data scientist for its Jet Propulsion Laboratory in California, whose primary function is the construction and operation of planetary robotic spacecraft and conducting Earth-orbit missions.

Among the high number of required qualifications, NASA listed knowledge in one or more related fields including big data, machine learning, Internet of Things, analytics, statistics and cloud computing, among others. In a separate line, the agency listed experience with cryptocurrency and blockchain technology, stating that such qualification will be considered a plus.

The listed qualifications are supposed to be implemented by the data scientist in designing and implementing a program for analyzing complex, large-scale data sets used for research, modeling, data mining and predictive analysis at NASA, the agency wrote.

NASA on blockchain

The major global aerospace agency is not new to blockchain technology. In January 2019, NASA proposed an air traffic management blockchain framework in order to enable secure, private and anonymous communication with air traffic services.

In April 2018, NASA awarded a grant supporting the development of an autonomous spacecraft that could implement blockchain technology to make decisions without human intervention.


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NASA looks to hire a data scientist with crypto and blockchain-related background, new job listing says

Scientist Mines Bitcoin on Computer Model Used by Apollo Missions

Scientist Mines Bitcoin on Computer Model Used by Apollo Missions

American scientist managed to mine Bitcoin on a 52-year-old Apollo Guidance Computer, one of the computers used by NASA to navigate moon landings

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An American computer scientist has managed to mine Bitcoin (BTC) on a 52-year-old Apollo Guidance Computer (AGC), British tech media outlet IT Pro reports on July 9.

Ken Shirriff, a specialist in reverse engineering, has reportedly worked out a code that enabled him to mine Bitcoin on one of the first integrated circuit-based computers that were used to navigate the first moon landings by the National Aeronautics and Space Administration (NASA) in the 1960s.

As Shirriff wrote on his personal website, the machine on which he managed to integrate Bitcoin mining code is the world’s only remaining working AGC.

With performance comparable to the first generation of home computers from the late 1970s like the Apple II, the 15-bit AGC is apparently not the best hardware to mine crypto. The computer turned out to have a hash power of 10.3 seconds per hash, the engineer reported, explaining that it would take a “billion times the age of the universe to mine a block.”

In comparison, the Antminer S9, a popular ASIC bitcoin miner developed by Chinese mining giant Bitmain exclusively for mining crypto, advertises a hash rate of around 13 terahash, or 13 trillion hashes per second (TH/s).

On his website, Shirriff noted that he has also attempted bitcoin mining on a 55-year-old IBM 1401 punch-card mainframe.

On July 7, Cointelegraph reported that the Bitcoin hash rate reached a new all-time high of 65.19 TH/s. Since then, the growth has continued, breaking 74 TH/s on the same day. As a major metrics for miners, hash rate is the number of calculations that a given hardware or network can perform every second.

A higher hash rate indicates miners’ chances of finding the next block and receiving their reward, also making the network safer by increasing the necessary resources for deploying a 51% attack.


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American scientist managed to mine Bitcoin on a 52-year-old Apollo Guidance Computer, one of the computers used by NASA to navigate moon landings