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Distributed Autonomous Energy Organizations 237

examined in future research. For example, Ethereum-based smart contracts
provide the ability for anyone to write electronic code that can be executed
in a blockchain. If an energy producer or consumer agrees to buy or sell
renewable energy from a neighbor for an agreed-upon price, it can be cap-
tured in a blockchain-based smart contract. AI could help to increase effi-
ciency by automating the auction to include other bidders and sellers in a
more efficient and dynamic way—this would require a lot more data and
analysis to recognize the discernable patterns that inform the AI algorithm
of the smart contract’s performance. Increased automation, however, will
also require that the code of the blockchain is more resilient to cyber-attacks.
Previously, Ethereum was shown to have several vulnerabilities that may
undermine the trustworthiness of this transaction mechanism. Vulnerabil-
ities in the code have been exploited in at least three multimillion dollar
cyber incidents. In June 2016 DAO was hacked—its smart contract code
was exploited, and approximately $50 million dollars were extracted. In July
2017 code in an Ethereum wallet was exploited to extract $30 million dollars
of cryptocurrency. In January 2018 hackers stole roughly 58 billion yen
($532.6 million) from a Tokyo-based cryptocurrency exchange, Coin-
check, Inc. The latter incident highlighted the need for increased security
and regulatory protection for cryptocurrencies and other blockchain appli-
cations. The Coincheck hack appears to have exploited vulnerabilities in a
“hot wallet,” which is a cryptocurrency wallet that is connected to the inter-
net. In contrast, cold wallets, such as Trezor and Ledger Nano S, are cryp-
tocurrency wallets that are stored offline.
Despite being a centralized currency, Coincheck was a cryptocurrency
exchange with a single point of failure. However, the blockchain shared led-
ger of the account may potentially be able to tag and follow the stolen coins
c
and identify any account that receives them (Fadilpas ˇi & Garlick, 2017).
Storing prodigious data sets that are constantly growing in a blockchain
can also create potential latency or bloat in the chain, requiring large
amounts of memory. Requirements for Ethereum-based smart contracts
have grown over time and the block takes a longer time to process. For
time-sensitive energy transactions, this situation may create speed, scale,
and cost issues if the smart contract is not designed properly. Certainly,
future research is needed to develop, validate, and verify a more secure
approach.
Finally, future research should examine the functional requirements and
potential barriers for applying blockchain to make energy organizations
more distributed, autonomous, and secure. For example, even if some