02071nas a2200253 4500008004100000020002200041245006800063210006800131260003100199520130700230653001501537653001801552653002001570653002301590653001901613653000801632653002001640100002101660700001501681700001801696700002201714700002301736856005801759 2020 eng d a978-1-7281-7445-700aIntegrating DOTS With Blockchain Can Secure Massive IoT Sensors0 aIntegrating DOTS With Blockchain Can Secure Massive IoT Sensors aNew Orleans, LA, USAbIEEE3 a

This paper presents a novel approach to securing IoT devices by leveraging DDoS Open Threat Signaling (DOTS) architecture on a Blockchain framework. Like many areas of the information technology domain, IoT sensors are also prone to attacks but on a larger scale. There are millions of devices being connected to a central domain to provide different types of services. Since these low-powered IoT devices have constrained technical requirements with less computational capabilities, they lack the capacity to judge their behavior as benign or malignant. IoT relies heavily on the higher level of intelligent nodes to decide on their status. An IoT Controller/Edge server handles the registration and the limited management of devices. Since traditional security is unable to protect the IoT environment sufficiently, we present a Blockchain-based DDoS detection approach to secure and mitigate such attacks in the IoT environment. Our test setup includes dataset from four sensors over two months. These values were tested using a threshold calculation against the variation of temperature, humidity, pressure, and wind direction on that day to find out whether an IoT sensor is under a DDoS attack. Our results show how DOTS can help in detection of attack when mapped on IoT edge computing.

10ablockchain10aCybersecurity10aDDOS Protection10adistributed ledger10aEdge Computing10aIoT10aSmart Contracts1 aBadruddoja, Syed1 aDantu, Ram1 aWidick, Logan1 aZaccagni, Zachary1 aUpadhyay, Kritagya uhttps://ieeexplore.ieee.org/abstract/document/915034501594nas a2200145 4500008004100000245007200041210006800113260000900181520108200190100002301272700001501295700002201310700002101332856009501353 2020 eng d00aIs your legal contract ambiguous? Convert to a smart legal contract0 ayour legal contract ambiguous Convert to a smart legal contract bIEEE3 a

A legal contract is something that is in spoken or in written form, which binds a party or multiple parties into given terms and conditions. On the other hand, a smart contract is also a contract which is a computer program that binds parties into given terms and conditions but unlike a legal contract, it is self-executable, efficient, and unambiguous. Almost all legal contracts are complex while reading because of its ambiguous nature. In this paper, we take a real-world ambiguous legal contact as a test contract, and generate various interpretations from it, convert all those interpretations into the smart legal contracts and identify the most ambiguous and accurate smart legal contract by performing various measurements such as transaction fees and ambiguity index for each interpretation. We came to the conclusion that the most ambiguous legal contract would be the contract with general interpretation as it was more complex when written in the smart contract and had many possible interpretations due to ambiguity than the rest of the interpretations.

1 aUpadhyay, Kritagya1 aDantu, Ram1 aZaccagni, Zachary1 aBadruddoja, Syed uhttps://nsl.cse.unt.edu/content/your-legal-contract-ambiguous-convert-smart-legal-contract01304nas a2200121 4500008004100000245005900041210005700100520088400157100002201041700001701063700001501080856008701095 2019 eng d00aMicro-Accreditation for Matching Employer E-Hire Needs0 aMicroAccreditation for Matching Employer EHire Needs3 a

This paper presents a novel way to help match employers' knowledge requirements with students' knowledge earned using blockchain's smart contracts to assure credentials and track student records. This decentralized approach proposes using the micro-accreditation of topics from the CAE framework to courses and associated tasks, while introducing a revolutionary idea of a blockchain-based peer-reviewed rigor score assignment. Our work and result metrics were completed in Ethereum and connected test networks. We concluded this new approach is mostly efficient and scalable depending on the network load, with faster transaction times when the miners are properly incentivized. Future work will include further fine-tuning of the transaction algorithms to improve time, as well as an investigation into a better consensus model for peer review and rigor determination.

1 aZaccagni, Zachary1 aPaul, Aditya1 aDantu, Ram uhttps://nsl.cse.unt.edu/content/micro-accreditation-matching-employer-e-hire-needs