More Like this

1. Scalability Analysis of Blockchain on a Serverless Cloud

   https://doi.org/10.1109/BigData47090.2019.9005529  

   Kaplunovich, Alex ; Joshi, Karuna P. ; Yesha, Yelena ( December 2019 , 2019 IEEE International Conference on Big Data (Big Data))

   null (Ed.)

   While adopting Blockchain technologies to automate their enterprise functionality, organizations are recognizing the challenges of scalability and manual configuration that the state of art present. Scalability of Hyperledger Fabric is an open challenge recognized by the research community. We have automated many of the configuration steps of installing Hyperledger Fabric Blockchain on AWS infrastructure and have benchmarked the scalability of that system. We have used the UCR (University of California Riverside) Time Series Archive with 128 timeseries datasets containing over 191,177 rows of data totaling 76,453,742 numbers. Using an automated Serverless approach, we have loaded this dataset, by chunks, into different AWS instances, triggering the load by SQS messaging. In this paper, we present the results of this benchmarking study and describe the approach we took to automate the Hyperledger Fabric processes using serverless Lambda functions and SQS triggering. We will also discuss what is needed to make the Blockchain technology more robust and scalable. 

   more » « less
2. Performance Modeling of Hyperledger Sawtooth Blockchain

   https://doi.org/10.1109/ISI.2019.8823238  

   Ampel, Ben ; Patton, Mark ; Chen, Hsinchun ( July 2019 , 2019 IEEE Conference on Intelligence and Security Informatics)

   With the rapid development of blockchain plat-forms, it is important that different implementations are tested and analyzed for comparative purposes. One such implementation is Hyperledger Sawtooth, a new member of the Hyperledger family. Sawtooth blockchain is a per-missioned implementation developed in part by Intel. While research has been done on Hyperledger Fabric, re-search on Sawtooth is not well documented. Using the Hy-perledger Caliper benchmarking tool, we aim to test the performance of the blockchain and identify potential issues. 

   more » « less
3. A Collaborative Enforcement Mechanism for Spectrum Sharing Using Blockchain and Smart Contracts: An application for the 1695-1710MHz band

   Bustamante, Pedro J ; Gomez, Marcela M. ; Weiss, Martin BH ; Znati, Taieb ; Das, Debarun ; Rose, J. Stephanie ( September 2019 , Telecommunications Policy Research Conference)

   Traditionally, spectrum allocation has been governed by centralized schemes (e.g., command-and-control). Nonetheless, other mechanisms, such as collaborative enforcement, have proven to be successful in a variety of scenarios. In Collaborative enforcement (i.e., collective action), the stakeholders agree on decision-making arrangements (i.e., access, allocation, and control of the resources) while being involved in monitoring the adherence to the rules as a shared effort. Blockchain is a distributed ledger of records/transactions (i.e., database) that brings many benefits such as decentralization, transparency, immutability, etc. One of the most notable characteristics of blockchain-based platforms is their definition as trust-less environments, as there is no central entity in charge of controlling the network interactions. Instead, trust is a group effort, achieved through repeated interactions, consensus algorithms, and cryptographic tools; therefore, converting blockchain systems into examples of collaborative governance regimes. In this paper, our goal is to analyze a particular application of blockchain and smart contracts for the 1695-1710MHz sharing scenario. In this way, we provide a theoretical analysis of the feasibility and the required characteristics to implement such a system. In addition, through the implementation of a Proof of Concept, we explore how the implementation of a blockchainbased organization can be the motor to build a collaborative governance scheme in the spectrum sharing arrangement of the 1695-1710MHz band 

   more » « less
4. Anomaly Detection based on Traffic Monitoring for Secure Blockchain Networking

   https://doi.org/10.1109/ICBC51069.2021.9461119  

   Kim, Jinoh ; Nakashima, Makiya ; Fan, Wenjun ; Wuthier, Simeon ; Zhou, Xiaobo ; Kim, Ikkyun ; Chang, Sang-Yoon ( May 2021 , IEEE International Conference on Blockchain and Cryptocurrency (ICBC))

   While the blockchain technology provides strong cryptographic protection on the ledger and the system operations, the underlying blockchain networking remains vulnerable due to potential threats such as denial of service (DoS), Eclipse, spoofing, and Sybil attacks. Effectively detecting such malicious events should thus be an essential task for securing blockchain networks and services. Due to its importance, several studies investigated anomaly detection in Bitcoin and blockchain networks, but their analyses mainly focused on the blockchain ledger in the application context (e.g., transactions) and targets specific types of attacks (e.g., double-spending, deanonymization, etc). In this study, we present a security mechanism based on the analysis of blockchain network traffic statistics (rather than ledger data) to detect malicious events, through the functions of data collection and anomaly detection. The data collection engine senses the underlying blockchain traffic and generates multi-dimensional data streams in a periodic manner. The anomaly detection engine then detects anomalies from the created data instances based on semi-supervised learning, which is capable of detecting previously unseen patterns, and we introduce our profiling-based detection engine implemented on top of AutoEncoder (AE). Our experimental results support the effectiveness of the presented security mechanism for accurate, online detection of malicious events from blockchain networking traffic data. We also show further reduction in time complexity (up to 66.8% for training and 85.7% for testing), without any performance degradation using feature prioritization compared to the utilization of the entire features. 

   more » « less
5. Dependable Public Ledger for Policy Compliance, a Blockchain Based Approach

   Wu, Zhou ; Williams, Andrew ; Perouli, Debbie ( July 2019 , 39th IEEE International Conference on Distributed Computing Systems (ICDCS 2019))

   The ever increasing amount of personal data accumulated by companies offering innovative services through the cloud, Internet of Things devices and, more recently, social robots has started to alert consumers and legislative authorities. In the advent of the first modern laws trying to protect user privacy, such as the European Union General Data Protection Regulation, it is still unclear what are the tools and techniques that the industry should employ to comply with regulations in a transparent and cost effective manner. We propose an architecture for a public blockchain based ledger that can provide strong evidence of policy compliance. To address scalability concerns, we define a new type of off-chain channel that is based on general state channels and offers verification for information external to the blockchain. We also create a model of the business relationships in a smart home setup that includes a social robot and suggest a sticky policy mechanism to monitor cross-boundary policy compliance. 

   more » « less