Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169446
Shiquan Zhang, Kaiwen Zhang, Bettina Kemme
Proof-of-Work (PoW) is the core of the most popular consensus protocol among current mainstream blockchain systems including Bitcoin. Selfish mining attacks are a possible threat towards PoW-based systems and recent works have shown that a miner can profit using selfish mining if it has more than 25% of the overall mining power. In this paper, we present a simulator based on a Markov Process model that can analyze scenarios where there are multiple, independently working selfish miners. In our evaluations, we present detailed results with two attackers showing that the threshold for profitable selfish mining decreases to 21% in this case.
{"title":"A Simulation-Based Analysis of Multiplayer Selfish Mining","authors":"Shiquan Zhang, Kaiwen Zhang, Bettina Kemme","doi":"10.1109/ICBC48266.2020.9169446","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169446","url":null,"abstract":"Proof-of-Work (PoW) is the core of the most popular consensus protocol among current mainstream blockchain systems including Bitcoin. Selfish mining attacks are a possible threat towards PoW-based systems and recent works have shown that a miner can profit using selfish mining if it has more than 25% of the overall mining power. In this paper, we present a simulator based on a Markov Process model that can analyze scenarios where there are multiple, independently working selfish miners. In our evaluations, we present detailed results with two attackers showing that the threshold for profitable selfish mining decreases to 21% in this case.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131034091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169430
Shashank Motepalli, Patrícia Vilain, H. Jacobsen
Enterprises and Governments, alike, are leveraging distributed ledger technologies to solve traditional problems across domains. They consider private blockchains such as Hyperledger Fabric as a safe bet for the obvious security and privacy reasons. However, the tools for software reliability are not yet matured. In this work, we propose FabricUnit, a unit testing framework for Hyperledger Fabric clients. FabricUnit identifies the safe methods that do not alter the state and re-uses the setup execution (deleting any stale data and reinitializes the data). Our experiment shows a reduction of approximately 30% in the tests execution time.
{"title":"FabricUnit: A Framework for Faster Execution of Unit Tests on Hyperledger Fabric","authors":"Shashank Motepalli, Patrícia Vilain, H. Jacobsen","doi":"10.1109/ICBC48266.2020.9169430","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169430","url":null,"abstract":"Enterprises and Governments, alike, are leveraging distributed ledger technologies to solve traditional problems across domains. They consider private blockchains such as Hyperledger Fabric as a safe bet for the obvious security and privacy reasons. However, the tools for software reliability are not yet matured. In this work, we propose FabricUnit, a unit testing framework for Hyperledger Fabric clients. FabricUnit identifies the safe methods that do not alter the state and re-uses the setup execution (deleting any stale data and reinitializes the data). Our experiment shows a reduction of approximately 30% in the tests execution time.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114678605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169439
Umang Goel, Rahul Sonanis, Ishan Rastogi, S. Lal, Aloknath De
Blockchain enabled systems are becoming increasingly popular in recent times, spreading across variety of domains such as finance, supply chain management, healthcare, etc. These systems usually involve homogeneous transactions with similar latency requirements. However, as increasingly complex systems are enabled through blockchain, they will include a variety of heterogeneous transactions having different latency requirements. For example, an IoT system such as smart building may include transactions corresponding to varied services like payment, biometric registration, etc. Present blockchain systems are transaction metadata agnostic in their ordering step i.e. during ordering and bundling of transactions into blocks. Since transactions in complex systems are heterogeneous in nature, a framework that prioritizes transactions having low latency requirements would be more suitable. In this work, we propose various transaction criticality aware ordering services and comprehensively evaluate them on a handcrafted smart building scenario. Our experiments demonstrate that a single ordering service is not suitable (in terms of number of transactions missing their latency requirement) for all practical scenarios. We demonstrate that selection of a suitable ordering service may give up to 58.25% improvement over other ordering services.
{"title":"Criticality Aware Orderer for Heterogeneous Transactions in Blockchain","authors":"Umang Goel, Rahul Sonanis, Ishan Rastogi, S. Lal, Aloknath De","doi":"10.1109/ICBC48266.2020.9169439","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169439","url":null,"abstract":"Blockchain enabled systems are becoming increasingly popular in recent times, spreading across variety of domains such as finance, supply chain management, healthcare, etc. These systems usually involve homogeneous transactions with similar latency requirements. However, as increasingly complex systems are enabled through blockchain, they will include a variety of heterogeneous transactions having different latency requirements. For example, an IoT system such as smart building may include transactions corresponding to varied services like payment, biometric registration, etc. Present blockchain systems are transaction metadata agnostic in their ordering step i.e. during ordering and bundling of transactions into blocks. Since transactions in complex systems are heterogeneous in nature, a framework that prioritizes transactions having low latency requirements would be more suitable. In this work, we propose various transaction criticality aware ordering services and comprehensively evaluate them on a handcrafted smart building scenario. Our experiments demonstrate that a single ordering service is not suitable (in terms of number of transactions missing their latency requirement) for all practical scenarios. We demonstrate that selection of a suitable ordering service may give up to 58.25% improvement over other ordering services.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122374857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169460
C. F. Torres, Mathis Baden, R. State
The Ethereum blockchain enables the execution of so-called smart contracts. These are programs that facilitate the automated transfer of funds according to a given business logic without the participants requiring to trust one another. However, recently attackers started using smart contracts to lure users into traps by deploying contracts that pretend to give away funds but in fact contain hidden traps. This new type of scam is commonly referred to as honeypots. In this paper, we propose a system that aims to protect users from falling into these traps. The system consists of a plugin for MetaMask and a back-end service that continuously scans the Ethereum blockchain for honeypots. Whenever a user is about to perform a transaction through MetaMask, our plugin sends a request to the back-end and warns the user if the target contract is a honeypot.
{"title":"Towards Usable Protection Against Honeypots","authors":"C. F. Torres, Mathis Baden, R. State","doi":"10.1109/ICBC48266.2020.9169460","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169460","url":null,"abstract":"The Ethereum blockchain enables the execution of so-called smart contracts. These are programs that facilitate the automated transfer of funds according to a given business logic without the participants requiring to trust one another. However, recently attackers started using smart contracts to lure users into traps by deploying contracts that pretend to give away funds but in fact contain hidden traps. This new type of scam is commonly referred to as honeypots. In this paper, we propose a system that aims to protect users from falling into these traps. The system consists of a plugin for MetaMask and a back-end service that continuously scans the Ethereum blockchain for honeypots. Whenever a user is about to perform a transaction through MetaMask, our plugin sends a request to the back-end and warns the user if the target contract is a honeypot.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125441946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169396
R. Camino, C. F. Torres, Mathis Baden, R. State
Ethereum smart contracts have recently drawn a considerable amount of attention from the media, the financial industry and academia. With the increase in popularity, malicious users found new opportunities to profit by deceiving newcomers. Consequently, attackers started luring other attackers into contracts that seem to have exploitable flaws, but that actually contain a complex hidden trap that in the end benefits the contract creator. In the blockchain community, these contracts are known as honeypots. A recent study presented a tool called HONEYBADGER that uses symbolic execution to detect honeypots by analyzing contract bytecode. In this paper, we present a data science detection approach based foremost on the contract transaction behavior. We create a partition of all the possible cases of fund movements between the contract creator, the contract, the transaction sender and other participants. To this end, we add transaction aggregated features, such as the number of transactions and the corresponding mean value and other contract features, for example compilation information and source code length. We find that all aforementioned categories of features contain useful information for the detection of honeypots. Moreover, our approach allows us to detect new, previously undetected honeypots of already known techniques. We furthermore employ our method to test the detection of unknown honeypot techniques by sequentially removing one technique from the training set. We show that our method is capable of discovering the removed honeypot techniques. Finally, we discovered two new techniques that were previously not known.
{"title":"A Data Science Approach for Detecting Honeypots in Ethereum","authors":"R. Camino, C. F. Torres, Mathis Baden, R. State","doi":"10.1109/ICBC48266.2020.9169396","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169396","url":null,"abstract":"Ethereum smart contracts have recently drawn a considerable amount of attention from the media, the financial industry and academia. With the increase in popularity, malicious users found new opportunities to profit by deceiving newcomers. Consequently, attackers started luring other attackers into contracts that seem to have exploitable flaws, but that actually contain a complex hidden trap that in the end benefits the contract creator. In the blockchain community, these contracts are known as honeypots. A recent study presented a tool called HONEYBADGER that uses symbolic execution to detect honeypots by analyzing contract bytecode. In this paper, we present a data science detection approach based foremost on the contract transaction behavior. We create a partition of all the possible cases of fund movements between the contract creator, the contract, the transaction sender and other participants. To this end, we add transaction aggregated features, such as the number of transactions and the corresponding mean value and other contract features, for example compilation information and source code length. We find that all aforementioned categories of features contain useful information for the detection of honeypots. Moreover, our approach allows us to detect new, previously undetected honeypots of already known techniques. We furthermore employ our method to test the detection of unknown honeypot techniques by sequentially removing one technique from the training set. We show that our method is capable of discovering the removed honeypot techniques. Finally, we discovered two new techniques that were previously not known.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126395675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169441
H. Niavis, Nikolaos Papadis, L. Tassiulas
Off-grid networks are recently emerging as a solution to connect the unconnected or provide alternative services to networks of possibly untrusted participants. The systems currently used, however, exhibit limitations due to their centralized nature and thus prove inadequate to secure trust. Blockchain technology can be the tool that will enable trust and transparency in such networks. In this paper, we introduce a platform for secure and privacy-respecting decentralized data sharing among untrusted participants in off-grid networks. The proposed architecture realizes this goal via the integration of existing blockchain frameworks (Hyperledger Fabric, Indy, Aries) with an off-grid network device and a distributed file system. We evaluate the proposed platform through experiments and show results for its throughput and latency, which indicate its adequate performance for supporting off-grid decentralized applications.
{"title":"A Blockchain-based Decentralized Data Sharing Infrastructure for Off-grid Networking","authors":"H. Niavis, Nikolaos Papadis, L. Tassiulas","doi":"10.1109/ICBC48266.2020.9169441","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169441","url":null,"abstract":"Off-grid networks are recently emerging as a solution to connect the unconnected or provide alternative services to networks of possibly untrusted participants. The systems currently used, however, exhibit limitations due to their centralized nature and thus prove inadequate to secure trust. Blockchain technology can be the tool that will enable trust and transparency in such networks. In this paper, we introduce a platform for secure and privacy-respecting decentralized data sharing among untrusted participants in off-grid networks. The proposed architecture realizes this goal via the integration of existing blockchain frameworks (Hyperledger Fabric, Indy, Aries) with an off-grid network device and a distributed file system. We evaluate the proposed platform through experiments and show results for its throughput and latency, which indicate its adequate performance for supporting off-grid decentralized applications.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125833464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although transaction fees are not obligatory in most of the current blockchain systems, extensive studies confirm their importance in maintaining the security and sustainability of blockchain. To enhance blockchain in the long term, it is crucial to design effective transaction pricing mechanisms. Different from the existing schemes based on auctions with more consideration about the profit of miners, we resort to game theory and propose a correlated equilibrium based transaction pricing mechanism through solving a pricing game among users with transactions, which can achieve both the individual and global optimum. To avoid the computational complexity exponentially increasing with the number of transactions, we further improve the game-theoretic solution with an approximate algorithm, which can derive almost the same results as the original one but costs significantly reduced time. Experimental results demonstrate the effectiveness and efficiency of our proposed mechanism.
{"title":"A Correlated Equilibrium based Transaction Pricing Mechanism in Blockchain","authors":"Qin Hu, Yash Nigam, Zhilin Wang, Yawei Wang, Yinhao Xiao","doi":"10.1109/ICBC48266.2020.9169475","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169475","url":null,"abstract":"Although transaction fees are not obligatory in most of the current blockchain systems, extensive studies confirm their importance in maintaining the security and sustainability of blockchain. To enhance blockchain in the long term, it is crucial to design effective transaction pricing mechanisms. Different from the existing schemes based on auctions with more consideration about the profit of miners, we resort to game theory and propose a correlated equilibrium based transaction pricing mechanism through solving a pricing game among users with transactions, which can achieve both the individual and global optimum. To avoid the computational complexity exponentially increasing with the number of transactions, we further improve the game-theoretic solution with an approximate algorithm, which can derive almost the same results as the original one but costs significantly reduced time. Experimental results demonstrate the effectiveness and efficiency of our proposed mechanism.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126661678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169474
Michael Zargham, J. Shorish, Krzysztof Paruch
Bonding curves are continuous liquidity mechanisms which are used in market design for cryptographically- supported token economies. Bonding curves are an example of an enforceable mechanism through which participating agents influence this state. By designing such mechanisms, an engineer may establish the topological structure of a token economy without presupposing the utilities or associated actions of the agents within that economy. This is accomplished by introducing configuration spaces, which are proper subsets of the global state space representing all achievable states under the designed mechanisms. This paper generalizes the notion of a bonding curve to formalize the relationship between cryptographically enforced mechanisms and their associated configuration spaces, using invariant properties of conservation functions.
{"title":"From Curved Bonding to Configuration Spaces","authors":"Michael Zargham, J. Shorish, Krzysztof Paruch","doi":"10.1109/ICBC48266.2020.9169474","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169474","url":null,"abstract":"Bonding curves are continuous liquidity mechanisms which are used in market design for cryptographically- supported token economies. Bonding curves are an example of an enforceable mechanism through which participating agents influence this state. By designing such mechanisms, an engineer may establish the topological structure of a token economy without presupposing the utilities or associated actions of the agents within that economy. This is accomplished by introducing configuration spaces, which are proper subsets of the global state space representing all achievable states under the designed mechanisms. This paper generalizes the notion of a bonding curve to formalize the relationship between cryptographically enforced mechanisms and their associated configuration spaces, using invariant properties of conservation functions.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127020529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.1109/ICBC48266.2020.9169455
Jonathan Heiss, Max-Robert Ulbricht, Jacob Eberhardt
Faulty access control in API-based multi-service setups can lead to violations of consent declarations through unauthorized Third Parties. This threatens Service Providers to lose the trust of their Service Consumers and to be exposed to sensitive fines as defined by the GDPR.Addressing this problem, in this paper, we propose a novel, blockchain-based approach for enabling economically motivated and technically mediated detection of violations of consent declarations in multi-service setups and derive its legal viability from a thorough analysis of the GDPR. The herein introduced Violation Detection mechanism allows for a censorship-resistant and publicly verifiable detection of violations to registered Consent Policies based on off-chain computed violation claims utilizing non-interactive zero-knowledge proofs. The corresponding System Design specifies all required roles and artifacts to integrate the Violation Detection mechanism with standard procedures for consent-based access control. The integration of our system supports Service Providers to fulfill legal requirements and, therefore, paves the way towards automated policy violation detection within GDPR-compliant consent-based access control solutions.
{"title":"Put Your Money Where Your Mouth Is – Towards Blockchain-based Consent Violation Detection","authors":"Jonathan Heiss, Max-Robert Ulbricht, Jacob Eberhardt","doi":"10.1109/ICBC48266.2020.9169455","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169455","url":null,"abstract":"Faulty access control in API-based multi-service setups can lead to violations of consent declarations through unauthorized Third Parties. This threatens Service Providers to lose the trust of their Service Consumers and to be exposed to sensitive fines as defined by the GDPR.Addressing this problem, in this paper, we propose a novel, blockchain-based approach for enabling economically motivated and technically mediated detection of violations of consent declarations in multi-service setups and derive its legal viability from a thorough analysis of the GDPR. The herein introduced Violation Detection mechanism allows for a censorship-resistant and publicly verifiable detection of violations to registered Consent Policies based on off-chain computed violation claims utilizing non-interactive zero-knowledge proofs. The corresponding System Design specifies all required roles and artifacts to integrate the Violation Detection mechanism with standard procedures for consent-based access control. The integration of our system supports Service Providers to fulfill legal requirements and, therefore, paves the way towards automated policy violation detection within GDPR-compliant consent-based access control solutions.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122264295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-30DOI: 10.1109/ICBC48266.2020.9169397
Suat Mercan, Mumin Cebe, Ege Tekiner, K. Akkaya, Melissa Chang, Selcuk Uluagac
IoT devices have been adopted widely in the last decade which enabled collection of various data from different environments. Data storage poses challenges since the data may be compromised during the storage and the integrity might be violated without being noticed. In such cases, integrity and data provenance are required in order to be able to detect the source of any incident and prove it in legal cases. To address these issues, blockchain provides excellent opportunities since it can protect the integrity of the data thanks to its distributed structure. However, it comes with certain costs as storing huge amount of data in a public blockchain will come with significant transaction fees. In this paper, we propose a highly cost effective and reliable digital forensics framework by exploiting multiple inexpensive blockchain networks as a temporary storage before the data is committed to Ethereum. To reduce Ethereum costs, we utilize Merkle trees which hierarchically stores hashes of the collected event data from IoT devices. We evaluated the approach on popular blockchains such as EOS, Stellar, and Ethereum by presenting a cost and security analysis. The results indicate that we can achieve significant cost savings without compromising the integrity of the data.
{"title":"A Cost-efficient IoT Forensics Framework with Blockchain","authors":"Suat Mercan, Mumin Cebe, Ege Tekiner, K. Akkaya, Melissa Chang, Selcuk Uluagac","doi":"10.1109/ICBC48266.2020.9169397","DOIUrl":"https://doi.org/10.1109/ICBC48266.2020.9169397","url":null,"abstract":"IoT devices have been adopted widely in the last decade which enabled collection of various data from different environments. Data storage poses challenges since the data may be compromised during the storage and the integrity might be violated without being noticed. In such cases, integrity and data provenance are required in order to be able to detect the source of any incident and prove it in legal cases. To address these issues, blockchain provides excellent opportunities since it can protect the integrity of the data thanks to its distributed structure. However, it comes with certain costs as storing huge amount of data in a public blockchain will come with significant transaction fees. In this paper, we propose a highly cost effective and reliable digital forensics framework by exploiting multiple inexpensive blockchain networks as a temporary storage before the data is committed to Ethereum. To reduce Ethereum costs, we utilize Merkle trees which hierarchically stores hashes of the collected event data from IoT devices. We evaluated the approach on popular blockchains such as EOS, Stellar, and Ethereum by presenting a cost and security analysis. The results indicate that we can achieve significant cost savings without compromising the integrity of the data.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130692794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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