Blockchain for AI: review and open research challenges
Open accessAbstract
Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology has the ability to automate payment in cryptocurrency and to provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. Also with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities for machines similar to humans. In this paper, we present a detailed survey on blockchain applications for AI. We review the literature, tabulate, and summarize the emerging blockchain applications, platforms, and protocols specifically targeting AI area. We also identify and discuss open research challenges of utilizing blockchain technologies for AI.
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Blockchain could be a promising secured solution if an IoT application requires maintaining a payment process for its services without third-party control.
“(2) Blockchain could be a promising secured solution if IoT application requires to maintain payment process for its provided services without the control of third parties [149].”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [149]
Deployment of FL on blockchain technology can establish data security and eliminate trust issues.
“Another approach to establish data security and eliminate the trust issues is the deployment of FL on blockchain technology [71]- [73].”
From Handling privacy-sensitive medical data with federated learning: Challenges and future directions (2023) · cites this paper as [73]
Blockchain-based FL replaces the central authority with a specially designed decentralized privacy protocol.
“The main advantage brought is the replacement of the central authority with a specially designed decentralized privacy protocol.”
From Handling privacy-sensitive medical data with federated learning: Challenges and future directions (2023) · cites this paper as [73]
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Artificial intelligence: a modern approach
Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,182 · see citing works
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570 · see citing works
Bitcoin: A Peer-to-Peer Electronic Cash SystemPreprint
Nakamoto, S. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3440802 · Cited by 14,599 · see citing works
Communication-Efficient Learning of Deep Networks from Decentralized Data
McMahan, H. B., Moore, E., Ramage, D., Hampson, S., & Arcas, B. A. Y. (2016) · arXiv · doi:10.48550/arxiv.1602.05629 · Cited by 14,215 · see citing works
Bitcoin: A Peer-to-Peer Electronic Cash SystemPreprint
Squarepants, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.3977007 · Cited by 11,146 · see citing works
(2013) · Cited by 5,372 · see citing works
Multimodal Machine Learning: A Survey and Taxonomy
Baltrusaitis, T., Ahuja, C., & Morency, L.-P. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2798607 · Cited by 5,018 · see citing works
Blockchains and smart contracts for the internet of things
Christidis, K., & Devetsikiotis, M. (2016) · IEEE Access · doi:10.1109/access.2016.2566339 · Cited by 4,552 · see citing works
Hyperledger fabric: a distributed operating system for permissioned blockchains
Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., Enyeart, D., Ferris, C., Laventman, G., Manevich, Y., et al. (2018) · Proceedings of the Thirteenth EuroSys Conference · doi:10.1145/3190508.3190538 · Cited by 3,654 · see citing works
Blockchain challenges and opportunities: a survey
Zheng, Z., Xie, S., Dai, H. N., Chen, X., & Wang, H. (2018) · International Journal of Web and Grid Services · doi:10.1504/ijwgs.2018.095647 · Cited by 3,651 · see citing works
(2015) · Cited by 3,471 · see citing works
Optimization Methods for Large-Scale Machine Learning
Bottou, L., Curtis, F. E., & Nocedal, J. M. (2018) · SIAM Review · doi:10.1137/16m1080173 · Cited by 3,233 · see citing works
Deep learning applications and challenges in big data analytics
Najafabadi, M. M., Villanustre, F., Khoshgoftaar, T. M., Seliya, N., Wald, R., & Muharemagic, E. (2015) · Journal of Big Data · doi:10.1186/s40537-014-0007-7 · Cited by 2,594 · see citing works
IoT security: Review, blockchain solutions, and open challenges
Khan, M. A., & Salah, K. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2017.11.022 · Cited by 2,488 · see citing works
Self-citationMaking Smart Contracts Smarter
Luu, L., Chu, D.-H., Olickel, H., Saxena, P., & Hobor, A. (2016) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2976749.2978309 · Cited by 2,337 · see citing works
On blockchain and its integration with IoT. Challenges and opportunities
Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.05.046 · Cited by 1,908 · see citing works
IPFS - Content Addressed, Versioned, P2P File SystemPreprint
Benet, J. (2014) · arXiv (Cornell University) · doi:10.4230/lipics.opodis.2022.9 · Cited by 1,856 · see citing works
Swarm robotics: a review from the swarm engineering perspective
Brambilla, M., Ferrante, E., Birattari, M., & Dorigo, M. (2013) · Swarm Intelligence · doi:10.1007/s11721-012-0075-2 · Cited by 1,791 · see citing works
A Survey on the Security of Blockchain Systems
Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2020) · Future Generation Computer Systems · doi:10.1016/j.future.2017.08.020 · Cited by 1,772 · see citing works
Bitcoin and beyond: a technical survey on decentralized digital currencies
Tschorsch, F., & Scheuermann, B. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2535718 · Cited by 1,690 · see citing works
Blockchain challenges and opportunities: a survey
Wang, H., Zheng, Z., Xie, S., Dai, H., & Chen, X. (2018) · International Journal of Web and Grid Services · doi:10.1504/ijwgs.2018.10016848 · Cited by 1,582 · see citing works
Algorand: Scaling Byzantine Agreements for Cryptocurrencies
Gilad, Y., Hemo, R., Micali, S., Vlachos, G., & Zeldovich, N. (2017) · Proceedings of the 26th Symposium on Operating Systems Principles · doi:10.1145/3132747.3132757 · Cited by 1,499 · see citing works
A Secure Sharding Protocol For Open Blockchains
Luu, L., Narayanan, V., Zheng, C., Baweja, K., Gilbert, S. L., & Saxena, P. (2016) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/2976749.2978389 · Cited by 1,457 · see citing works
Untangling Blockchain: A Data Processing View of Blockchain Systems
Dinh, T. T. A., Liu, R. Z. Z., Zhang, M., Chen, G., Ooi, B. C., & Wang, J. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2781227 · Cited by 1,189 · see citing works
Brain intelligence: go beyond artificial intelligence
Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018) · Mobile Networks and Applications · doi:10.1007/s11036-017-0932-8 · Cited by 1,153 · see citing works
Zamani, M., Movahedi, M., & Raykova, M. (2018) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3243734.3243853 · Cited by 1,129 · see citing works
Consortium Blockchain for Secure Energy Trading in Industrial Internet of Things
Li, Z., Kang, J., Yu, R., Ye, D., Deng, Q., & Zhang, Y. (2017) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2017.2786307 · Cited by 1,103 · see citing works
Samek, W., Wiegand, T., & Müller, K.-R. (2017) · arXiv · doi:10.48550/arxiv.1708.08296 · Cited by 1,080 · see citing works
A Review on the Use of Blockchain for the Internet of Things
Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018) · IEEE Access · doi:10.1109/access.2018.2842685 · Cited by 1,078 · see citing works
PPCoin: Peer-to-Peer Crypto-Currency with Proof-of-Stake
King, S., & Nadal, S. (2012) · Cited by 984 · see citing works
Dinh, T. T. A., Wang, J., Chen, G., Liu, R. Z. Z., Ooi, B. C., & Tan, K. (2017) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/3035918.3064033 · Cited by 824 · see citing works
Blockchain and IoT Integration: A Systematic Survey
Panarello, A., Tapas, N., Merlino, G., Longo, F., & Puliafito, A. (2018) · Sensors · doi:10.3390/s18082575 · Cited by 756 · see citing works
Tikhomirov, S., Voskresenskaya, E., Ivanitskiy, I., Takhaviev, R., Marchenko, E., & Alexandrov, Y. (2018) · IEEE/ACM International Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB) · doi:10.1145/3194113.3194115 · Cited by 678 · see citing works
Proof of activity: Extending bitcoin’s proof of work via proof of stake [extended abstract] y
Bentov, I., Lee, C., Mizrahi, A., & Rosenfeld, M. (2014) · ACM SIGMETRICS Performance Evaluation Review · doi:10.1145/2695533.2695545 · Cited by 592 · see citing works
Blockchains everywhere - a use-case of blockchains in the pharma supply-chain
Bocek, T., Rodrigues, B. B., Strasser, T., & Stiller, B. (2017) · 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM) · doi:10.23919/inm.2017.7987376 · Cited by 585 · cited 1× · see citing works
“A smart contract is a self-executing code that can verify the enforcement of predefined terms and conditions [29].”
BackgroundExperimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0
Schluse, M., Priggemeyer, M., Atorf, L., & Roßmann, J. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2804917 · Cited by 524 · see citing works
Security services using blockchains: a state of the art survey
Salman, T., Zolanvari, M., Erbad, A., Jain, R., & Samaka, M. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2863956 · Cited by 502 · see citing works
Artificial intelligence—A personal view
Marr, D. (1977) · Artificial Intelligence · doi:10.1016/0004-3702(77)90013-3 · Cited by 500 · see citing works
Towards Blockchain-based Auditable Storage and Sharing of IoT Data
Shafagh, H., Burkhalter, L., Hithnawi, A., & Duquennoy, S. (2017) · Cloud Computing Security Workshop · doi:10.1145/3140649.3140656 · Cited by 487 · see citing works
Decentralized Applications: The Blockchain-Empowered Software System
Cai, W., Wang, Z., Ernst, J. B., Hong, Z., Feng, C., & Leung, V. C. M. (2018) · IEEE Access · doi:10.1109/access.2018.2870644 · Cited by 487 · see citing works
Mamoshina, P., Ojomoko, L., Yanovich, Y., Ostrovski, A., Botezatu, A., Prikhodko, P., Izumchenko, E., Aliper, A., Romantsov, K., Zhebrak, A., et al. (2018) · Oncotarget · doi:10.18632/oncotarget.22345 · Cited by 471 · see citing works
Bowers, K. D., Juels, A., & Oprea, A. (2009) · doi:10.1145/1655008.1655015 · Cited by 452 · see citing works
An Overview of Smart Contract: Architecture, Applications, and Future Trends
Wang, S., Yuan, Y., Wang, X., Li, J., Qin, R., & Wang, F. (2018) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2018.8500488 · Cited by 415 · see citing works
Pbft Vs Proof-Of-Authority: Applying The Cap Theorem To Permissioned Blockchain
Angelis, S. D., Aniello, L., Baldoni, R., Lombardi, F., Margheri, A., & Vladimiro Sassone, C. (2017) · ePrints Soton (University of Southampton) · doi:10.5281/zenodo.1169272 · Cited by 394 · see citing works
Deep learning of feature representation with multiple instance learning for medical image analysis
Xu, Y. L., Mo, T., Feng, Q., Zhong, P., Lai, M., & Chang, E. (2014) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2014.6853873 · Cited by 385 · see citing works
On Security Analysis of Proof-of-Elapsed-Time (PoET)
Chen, L., Xu, L., Shah, N., Gao, Z., Lu, Y., & Shi, W. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-69084-1_19 · Cited by 351 · see citing works
Blockchain for smart grid resilience: Exchanging distributed energy at speed, scale and security
Mylrea, M., & Gourisetti, S. N. G. (2017) · Resilience Week (RWS) · doi:10.1109/rweek.2017.8088642 · Cited by 339 · see citing works
AI and Blockchain: A Disruptive Integration
Dinh, T. N., & Thai, M. T. (2018) · Computer · doi:10.1109/mc.2018.3620971 · Cited by 317 · see citing works
(2017) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 288 · see citing works
Blockchain standards for compliance and trust
Anjum, A., Sporny, M., & Sill, A. (2017) · IEEE Cloud Computing · doi:10.1109/mcc.2017.3791019 · Cited by 265 · see citing works
Kiktenko, E. O., Pozhar, N. O., Anufriev, M. N., Trushechkin, A. S., Yunusov, R. R., Kurochkin, Y. V., Lvovsky, A. I., & Fedorov, A. K. (2018) · Quantum Science and Technology · doi:10.1088/2058-9565/aabc6b · Cited by 264 · see citing works
Smart contracts vulnerabilities: a call for blockchain software engineering?
Destefanis, G., Marchesi, M., Ortu, M., Tonelli, R., Bracciali, A., & Hierons, R. M. (2018) · doi:10.1109/iwbose.2018.8327567 · Cited by 257 · see citing works
Milutinovic, M., He, W., Wu, H., & Kanwal, M. (2016) · Workshop on System Software for Trusted Execution (SysTEX) · doi:10.1145/3007788.3007790 · Cited by 246 · see citing works
Decentralized Consensus for Edge-Centric Internet of Things: A Review, Taxonomy, and Research Issues
Yeow, K., Gani, A., Ahmad, R. W., Rodrigues, J. J. P. C., & Ko, K. (2017) · IEEE Access · doi:10.1109/access.2017.2779263 · Cited by 238 · see citing works
Kakavand, H., Sevres, N. K. D., & Chilton, B. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2849251 · Cited by 233 · see citing works
A Decentralized Approach for Anticipatory Vehicle Routing Using Delegate Multiagent Systems
Claes, R., Holvoet, T., & Weyns, D. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2105867 · Cited by 223 · see citing works
Decision Making in Multiagent Systems: A Survey
Rizk, Y., Awad, M., & Tunstel, E. W. (2018) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2018.2840971 · Cited by 219 · see citing works
Distributed Constraint Optimization Problems and Applications: A Survey
Fioretto, F., Pontelli, E., & Yeoh, W. (2018) · Journal of Artificial Intelligence Research · doi:10.1613/jair.5565 · Cited by 203 · see citing works
Intelligent Resource Management in Blockchain-Based Cloud Datacenters
Xu, C., Wang, K., & Guo, M. (2017) · IEEE Cloud Computing · doi:10.1109/mcc.2018.1081060 · Cited by 198 · see citing works
Validation and Verification of Smart Contracts: A Research Agenda
Magazzeni, D., McBurney, P., & Nash, W. (2017) · Computer · doi:10.1109/mc.2017.3571045 · Cited by 184 · see citing works
Securify: Practical Security Analysis of Smart ContractsPreprint
Tsankov, P., Dan, A., Drachsler-Cohen, D., Gervais, A., Bünzli, F., & Vechev, M. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.01143 · Cited by 167 · see citing works
Network Layer Aspects of Permissionless Blockchains
Neudecker, T., & Hannes Hartenstein, B. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2852480 · Cited by 165 · see citing works
A Survey of Self-Organization Mechanisms in Multiagent Systems
Ye, D., Zhang, M., & Vasilakos, A. V. (2016) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2015.2504350 · Cited by 163 · see citing works
Strobel, V., Castelló Ferrer, E., & Dorigo, M. (2018) · International Joint Conference on Autonomous Agents and Multiagent Systems · doi:10.65109/nlel1871 · Cited by 149 · see citing works
Özyılmaz, K. R., & Yurdakul, A. (2019) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2018.2880806 · Cited by 149 · see citing works
Proof of Vote: A High-Performance Consensus Protocol Based on Vote Mechanism & Consortium Blockchain
Li, K., Li, H., Hou, H., Li, K., & Chen, Y. (2017) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc-smartcity-dss.2017.61 · Cited by 133 · see citing works
A Blockchain-Based Decentralized Data Storage and Access Framework for PingER
Ali, S., Wang, G., White, B., & Cottrell, R. L. A. (2018) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom/bigdatase.2018.00179 · Cited by 120 · see citing works
Lv, C., Xing, Y., Lu, C., Liu, Y., Guo, H., Gao, H., & Cao, D. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2808359 · Cited by 113 · see citing works
FinBrain: when finance meets AI 2.0
Zheng, X., Zhu, M., Li, Q., Chen, C., & Tan, Y. (2019) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1700822 · Cited by 110 · see citing works
Kurtulmus, A. B., & Daniel, K. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.10185 · Cited by 107 · see citing works
Blockchain could boost food security
Ahmed, S., & ten Broek, N. (2017) · Nature · doi:10.1038/550043e · Cited by 105 · see citing works
Joint Semantic and Latent Attribute Modelling for Cross-Class Transfer Learning
Peng, P., Tian, Y., Xiang, T., et al. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2723882 · Cited by 102 · see citing works
Blockchain and Trusted Computing: Problems, Pitfalls, and a Solution for Hyperledger FabricPreprint
Brandenburger, M., Cachin, C., Kapitza, R., & Reiter, M. K. (2018) · arXiv (Cornell University) · doi:10.4230/lipics.opodis.2022.24 · Cited by 99 · see citing works
On-Device Federated Learning via Blockchain and its Latency Analysis.
Kim, H., Park, J., Bennis, M., & Kim, S. (2018) · Cited by 94 · see citing works
Deep Learning Stock Volatility with Google Domestic TrendsPreprint
Xiong, R., Nichols, E. P., & Shen, Y. K. (2015) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1512.04916 · Cited by 89 · see citing works
Sustainable blockchain through proof of exercise
Shoker, A. (2017) · IEEE International Symposium on Network Computing and Applications (NCA) · doi:10.1109/nca.2017.8171383 · Cited by 86 · see citing works
Blockchain-Based Decentralized Cloud/Fog Solutions: Challenges, Opportunities, and Standards
Uriarte, R. B., & Nicola, R. D. (2018) · IEEE Communications Standards Magazine · doi:10.1109/mcomstd.2018.1800020 · Cited by 84 · see citing works
A High Performance Blockchain Platform for Intelligent Devices
Yu, S., Lv, K., Shao, Z., Guo, Y., Zou, J., & Zhang, B. (2018) · International Conference on Hot Information-Centric Networking (HotICN) · doi:10.1109/hoticn.2018.8606017 · Cited by 81 · see citing works
Event stream-based process discovery using abstract representations
van Zelst, S. J., van Dongen, B. F., & van der Aalst, W. M. P. (2017) · Knowledge and Information Systems · doi:10.1007/s10115-017-1060-2 · Cited by 78 · see citing works
A Survey on the Security of Blockchain SystemsPreprint
Li, X., Jiang, P., Chen, T., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.06993 · Cited by 77 · see citing works
Research Directions in Blockchain Data Management and Analytics
Vo, H. T., Kundu, A., & Mohania, M. (2018) · Movebank · doi:10.5441/002/edbt.2018.43 · Cited by 77 · see citing works
Qi, Y., & Xiao, J. J. (2018) · Communications of the ACM · doi:10.1145/3239550 · Cited by 75 · see citing works
Socially Assistive Robotics: Robot Exercise Trainer for Older Adults
Lotfi, A., Langensiepen, C. S., & Yahaya, S. W. (2018) · Technologies · doi:10.3390/technologies6010032 · Cited by 74 · see citing works
The Swarm scalable storage system
Hartman, J. H., Murdock, I., & Spalink, T. (2003) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs.1999.776508 · Cited by 71 · see citing works
Blockchain and Artificial Intelligence
Marwala, T., & Xing, B. (2018) · arXiv · doi:10.48550/arxiv.1802.04451 · Cited by 62 · see citing works
AI researchers embrace Bitcoin technology to share medical data
Maxmen, A. (2018) · Nature · doi:10.1038/d41586-018-02641-7 · Cited by 58 · see citing works
Rehman, M. H. U., Liew, C. S., Wah, T. Y., & Khan, M. K. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.11.031 · Cited by 48 · see citing works
Self-citationArtificial Intelligence Is Becoming Natural
Koch, M. (2018) · Cell · doi:10.1016/j.cell.2018.04.007 · Cited by 48 · see citing works
Patient-controlled sharing of medical imaging data across unaffiliated healthcare organizations
Ge, Y., Ahn, D. K., Unde, B., Gage, H. D., & Carr, J. J. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001146 · Cited by 43 · see citing works
Boyen, X., Carr, C., & Haines, T. (2018) · doi:10.1145/3205230.3205235 · Cited by 39 · see citing works
A Comparative Study on Decision-Making Capability Between Human and Artificial Intelligence
Banerjee, S., Singh, P. K., & Bajpai, J. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-6747-1_23 · Cited by 37 · see citing works
Enlist blockchain to boost conservation
Baynham‐Herd, Z. (2017) · Nature · doi:10.1038/548523c · Cited by 30 · see citing works
A decentralization approach for swarm intelligence algorithms in networks applied to multi swarm PSO
Janson, S., Merkle, D., & Middendorf, M. (2008) · International Journal of Intelligent Computing and Cybernetics · doi:10.1108/17563780810857112 · Cited by 27 · see citing works
Towards Blockchain-Based Scalable and Trustworthy File Sharing
Cui, S., Asghar, M. R., & Russello, G. (2018) · International Conference on Computer Communications and Networks (ICCCN) · doi:10.1109/icccn.2018.8487379 · Cited by 27 · see citing works
Hwang, G., Chen, P., Lu, C.-H., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-94478-4_4 · Cited by 22 · see citing works
Distributed path planning for multi-robot teams based on Artificial Bee Colony
Contreras-Cruz, M. A., Lopez-Perez, J. J., & Ayala-Ramírez, V. (2017) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2017.7969358 · Cited by 18 · see citing works
Osaba, E., Onieva, E., Moreno, A., López-García, P., Perallos, A., & Bringas, P. G. (2016) · IET Intelligent Transport Systems · doi:10.1049/iet-its.2016.0047 · Cited by 14 · see citing works
Execution Models for Mobile Data Analytics
Rehman, M. H. U., Batool, A., Liew, C. S., et al. (2017) · IT Professional · doi:10.1109/mitp.2017.53 · Cited by 10 · see citing works
Self-citationRethinking Machine Learning Development and Deployment for Edge DevicesPreprint
Lai, L., & Suda, N. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.07846 · Cited by 9 · see citing works
Solving Large Problems with Heuristic Search: General-Purpose Parallel External-Memory Search
Hatem, M., Burns, E., & Ruml, W. (2018) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11209 · Cited by 8 · see citing works
Augmented Chain of Ownership: Configuring IoT Devices with the Help of the Blockchain
Dramé-Maigné, S., Laurent, M., Castillo, L., & Ganem, H. (2018) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-01701-9_4 · Cited by 5 · see citing works
An Overview of Blockchain Integration with Robotics and Artificial IntelligencePreprint
Lopes, V., & Alexandre, L. A. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.00329 · Cited by 3 · see citing works
FinBrain: When Finance Meets AI 2.0Preprint
Zheng, X., Zhu, M., Li, Q., et al. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.08497
Flagged first, then by citations
Research works printed but not linked: 12
- Y. Qi and J. Xiao, ''Fintech: Ai powers financial services to improve people's lives,'' Commun. ACM, vol. 61, no. 11, pp. 65-69, 2018.
- F. Fioretto, E. Pontelli, and W. Yeoh. (2016). ''Distributed constraint optimization problems and applications: A survey.'' [Online]. Available: https://arxiv.org/abs/1602.06347 · arXiv
- M. Feurer, K. Eggensperger, S. Falkner, M. Lindauer, and F. Hutter, ''Practical automated machine learning for the automl challenge 2018,'' in Proc. Int. Workshop Autom. Mach. Learn. (ICML), 2018, pp. 1-12.
- M. Zamani, M. Movahedi, and M. Raykova, ''RapidChain: Scaling blockchain via full sharding,'' in Proc. ACM SIGSAC Conf. Comput. Commun. Secur., 2018, pp. 931-948.
- K. R. Özyılmaz and A. Yurdakul. (2018). ''Designing a blockchain-based IoT infrastructure with ethereum, swarm and LoRa.'' [Online]. Available: https://arxiv.org/abs/1809.07655 · arXiv
- T. T. A. Dinh, J. Wang, G. Chen, R. Liu, B. C. Ooi, and K.-L. Tan, ''Blockbench: A framework for analyzing private blockchains,'' in Proc. ACM Int. Conf. Manage. Data, 2017, pp. 1085-1100.
- D. Joshi, ''IBM, Amazon & microsoft are offering their blockchain technology as a service,'' Bus. Insider, vol. 24, Oct. 2017. Accessed: Jan. 10, 2019. [Online]. Available: https://www. thewealthadvisor.com/article/ibm-amazon-microsoft-are-offering-their- blockchain-technology-service
- I. Sargeant and A. Tomlinson, ''Maliciously manipulating a robotic swarm,'' in Proc. ESCS 14th Int. Conf. Embedded Syst., Cyber-Phys. Syst., Appl., 2016, pp. 122-128.
- K. Peterson, R. Deeduvanu, P. Kanjamala, and K. Boles, ''A blockchain- based approach to health information exchange networks,'' in Proc. NIST Workshop Blockchain Healthcare, vol. 1, 2016, pp. 1-10.
- X. Boyen, C. Carr, and T. Haines, ''Graphchain: A blockchain-free scal- able decentralised ledger,'' in Proc. 2nd ACM Workshop Blockchains, Cryptocurrencies, Contracts, 2018, pp. 21-33.
- S. Tikhomirov, E. Voskresenskaya, I. Ivanitskiy, R. Takhaviev, E. Marchenko, and Y. Alexandrov, ''Smartcheck: Static analysis of ethereum smart contracts,'' in Proc. IEEE/ACM 1st Int. Workshop Emerg. Trends Softw. Eng. Blockchain (WETSEB), May/Jun. 2018, pp. 9-16.
- M. HABIB UR REHMAN was an Assistant Professor of computer science with the COMSATS Institute of IT, Wah Cantonment, Pakistan. His Ph.D. dissertation was with the Department of Computer Systems and Technology, University of Malaya, Kuala Lumpur. He is currently an Assis- tant Professor of computer science with the FAST National University of Computer and Emerging Sciences, Lahore, Pakistan. He focuses on big data analytics, the industrial Internet of Things, and blockchain technologies. He has authored or co-authored in 25 publications including 16 ISI-listed journal and magazine articles, three IEEE conference proceedings, and two book chapters. His research interests include wide spectrum of application areas including smart cities, blockchain, mobile social networks, quantified self, mHealth, and wearable assistive technolo- gies among many others. His key research interests include mobile comput- ing, edge-cloud computing, blockchain technologies, the Internet of Things, data mining, machine learning, and mobile distributed analytics.
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Self-citation
- Authors
- Salah, K., Rehman, M. H. U., Nizamuddin, N., & Al-Fuqaha, A.
- Affiliations
- Khalifa University of Science and Technology (AE)
- National University of Computer and Emerging Sciences (PK)
- Corresponding author
- Salah, Khaled
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 10127-10149
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2907683311
- Cited by
- 1,001
- References
- 103
- Citations by year
- 2026: 69 · 2025: 132 · 2024: 141 · 2023: 168 · 2022: 149 · 2021: 142 · 2020: 134 · 2019: 65 · 2017: 1
- FWCI
- 152.42
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- blockchain, artificial intelligence, smart contracts, distributed ledger technology, cryptocurrency, open problems
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