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JONGHYUP LEE received the B.S. degree in electronic engineering from Yonsei University, Seoul, Korea, in 2002, and the M.S. and Ph.D. degrees in computer science from Yonsei University in 2004 and 2009, respectively. From 2009 to 2012, he was a Postdoctoral Researcher at CyLab, Carnegie Mellon University and, from 2012 to 2015, an Assistant Professor of Software at Korea National University of Transportation. Currently, he is an Associate Professor of Mathematical Finance at Gachon University. His research interests include smart contract engineering, software security, and blockchain systems.
The Industrial Internet of Things (IIoT) could enhance automation and analytics in industrial environments. Despite the promising benefits of IIoT, securely managing software updates is a challenging problem for those critical applications. This is due to at least the intrinsic lack of software protection mechanisms in legacy industrial systems. In this paper, to address the challenges in building a secure software supply chain for industrial environments, we propose a new approach that leverages distributed watchdogs with blockchain systems in protecting software supply chains. For this purpose, we bind every entity with a unique identity in the blockchain and employ the blockchain as a delegated authenticator by mapping every reporting action to a non-fungible token transfer. Moreover, we present a detailed specification to clearly define the behavior of systems and to apply model checking.
JongHyup Lee; Taekyoung Kwon. Distributed Watchdogs Based on Blockchain for Securing Industrial Internet of Things. Sensors 2021, 21, 4393 .
AMA StyleJongHyup Lee, Taekyoung Kwon. Distributed Watchdogs Based on Blockchain for Securing Industrial Internet of Things. Sensors. 2021; 21 (13):4393.
Chicago/Turabian StyleJongHyup Lee; Taekyoung Kwon. 2021. "Distributed Watchdogs Based on Blockchain for Securing Industrial Internet of Things." Sensors 21, no. 13: 4393.
We address the absence of reliable tests on contract analyzers of smart contracts and present a systematic method to diversify test cases by combining smart-contract-specific bugs and static analysis barriers in this paper. Using contract analyzers is the most practical solution for building a secure blockchain service, but they are relatively immature and lacking stable performance metrics. Traditionally, performance reports only compare static contract analyzers with pre-defined test cases, such as the Juliet test suite. However, building such test suites is burdensome for smart contracts, which are frequently change. In this paper, we propose an automated method to assess contract analyzers of smart contracts by diversifying test cases. In the experimental results, we identified nine erroneous alarms in the state-of-the-art contract analyzers with automatically generated test cases on five vulnerabilities.
Ki Byung Kim; JongHyup Lee. Automated Generation of Test Cases for Smart Contract Security Analyzers. IEEE Access 2020, 8, 209377 -209392.
AMA StyleKi Byung Kim, JongHyup Lee. Automated Generation of Test Cases for Smart Contract Security Analyzers. IEEE Access. 2020; 8 (99):209377-209392.
Chicago/Turabian StyleKi Byung Kim; JongHyup Lee. 2020. "Automated Generation of Test Cases for Smart Contract Security Analyzers." IEEE Access 8, no. 99: 209377-209392.
Smart contracts on blockchain systems implement business logic and directly handle important assets. Although smart contracts play these critical roles, it is hard for users interacting with the system to understand the real behavior of the deployed bytecodes of smart contracts. The quirks of smart contracts, such as code reuse and limited unique datasets, make it challenging to recognize the functional details of smart contracts. In this paper, we propose a new method for characterizing bytecode-only smart contracts by automatically assigning multiple attribute tags. Using a deep learning approach our system, ScanAT, extracts attribute tags from the source code and metadata of known smart contracts and trains their bytecode with the attribute tags. ScanAT then infers attribute tags from the bytecode of smart contracts alone. Our experiments show that ScanAT can achieve 81% accuracy in predicting attribute tags, using convolutional neural networks and a customized autoencoder.
Yuntae Kim; Dohyun Pak; JongHyup Lee. ScanAT: Identification of Bytecode-Only Smart Contracts With Multiple Attribute Tags. IEEE Access 2019, 7, 98669 -98683.
AMA StyleYuntae Kim, Dohyun Pak, JongHyup Lee. ScanAT: Identification of Bytecode-Only Smart Contracts With Multiple Attribute Tags. IEEE Access. 2019; 7 (99):98669-98683.
Chicago/Turabian StyleYuntae Kim; Dohyun Pak; JongHyup Lee. 2019. "ScanAT: Identification of Bytecode-Only Smart Contracts With Multiple Attribute Tags." IEEE Access 7, no. 99: 98669-98683.
The swarm attestation methods have been proposed to detect illegitimate modifications in a large network efficiently. However, they do not provide the scalable identification of detected devices, which is critical to keep a swarm network trustworthy in the practical uses. In this paper, we propose a lightweight attestation method with efficient scalable identification of target devices. The proposed approach, called (Collective Attestation for Manageable IoT Environments), combines binary-embedded tag generation and regional reports to build the region-based attestation result. During the attestation process, the swarm network generates merged region summaries. An authorized verifier can infer the individual device information from the regional attestation results. In this way, can achieve the scalable identification of compromised devices with significantly less overhead.
JongHyup Lee. Collective Attestation for Manageable IoT Environments. Applied Sciences 2018, 8, 2652 .
AMA StyleJongHyup Lee. Collective Attestation for Manageable IoT Environments. Applied Sciences. 2018; 8 (12):2652.
Chicago/Turabian StyleJongHyup Lee. 2018. "Collective Attestation for Manageable IoT Environments." Applied Sciences 8, no. 12: 2652.
In the complicated settings of WSN (Wireless Sensor Networks) and IoT (Internet of Things) environments, keeping a number of heterogeneous devices updated is a challenging job, especially with respect to effectively discovering target devices and rapidly delivering the software updates. In this paper, we convert the traditional software update process to a distributed service. We set an incentive system for faithfully transporting the patches to the recipient devices. The incentive system motivates independent, self-interested transporters for helping the devices to be updated. To ensure the system correctly operates, we employ the blockchain system that enforces the commitment in a decentralized manner. We also present a detailed specification for the proposed protocol and validate it by model checking and simulations for correctness.
JongHyup Lee. Patch Transporter: Incentivized, Decentralized Software Patch System for WSN and IoT Environments. Sensors 2018, 18, 574 .
AMA StyleJongHyup Lee. Patch Transporter: Incentivized, Decentralized Software Patch System for WSN and IoT Environments. Sensors. 2018; 18 (2):574.
Chicago/Turabian StyleJongHyup Lee. 2018. "Patch Transporter: Incentivized, Decentralized Software Patch System for WSN and IoT Environments." Sensors 18, no. 2: 574.
For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.
JongHyup Lee; Dohyun Pak. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks. Sensors 2016, 16, 1380 .
AMA StyleJongHyup Lee, Dohyun Pak. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks. Sensors. 2016; 16 (9):1380.
Chicago/Turabian StyleJongHyup Lee; Dohyun Pak. 2016. "A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks." Sensors 16, no. 9: 1380.
Dohyun Pak; JongHyup Lee. A lightweight detection mechanism of control flow modification for IoT devices. Journal of the Korea Institute of Information Security and Cryptology 2015, 25, 1449 -1453.
AMA StyleDohyun Pak, JongHyup Lee. A lightweight detection mechanism of control flow modification for IoT devices. Journal of the Korea Institute of Information Security and Cryptology. 2015; 25 (6):1449-1453.
Chicago/Turabian StyleDohyun Pak; JongHyup Lee. 2015. "A lightweight detection mechanism of control flow modification for IoT devices." Journal of the Korea Institute of Information Security and Cryptology 25, no. 6: 1449-1453.
JongHyup LEE; Taekyoung Kwon. Secure Authentication Scheme with Improved Anonymity for Wireless Environments. IEICE Transactions on Communications 2011, E94-B, 554 -557.
AMA StyleJongHyup LEE, Taekyoung Kwon. Secure Authentication Scheme with Improved Anonymity for Wireless Environments. IEICE Transactions on Communications. 2011; E94-B (2):554-557.
Chicago/Turabian StyleJongHyup LEE; Taekyoung Kwon. 2011. "Secure Authentication Scheme with Improved Anonymity for Wireless Environments." IEICE Transactions on Communications E94-B, no. 2: 554-557.
A practical pairwise key distribution scheme is necessary for wireless sensor networks since sensor nodes are susceptible to physical capture and constrained in their resources. In this paper, we investigate a simple and practical scheme that achieves higher connectivities and perfect resilience with less resources, even in case of deployment errors.
Taekyoung Kwon; JongHyup Lee; JooSeok Song. Location-based pairwise key predistribution for wireless sensor networks. IEEE Transactions on Wireless Communications 2009, 8, 5436 -5442.
AMA StyleTaekyoung Kwon, JongHyup Lee, JooSeok Song. Location-based pairwise key predistribution for wireless sensor networks. IEEE Transactions on Wireless Communications. 2009; 8 (11):5436-5442.
Chicago/Turabian StyleTaekyoung Kwon; JongHyup Lee; JooSeok Song. 2009. "Location-based pairwise key predistribution for wireless sensor networks." IEEE Transactions on Wireless Communications 8, no. 11: 5436-5442.
It is a recent trend to consider wireless sensor networks in harsh industrial environments. With actual deployment of wireless sensor networks, it would be desirable to make a concrete deployment plan regarding connectivities and to place sensors by grouping them according to the planned deployment points, even more in case of targeting multiple objects to be sensed and monitored in harsh environments. The connectedness of groups as well as individual sensors is important specifically for real-time data acquisitions and even more if there are no external communication links among these groups. In this paper, we focus on the connectivity of sensor groups, rather than the individual sensors only, and propose a novel group connectivity model so as to analyze group connectivity and to make a concrete deployment plan of sensor groups with regard to the internal distribution of sensors and group positions. We believe that the proposed model should be useful in planning the deployment of wireless sensor networks in harsh industrial environments where running wires is less practical and also prohibitively expensive.
JongHyup Lee; Taekyoung Kwon; JooSeok Song. Group Connectivity Model for Industrial Wireless Sensor Networks. IEEE Transactions on Industrial Electronics 2009, 57, 1835 -1844.
AMA StyleJongHyup Lee, Taekyoung Kwon, JooSeok Song. Group Connectivity Model for Industrial Wireless Sensor Networks. IEEE Transactions on Industrial Electronics. 2009; 57 (5):1835-1844.
Chicago/Turabian StyleJongHyup Lee; Taekyoung Kwon; JooSeok Song. 2009. "Group Connectivity Model for Industrial Wireless Sensor Networks." IEEE Transactions on Industrial Electronics 57, no. 5: 1835-1844.