|Author||Yang, Xinyu ♦ He, Xiaofei ♦ Yu, Wei ♦ Lin, Jie ♦ Li, Rui ♦ Yang, Qingyu ♦ Song, Houbing|
|Source||World Health Organization (WHO)-Global Index Medicus|
|Publisher||Multidisciplinary Digital Publishing Institute|
|File Format||HTM / HTML|
|Subject Domain (in DDC)||Technology ♦ Medicine & health|
|Abstract||In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes.|
|Description||Country affiliation: China
Author Affiliation: Yang X ( Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. firstname.lastname@example.org.); He X ( Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. email@example.com.); Yu W ( Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA. firstname.lastname@example.org.); Lin J ( Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. email@example.com.); Li R ( Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China. firstname.lastname@example.org.); Yang Q ( SKLMSE Lab, School of Electronic Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China. email@example.com.); Song H ( Department of Electrical and Computer Engineering, West Virginia University, Montgomery, WV 25136, USA. Houbing.Song@mail.wvu.edu.)
|Educational Role||Student ♦ Teacher|
|Age Range||above 22 year|
|Educational Use||Reading ♦ Research ♦ Self Learning|
|Education Level||UG and PG|
|Learning Resource Type||Article|
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