TY - GEN
T1 - An Efficient Secure Coded Edge Computing Scheme Using Orthogonal Vector
AU - Zhou, Wei
AU - Wang, Jin
AU - Li, Lingzhi
AU - Wang, Jianping
AU - Lu, Kejie
AU - Zhou, Xiaobo
PY - 2019/12
Y1 - 2019/12
N2 - In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. 0 ©2019 IEEE.
AB - In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. In recent years, Edge Computing (EC) has attracted increasing attention for its advantages in handling latencysensitive and compute-intensive applications. It is becoming a widespread solution to solve the last mile problem of cloud computing. However, in actual EC deployments, data confidentiality becomes an unignorable issue because edge devices may be untrusted. In this paper, a secure and efficient edge computing scheme based on linear coding is proposed. Generally, linear coding can be utilized to achieve data confidentiality by encoding random blocks with original data blocks before they are distributed to unreliable edge nodes. However, the addition of a large amount of irrelevant random blocks also brings great communication overhead and high decoding complexities. In this paper, we focus on the design of secure coded edge computing using orthogonal vector to protect the information theoretic security of the data matrix stored on edge nodes and the input matrix uploaded by the user device, while to further reduce the communication overhead and decoding complexities. 0 ©2019 IEEE.
KW - Data security
KW - Edge computing
KW - Information theoretical security
KW - Linear coding
KW - Orthogonal vector
UR - https://www.scopus.com/pages/publications/85085530905
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85085530905&origin=recordpage
U2 - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00025
DO - 10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00025
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781728143286
T3 - Proceedings - IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking, ISPA/BDCloud/SustainCom/SocialCom
SP - 100
EP - 107
BT - Proceedings - 2019 IEEE Intl Conf on Parallel and Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking, ISPA/BDCloud/SustainCom/SocialCom 2019s
PB - IEEE
T2 - 17th IEEE International Conference on Parallel and Distributed Processing with Applications, 9th IEEE International Conference on Big Data and Cloud Computing, 9th IEEE International Conference on Sustainable Computing and Communications, 12th IEEE International Conference on Social Computing and Networking (ISPA/BDCloud/SustainCom/SocialCom 2019s)
Y2 - 16 December 2019 through 18 December 2019
ER -