A survey of privacy-preserving offloading methods in mobile-edge computing

Li, Tianheng; He, Xiaofan; Jiang, Shaojun; Liu, Juan

doi:10.1016/j.jnca.2022.103395

Cited by 35 publications

(9 citation statements)

References 201 publications

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“…Based on homomorphic encryption: Freedman and his team [9] innovatively represented elements as roots of polynomials and encrypted the coefficients of these polynomials using Paillier homomorphic encryption technology, combined with zero-knowledge proofs, to implement a two-party PSI protocol resistant to malicious attacks. In 2016, Freedman et al [10] further improved computational efficiency through the ElGamal encryption mechanism and reduced the protocol's computational complexity using Cuckoo Hash technology [4]. Abadi et al [11] introduced a set representation method based on point-value pairs of d-degree polynomials, implemented through the Paillier encryption scheme, reducing the multiplication complexity from O(d 2 ) to O(d) [4].…”

Section: Design Framework Based On Public Key Encryptionmentioning

confidence: 99%

Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks

Tan,

Du,

Weng

2024

Preprint

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Private Set Intersection Cardinality(PSI-CA) is a cryptographic method in secure multi-party computation that allows entities to identify cardinality of the intersection without revealing their private data.Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances.In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI-CA protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI-CA protocols to these imbalances is crucial.This paper explores unbalanced scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities.This paper, based on the concept of commutative encryption, introduces Cuckoo filter, cloud computing technology, homomorphic encryption, among other technologies, to construct three novel solutions for unbalanced Private Set Intersection Cardinality (PSI-CA): an unbalanced PSI-CA protocol based on Cuckoo filter, an unbalanced PSI-CA protocol based on single cloud assistance, and an unbalanced PSI-CA protocol based on dual cloud assistance. Depending on performance and security requirements, different protocols can be employed for various applications.

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Section: Design Framework Based On Public Key Encryptionmentioning

confidence: 99%

Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks

Tan,

Du,

Weng

2024

Preprint

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“…Three types of privacy-preserving offloading in MEC namely organizing the offloading data, transferring offloaded data, and selecting the appropriate destination for offloading are discussed in this research work. 50 A three-layer cloudlet model 51 is implemented to provide a load balancing scheme during the larger number of mobile edge servers and user requests. The simulation results under various network sizes depict a significant reduction in intra-cluster load balancing.…”

Section: Research Backgroundmentioning

confidence: 99%

“…The issues required to minimize energy consumption, delay, and also parameters to increase revenue and system utilizations are addressed in this research work. Three types of privacy‐preserving offloading in MEC namely organizing the offloading data, transferring offloaded data, and selecting the appropriate destination for offloading are discussed in this research work 50 …”

Section: Research Backgroundmentioning

confidence: 99%

A generic resource augmentation architecture for efficient mobile communication

Anitha

Padma²,

Vallimayil

2023

Concurrency and Computation

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SummaryMobile devices play a vital role in people's day‐to‐day activities and are essential for communication, accessing Internet resources, entertainment, and so forth. In most cases, the performance of mobile applications is restricted due to the inadequate resources of mobile specifications such as controlled battery power, predetermined storage, and limited processing competence. Thus to improve the processing efficiency of resource‐constrained mobile devices, this research proposes a model developed on offloading technique based on the recent literature observations which transfer the resource‐consuming tasks from mobile devices to proximate computing entities. This generic architecture aiming for resource augmentation is formulated with five fundamental components including a mobile device, offloading engine, resource augmentation engine, scheduler, and synchronizer. The offloading engine identifies the resource‐intensive tasks that need to be executed on external entities using soft computing techniques such as neural network training algorithms, fuzzy logic, and neuro‐fuzzy logic processing. The augmentation engine chooses feasible edge computing entities such as Arduino, Raspberry PI controller, and fog devices. The scheduler prioritizes the resource‐consuming tasks for offloading based on their importance. The synchronizer coordinates all the central components by updating the execution status of tasks at regular intervals of time. Further extension of this research work, based on the proposed architecture three resource augmentation frameworks are developed namely (a) an adaptive proximate computing framework (b) a web service‐based IoT framework, and (c) a neuro‐fuzzy hybrid framework. Moreover, these frameworks are realized through the development of resource‐efficient intelligent edge computing IoT mobile apps namely (a) an inventory monitoring app (b) a lecture recording app, and (c) an intelligent transport app. The performance of these three resource augmentation frameworks is analyzed through the simulation results and it illustrates that the neuro‐fuzzy hybrid framework outperforms the other two. The outcome of the proposed research contributions improves the effectiveness of mobile communication by providing seamless services to mobile users regardless of their resource‐limited devices. Besides the devised edge computing architecture supports mobile application developers in the design and deployment of resource‐rich mobile applications in low‐specification mobile devices. Also, there is a strong scope for implementing the proposed generic architecture as an industrial smart product with adequate hardware and software configurations.

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“…They covered offloading decisions and resource-allocation techniques in their surveys. The authors in [ 26 ] discussed privacy issues in offloading and classified various privacy-preserving offloading techniques. Reference [ 27 ] discussed the path planning techniques for UAVs.…”

Section: Introductionmentioning

confidence: 99%

Trajectory-Aware Offloading Decision in UAV-Aided Edge Computing: A Comprehensive Survey

Baidya,

Nabi,

Moh

2024

Sensors

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Recently, the integration of unmanned aerial vehicles (UAVs) with edge computing has emerged as a promising paradigm for providing computational support for Internet of Things (IoT) applications in remote, disaster-stricken, and maritime areas. In UAV-aided edge computing, the offloading decision plays a central role in optimizing the overall system performance. However, the trajectory directly affects the offloading decision. In general, IoT devices use ground offload computation-intensive tasks on UAV-aided edge servers. The UAVs plan their trajectories based on the task generation rate. Therefore, researchers are attempting to optimize the offloading decision along with the trajectory, and numerous studies are ongoing to determine the impact of the trajectory on offloading decisions. In this survey, we review existing trajectory-aware offloading decision techniques by focusing on design concepts, operational features, and outstanding characteristics. Moreover, they are compared in terms of design principles and operational characteristics. Open issues and research challenges are discussed, along with future directions.

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A survey of privacy-preserving offloading methods in mobile-edge computing

Cited by 35 publications

References 201 publications

Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks

Enhancing Efficiency and Security in Unbalanced PSI-CA Protocols through Cloud Computing and Homomorphic Encryption in Mobile Networks

A generic resource augmentation architecture for efficient mobile communication

Trajectory-Aware Offloading Decision in UAV-Aided Edge Computing: A Comprehensive Survey

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