With the advance of machine learning and the internet of things (IoT), security and privacy have become key concerns in mobile services and networks. Transferring data to a central unit violates privacy as well as protection of sensitive data while increasing bandwidth demands.Federated learning miti...
Detecting anomalies, intrusions, and security threats in the network (including Internet of Things) traffic necessitates the processing of large volumes of sensitive data, which raises concerns about privacy and security. Federated learning, a distributed machine learning approach, enables multiple parties...
Hypermine smart tools and protocols for Identity, Privacy & Security, with our roots in Distributed Systems, Machine Learning & Cryptography. - - - - Entropy1729 Zero Knowledge Shop - - - - Trivium provides validator services to serveral networks, and develops privacy-preserving dApps Github - -...
Training usually requires privacy-sensitive local data, for instance, adjusting the communication rate based on citizens' mobility. This paper studies the following research question: How feasible is to train with privacy-preserving aggregate data and test on local data to improve cost-effectiveness of...
However, we are still able to ensure that nothing about the sensitive data beyond the desired frequencies is revealed to the data miner. To illustrate the power of our approach, we use our frequency mining computation to obtain a privacy- preserving naive Bayes classifler learning algorithm. ...
Poor, "Cost-effective and privacy- preserving energy management for smart meters," IEEE Trans. on Smart Grid, vol. 6, ... Zuo,Cong,Liang,... - 《Personal & Ubiquitousuting》 被引量: 4发表: 2017年 Privacy-cost trade-offs in smart electricity metering systems Trade-offs between privacy ...
In privacy-preserving data mining, sensitive data are perturbed by adding noise to a statistical distribution [48]. This technique works well when a large data set is provided and aggregated results such as summation or average are needed. This technique is not feasible in intrusion detection ...
On the other hand, preserving the privacy of intermediate dataset becomes a big problem because adversaries may recover the sensitive data by analysing multiple intermediate datasets. Encrypting all the data in the cloud is hugely adopted in the present system that approaches to address this challenge...
Our design is based on the DAC single-server model and realizes the preservation of the privacy of the client’s data and machine learning model through a novel norm-preserving matrix transformation technique combining with random permutations. Also, our design enables the client CRediT authorship ...
Privacy Preserving Data Mining (PPDM) is used to extract relevant knowledge from large amount of data and at the same time protect the sensitive informatio... MS Ramya - 《Bonfring International Journal of Software Engineering & Soft Computing》 被引量: 3发表: 2012年 Twins (1): Extending SQ...