Search

Cloud computing plays a vital role in processing a large amount of data. However, with the arrival of the Internet of Things, huge data are generated from these devices. Thus, there is the need for bringing characteristics of cloud closer to the request generator, so that processing of these huge data takes place at one-hop distance closer to that end user. This led to the emergence of fog computing with the aim to provide storage and computation at the edge of the network that reduces network traffic and overcomes many cloud computing drawbacks. Fog computing technology helps to overcome challenges of big data processing. The paper discusses the taxonomy of fog computing, how this is different from cloud computing and edge computing technologies, its applications, emerging key technologies (i.e., communication technologies and storage technologies) and various challenges involved in fog technology. [ABSTRACT FROM AUTHOR]

In today's world, data leakage on computer systems, Internet of Things (IoT) devices, or mobile devices carriages a significant threat due to weaker encryption or communication techniques, resulting in the loss of data items. Identifying the leakage of sensitive data during data transmission requires an appropriate technique. In the IoT environment, default permissions granted to devices often lead to data leakage. This proposed method offers data leakage security based on data sensitivity. However, classifying sensitive data is challenging due to its large volume and data transformation. The proposed technique utilizes the minimum redundancy and maximum relevancy (mRMR) technique for feature selection. It accurately detects confidential data better than existing state-of-the-art methods and can identify rephrased confidential contents using filter-based features for sequential data leak deterrence. Specifically, data leakage measurement can be achieved using DBSCAN (Density-based Spatial Clustering of Applications with Noise) to average F-statistical values measured over individual time steps and to ensure continuity between leakage data points. [ABSTRACT FROM AUTHOR]