This paper explores the integration of machine learning, specifically recurrent neural
networks (RNNs), for automated anomaly detection within NoSQL databases. It addresses …

In this paper, we propose a new framework for mitigating biases in machine learning
systems. The problem of the existing mitigation approaches is that they are model-oriented …

Due to the proliferation of requests in heterogeneous resources in edge computing, the
existence of a large number of tasks and workloads in virtual machines in the edge …

Resource-constrainted and located closer to users, edge servers are more vulnerable to
Distributed Denial of Service (DDoS) attacks. In order to mitigate the impact of DDoS attacks …

Supporting security and data privacy in cloud workflows has attracted significant research
attention. For example, private patients' data managed by a workflow deployed on the cloud …

Vehicular crowdsourcing is an emerging mobile sensing-based paradigm in which a service
platform manages the allocation of data collection and processing tasks to vehicles …

A secure execution of offloaded tasks in the 5G-driven mobile edge computing (MEC)
deployment is critical for all societal sectors. To realize it, mobile network operators have to …

Abstract Mobile Edge Computing (MEC) over a densified 5G wireless network deployment
arises as an effective response to the skyrocketing demand for latency-driven mobile …

Mobile cloud computing MCC provide to a certain extent many settlement like battery timing,
memory, consistency and scalability. Though, still there some sort essential elements, those …

Ensuring security and safeguarding data privacy within cloud workflows has garnered
considerable attention in research circles. For instance, protecting the confidentiality of …