Context-driven Policies Enforcement for Edge-based IoT Data Sharing-as-a-Service

Sharing real-time data originating from connected devices is crucial to real-world intelligent Internet of Things (IoT) applications, i.e., based on artificial intelligence/machine learning (AI/ML). Such IoT data sharing involves multiple parties for different purposes and is usually based on data contracts that might depend on the dynamic change of IoT data variety and velocity. It is still an open challenge to support multiple parties (aka tenants) with these dynamic contracts based on the data value for their specific contextual purposes.This work addresses these challenges by introducing a novel dynamic context-based policy enforcement framework to support IoT data sharing (on-Edge) based on dynamic contracts. Our enforcement framework allows IoT Data Hub owners to define extensible rules and metrics to govern the tenants in accessing the shared data on the Edge based on policies defined with static and dynamic contexts. We have developed a proof-of-concept prototype for sharing sensitive data such as surveillance camera videos to illustrate our proposed framework. The experimental results demonstrated that our framework could soundly and timely enforce context-based policies at runtime with moderate overhead. Moreover, the context and policy changes are correctly reflected in the system in nearly real-time.acceptedVersio

Migrating Monoliths to Microservices-based Customizable Multi-tenant Cloud-native Apps

It was common that software vendors sell licenses to their clients to use software products, such as Enterprise Resource Planning, which are deployed as a monolithic entity on clients’ premises. Moreover, many clients, especially big organizations, often require software products to be customized for their specific needs before deployment on premises. While software vendors are trying to migrate their monolithic software products to Cloud-native Software-as-a-Service (SaaS), they face two big challenges that this paper aims at addressing: 1) How to migrate their exclusive monoliths to multi-tenant Cloud-native SaaS; and 2) How to enable tenant-specific customization for multi-tenant Cloud-native SaaS. This paper suggests an approach for migrating monoliths to microservice-based Cloud-native SaaS, providing customers with a flexible customization opportunity, while taking advantage of the economies of scale that the Cloud and multi-tenancy provide. Our approach shows not only the migration to microservices but also how to introduce the necessary infrastructure to support the new services and enable tenant-specific customization. We illustrate the application of our approach on migrating a reference application of Microsoft called SportStore.acceptedVersio

Exploiting secure performance of full-duplex decode and forward in optimal relay selection networks

In the presence of an illegitimate user, we investigate the secrecy outage probability (SOP) of the optimal relay selection (ORS) networks by applying decode-and-forward (DnF) based full-duplex (FD) relaying mode. The closed-form expressions for the allocations of the end-to-end signal-to-interference-plus-noise ratio (SINR) in each wireless network are derived as well as the closed-form expression for the exact SOP of the proposed ORS system is presented under Rayleigh fading schemes. As an important achievement, SOP is also compared between orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) schemes. Our results reveal that the SOP of the suggested scheme can be considerably influenced by several parameters involved, including the number of relays, the average signal-to-noise ratio (SNR) of eavesdropper links, transmit power and the average residual self-interference (SI) enforced on the FD relays.Web of Science244767

Examination of influential factors on shear strength of externally bonded FRP reinforcement in RC beams

The fiber-reinforced polymer (FRP) retrofitting technique has been increasingly created to enhance the capacity of the existing concrete members. In this study, the shear contribution of the external FRP strengthening system in the reinforced concrete (RC) beams is estimated by the semi-empirical models available in the open literatures and guidelines. Number of beams monitored in the previous studies are first considered to assess the reliability of the models. Afterwards, the investigation of influential factors such as the beam configurations, the strengthening characteristics and the material properties are implemented. With high accuracy and low coefficient of variation, the model proposed in a previous study of the authors gains the mostly considerable estimation for the shear resisting strength of FRP strengthening system compared to the accessible data base from the experiments. In addition, the critical properties of the materials associating with the retrofitting systems for the strengthened beams are investigated to obtain the acquired shear performance

Examination of influential factors on shear strength of externally bonded FRP reinforcement in RC beams

The fiber-reinforced polymer (FRP) retrofitting technique has been increasingly created to enhance the capacity of the existing concrete members. In this study, the shear contribution of the external FRP strengthening system in the reinforced concrete (RC) beams is estimated by the semi-empirical models available in the open literatures and guidelines. Number of beams monitored in the previous studies are first considered to assess the reliability of the models. Afterwards, the investigation of influential factors such as the beam configurations, the strengthening characteristics and the material properties are implemented. With high accuracy and low coefficient of variation, the model proposed in a previous study of the authors gains the mostly considerable estimation for the shear resisting strength of FRP strengthening system compared to the accessible data base from the experiments. In addition, the critical properties of the materials associating with the retrofitting systems for the strengthened beams are investigated to obtain the acquired shear performance

Secrecy performance analysis on spatial modeling of wireless communications with unmanned aerial vehicle and ground devices

In this paper, the secrecy performance of the spatial modeling for ground devices with randomly placed eavesdroppers when an unmanned aerial vehicle (UAV) acted as two hops decode and forward (DF) was investigated. We characterize the secrecy outage probability (SOP) and intercept probability (IP) expressions. Our capacity performance analysis is based on the Rayleigh fading distributions. After analytical results by Monte Carlo simulation, and the Gauss-Chebyshev parameter was selected to yield a close approximation, the results demonstrate the SOP with the average signal-to-noise ratio (SNR) between UAV and ground users among the eavesdroppers and the IP relationship with the ability to intercept the information of the ground users successfully

Model-based Continuous Deployment of SIS

This chapter is organized as follows. Section 4.2 provides an overview of the current state of the art and of the practice for the automatic deployment of SIS. Section 4.3 introduces our solutions for the automatic deployment of SIS, first describing how they can be integrated in order to form a coherent deployment bundle and then detailing each our two enablers: GENESIS and DivENACT. Section 4.4 focus on the support offered by our solutions to ensure the trustworthiness deployment of SIS. Finally, Section 4.5 draws some conclusions.publishedVersio

A Systematic Mapping Study on Approaches for AI-Supported Security Risk Assessment

Effective assessment of cyber risks in the increasingly dynamic threat landscape must be supported by artificial intelligence techniques due to their ability to dynamically scale and adapt. This article provides the state of the art of AI-supported security risk assessment approaches in terms of a systematic mapping study. The overall goal is to obtain an overview of security risk assessment approaches that use AI techniques to identify, estimate, and/or evaluate cyber risks. We carried out the systematic mapping study following standard processes and identified in total 33 relevant primary studies that we included in our mapping study. The results of our study show that on average, the number of papers about AI-supported security risk assessment has been increasing since 2010 with the growth rate of 133% between 2010 and 2020. The risk assessment approaches reported have mainly been used to assess cyber risks related to intrusion detection, malware detection, and industrial systems. The approaches focus mostly on identifying and/or estimating security risks, and primarily make use of Bayesian networks and neural networks as supporting AI methods/techniques.acceptedVersio

STUDENTS’ OPINIONS ON VOCATIONAL GUIDANCE: A CASE STUDY

The problem of employment is always a crucial problem and is the concern of most parents and school students. The survey on the perception of 40 students about vocational guidance was carried out in Nguyen Viet Dung High School in Can Tho City, Vietnam. Results show that students are very concerned about their future career; students have a proper perception of vocational guidance and recognize well factors which affect their career choice.  Article visualizations