Trustworthy Service Research Articles

Placement of Social Digital Twins at the Edge for Beyond 5G IoT Networks

As the fifth-generation (5G) and beyond (5G+/6G) networks move forward, and a wide variety of new advanced Internet of Things (IoT) applications are offered, effective methodologies for discovering time-relevant information, services, and resources are being demanded. To this end, computing-, storage-, and battery-constrained IoT devices are progressively augmented via digital twins (DTs) hosted on edge servers. According to recent research results, a further feature these devices may acquire is social behavior; this latter offers enormous possibilities for fast and trustworthy service discovery, although it requires new orchestration policies of DTs at the network edge. This work addresses the dynamic placement of DTs with social capabilities [social digital twins (SDTs)] at the edge, by providing an optimal solution under IoT device mobility and by accounting for edge network deployment specifics, types of devices, and their social peculiarities. The optimization problem is formulated as a particular case of the quadratic assignment problem (QAP); also, an approximation algorithm is proposed and two relaxation techniques are applied to reduce computation complexity. Results show that the proposed placement policy ensures a latency among SDTs up to 1.4 times lower than the one obtainable with a traditional proximity-based only placement while still guaranteeing appropriate proximity between physical devices and their virtual counterparts. Moreover, the proposed heuristic closely approximates the optimal solution while guaranteeing the lowest computational time.

Performance Evaluation for Secure Communications in Mobile Internet of Vehicles With Joint Reactive Jamming and Eavesdropping Attacks

Internet of Vehicles (IoV) is considered to be a backbone of smart transportation system where vehicles are expected to exchange traffic information and other data using vehicle-to-vehicle (V2V) communications. Furthermore, V2V communications is regarded as a medium to send upcoming traffic information to vehicles/drivers or passengers using wireless technology in a timely manner. This will help reduce traffic accidents, traffic jams, fuel consumption caused by traffic jams, loss of hours caused by delayed commuting and carbon emission caused by vehicles. Because of the critical nature of IoV for smart transportation systems, secure wireless communication is one of the critical and essential components to offer trustworthy services through IoV. Like in other wireless systems, wireless communication is open in air, which makes attackers’ job easy to launch the malicious actions in IoV. In this paper, we investigate the impact of mobility of vehicles for secure communications in IoV with joint jamming and eavesdropping attacks. We investigate different scenarios, when vehicles (legitimate ones and attackers) travel in same and opposite directions with low speed (school zone speed) limit to highway speed limit. Furthermore, we study the impact of association time and encryption time not only for establishing the connection between vehicles for V2V communications but also for exchanging messages for vehicles after successful association between vehicles and encryption of the message. In addition, we also study the joint impact of jamming and eavesdropping attacks in IoV for different speed limits, transmission ranges and wireless bandwidths. We investigate the extra cost in terms of transmit power and bandwidth incurred by jamming and eavesdropping attacks while maintaining the same secrecy rate as it could have been without those attacks. Numerical results are used to support the analysis.

A reputation assessment model for trustful service recommendation

Nowadays, software systems are mainly Web front-based, Cloud-deployed and accessible by a wide audience over the Internet. These online systems commonly rely on Service-oriented Architecture principles, where they are built as orchestrations of RESTful (and in some rare cases as SOAP-based) services. Integrating new services in an existing orchestration is a challenging and risky task because trustworthiness of these services is not guaranteed throughout their lifetime. Reputation of services is a good indicator about the overall quality of services, because it reflects consumer satisfaction regarding the service-offered functionality and quality. Thus, reputation of services could be considered in the selection and recommendation of trustworthy services. In this paper, we present a framework for the management of web service reputation to conduct a better service recommendation. We present a reputation assessment model that aggregates fair user feedback ratings. The model includes a mechanism that prevents the introduction of malicious feedback ratings, by penalizing detected specious users. In addition, this framework includes a bootstrapping technique for estimating reputation of newcomer services based on neighbor similarity and initial advertised QoS. A set of experiments has been conducted to evaluate the effectiveness of the proposed framework. The results of these experiments highlighted the potential of our framework. These are presented at the end of the paper.

A new fuzzy-based method for energy-aware resource allocation in vehicular cloud computing using a nature-inspired algorithm

Vehicular cloud computing is a hopeful solution to utilize underused vehicle resources such as processing energy, storage space, Internet connection, etc. These resources can be shared among vehicles or rented by landlords for multiple purposes, such as meeting the hardware needs of automotive network services and applications. It is possible to meet the growing need for resources in the automotive network. Although this plan seems possible, its implementation has some problems. Several scholars have concentrated on architectural design to solve various difficulties and provide users with trustworthy service. This paper presents a fuzzy-based method to allocate resources in vehicular cloud computing using a nature-inspired (cuckoo search algorithm). The suggested algorithm is compared to some state-of-the-art algorithms. The outcomes illustrated that the recommended method outperforms other algorithms in terms of execution time, delay, and makespan.

SaaS Service Combinatorial Trustworthiness Measurement Method Based on Markov Theory and Cosine Similarity

With the rapid progress of information technology, cloud computing and cloud services are widely accepted and applied to all aspects of social life. In the cloud computing environment, SaaS (Software-as-a-Service) services have become the main form of software services. For SaaS services, evolutionary and iterative development methods have become the main methods of software system construction. For systems with high trustworthiness, the independent trustworthiness of each SaaS service has a great impact on the overall status. However, SaaS services with high independent trustworthiness do not always build highly trusted software systems. The combinatorial trustworthiness between SaaS services is as important as the independent trustworthiness of each SaaS service. This paper takes combinatorial trustworthiness between SaaS services as the research object. Combinatorial trustworthiness measurement method based on Markov and cosine similarity theory is proposed. The feasibility and effectiveness of the proposed method are verified through simulation experiments. Applicable scenarios, advantages, and disadvantages of the proposed method are shown through the comparison of different measurement methods. The proposed method provides theoretical and technical support for users to select SaaS services suitable for their application scenarios, build cloud service systems, and monitor the operation status of cloud service systems.

Enhancing the Privacy of Network Services through Trusted Computing

The addressing and discovering service is a vital infrastructure of the Internet. New applications and scenarios in next-generation networks rely on the secure and stable operation of domain name services, which puts forward new security challenges for the original domain name mechanism. While previous security enhancements of network services struggled to strike a balance between security, performance, and compatibility, hindering further use of core network services, the TEE (Trusted Computing Environment) technology can provide trusted and confidential services in untrusted network environments by verifiable hardware signatures. In this paper, we present a novel trustworthy service architecture with the preservation of security and privacy for addressing messages. The scheme provides a secure enclave to generate authenticatable responses between clients and targets, thus ensuring the privacy of services. We further build a new TEE compilation model to ensure that the built resolver application can provide trusted and secure services within TEE while keeping the availability without the TEE hardware. Experimental results show that our approach can enhance the privacy and security of addressing services such as DNS (Domain Name System) without sacrificing the quality of service and breaking the infrastructures of existing services.

Trusted Cloud Service System Based on Block Chain Technology

With the development and popularization of cloud computing technology, more and more users choose cloud services to build their application systems. With the improvement of users’ understanding of software systems, in addition to functionality, trustworthiness has become another key issue concerned by users. Based on the existing research on cloud service trustworthiness measurement and evaluation, this paper proposes a cloud service-trusted delivery model based on asymmetric encryption and hash function and a trusted runtime model of cloud service system based on block chain technology. The proposed models will effectively solve the untrusted problems such as denial and tampering in the process of cloud service acquisition, as well as the system anomaly at runtime. Finally, through targeted experiments to verify the effectiveness and feasibility of the proposed models, and through experimental analysis, this paper expounds on the principle and mechanism of model operation and trustworthiness guarantee.

ANALYSIS OF MARKETING STRATEGIES IN INCREASING THE NUMBER OF CUSTOMERS IN PERUMDA BPR BANK GRESIK

The objective of this research is to determine the application of marketing strategies in increasing the number of customers at PERUMDA BPR Bank Gresik. A qualitative descriptive method was implemented in this research, which is intended to collect facts and elaborate in a detailed and thorough manner according to the problem to be solved. SWOT analysis (Strengths, Weaknesses, Opportunities, dan Threats) was also employed in this research to find out the strategy conducted by PERUMDA BPR Bank Gresik in increasing the number of customers. The results show that company situation is in Quadrant I (+,+), Progressivity, PERUMDA BPR Bank Gresik carried out economic and trustworthy services to implement the company vision and mission. This position indicates that the company is in a strong position and is already on track. In the future, company still needs to make efforts to maintain this position.

IMPLEMENTASI PROGRAM PELAYANAN IZIN DI TEMPAT DENGAN HANGAT, AMANAH, TRANSPARAN DAN INOVATIF (PELITA HATI) DALAM PEMBUATAN SURAT IZIN USAHA DI KABUPATEN PROBOLINGGO

Currently, services in the licensing administration sector are the types of services that are quite in demand such as Building Construction Permits, Transportation Uzaha Permits, Fisheries Business Permits, Plantation Business Permits, Industrial Business Permits, more specifically regarding Trading Business Permits. Through the Investment Coordinating Board (BKPM) the Probolinggo Regency created an innovative on-site permit service program, namely PELITA HATI which aims to assist the community in making business licenses. This study aims to describe the Implementation of a Warm, Trustworthy, Transparent and Innovative Service Permit Service Program (Pelita Hati) in Making Business Licenses in Probolinggo Regency. The research method used is descriptive qualitative. The selection of informants was chosen deliberately who was considered to understand the problem, took data from relevant sources according to the theme raised, so as to produce reliable data and determine the accuracy of the research results. The results showed that the implementation of the Pelita Hati program in making business licenses in Probolinggo Regency was running well and optimally.

Security Requirements for Electronic Health Record (EHR) Sharing in Public Clouds

Hospital health care supplier is also moving from paper records to electronic health records (EHRs) or may be mistreatment EHRs already. EHRs permit suppliers to use info additional effectively to boost the standard and potency of your care, however EHRs won't amendment the privacy protections or security safeguards that apply to your health information. Our project focuses on developing secure cloud framework for evolving and accessing trustworthy computing services all told levels of public cloud readying model. Thus, eliminates each internal and external security threats. These leads to achieving knowledge confidentiality, data integrity, authentication and authorization, eliminating both active and passive attacks from cloud network environment. To develop a secure cloud framework for accessing trustworthy computing and storage services all told levels of public cloud readying model.

Toward a Trust Aware Network Slice-Based Service Provision in Virtualized Infrastructures

Future communication networks such as 5G are expected to support end-to-end delivery of services for several vertical markets with diverging requirements. Network slicing is a key construct that is used to provide end to end logical virtual networks running on a common virtualised infrastructure, which are mutually isolated. Having different network slices operating over the same 5G infrastructure creates several challenges in security and trust. This paper addresses the fundamental issue of trust of a network slice. It presents a trust model and property-based trust attestation mechanisms, which can be used to evaluate the trust of the virtual network functions that compose the network slice. The proposed model helps to determine the trust of the virtual network functions, as well as the properties that should be satisfied by the virtual platforms (both at boot and run time), on which these network functions are deployed for them to be trusted. We present a logic-based language that defines simple rules for the specification of properties and the conditions under which these properties need to be satisfied for trusted virtualized platforms. The proposed trust model and mechanisms enable the service providers to determine the trustworthiness of the network services as well as the users to develop trustworthy applications. We have developed a trust management architecture that enables the service providers to determine the trustworthiness of the network slices providing the network services. We have implemented a prototype of the trust management architecture using the Open Source MANO Platform and presented the performance results. The results show that our trust mechanisms cause only a slight reduction in the performance of network slices over virtualized infrastructure. We have also discussed how the proposed architecture can be used to detect and mitigate the impact of malicious virtual network functions in a dynamic manner.

DT-SSIM: A Decentralized Trustworthy Self-Sovereign Identity Management Framework

In a ubiquitous environment enclosing cooperative Internet-of-Things (IoT) devices, individuals, and entities, digital identity management (DIM) becomes critical and challenging. DIM pertains to device identities authentication and verification to enable trustworthy service exchange, data collection, and decision making. DIM is the supporting pillar for all online services and the foundation for security and authentication mechanisms. Due to the extreme heterogeneity, scale, and configuration complexity of such environments, enabling trustworthy DIM is crucial and seriously challenging. In an IoT context, devices use local digital identities stored within a tamper-proof unit and verified by a centralized authority for authentication. The recent attacks on IoT systems showed how vulnerable such a design is. It is also an inherent problem that influences humans. From that, self-sovereign identity (SSI) has emerged as a decentralized DIM approach embracing the concept of portable self-possession identity. SSI was presented to couple the digital identity from the owner to enable large-scale cooperation. However, digital identity storage and verification still occur on the device and in a centralized manner. Utilizing a local single-point-of-failure storage memory for verifiable credentials is one of the considerable drawbacks in contemporary SSI. In this regard, this article introduces decentralized trustworthy-self-sovereign identity management (DT-SSIM), a novel decentralized trustworthy SSI management framework. DT-SSIM integrates the secret share scheme with the blockchain-based smart contracts technologies to provide transparent and trustworthy SSI-based DIM services for IoT. Storing IoT identity credentials outside the devices’ local storage preserves the identity credentials from being tampered with or misused. Evaluations and discussions show the resiliency assessment of the system and the cost and estimated running times for verification processes in DT-SSIM.

A Fuzzy-Multi Attribute Decision Making approach for efficient service selection in cloud environments

In general, objective and subjective QoS assessment data forms the major data source for service evaluations. Especially, in the most dynamic service-oriented computing ecosystem like cloud environments, such assessment data is subjected to high uncertainty due to the dynamics in the number of cloud services and related QoS values. In such cases, the accuracy and reliability of the most efficient cloud service selection model remain questionable. Further, the complex interdependencies among the multiple QoS parameters and the trustworthiness of the cloud services complicate the process of handling uncertainty during cloud service selection. This work presents Fuzzy-Multi Attribute Decision Making (FMADM), a hybrid trust prediction model to provide accurate trust-based cloud service evaluations while efficiently handling the uncertainty in the cloud service assessment data. FMADM employs (i) Picture Fuzzy Sets (PFSs): to capture inconsistency, uncertainty, and ambiguity in the QoS data, (ii) Naïve Bayes: to recompute the weights of the QoS attributes, (iii) Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS): to model the non-linear relationship between the QoS values of cloud services and their corresponding trust result, and (iv) Random Forest Classifier (RFC): to predict the trust value of cloud services. The performance of FMADM was evaluated using Quality Web Service (QWS) v1.0 dataset under different scenarios using various quality metrics.

UAV-Based Privacy-Preserved Trustworthy Seamless Service Agility for NextG Cellular Networks

Next Generation cellular networks are expected to offer better service quality, secure and reliable service provisioning, and more cooperative operation even in unexpected stressful situations. Service provider cooperation can facilitate reliable service provisioning and extended coverage in disasters situations or partial network failures. However, the current 4G and 5G standards do not offer security and privacy-friendly support for inter-operator agility and service mobility, a key enabler for such cooperation. The situation becomes more critical in presence of attackers, where establishing trust relationships becomes very complicated. This paper presents a novel UAV-assisted user-agility support framework that enables trustworthy seamless service migration in a zero-trust environment. The proposed framework facilitates temporal authentication-authority delegation and proxying to enable preservice, all-party mutual authentication. The framework is implemented and tested on top of the srsRAN open-source 4G/5G software stack. Experiments showed that the presented framework managed to facilitate effective and efficient trustworthy service migration between heterogeneous service provider networks.

Effectiveness Evaluation of Different IDSs Using Integrated Fuzzy MCDM Model

Cyber-attacks are becoming progressively complicated; hence, the functional issues of intrusion-detection systems (IDSs) present ever-growing challenges. Failing to detect intrusions may jeopardize the trustworthiness of security services, such as privacy preservation, authenticity, and accessibility. To fight these risks, different organizations nowadays use a variety of approaches, techniques, and technologies to safeguard the systems’ credibility. Establishing policies and procedures, raising user awareness, implementing firewall and verification systems, controlling system access, and building computer-issue management groups are all examples of safeguarding methods. There is a lack of sufficient emphasis on the effectiveness of intrusion-detection systems. In enterprises, IDS is used to analyze the potentially dangerous activities taking place within the technological settings. The selection of efficient IDS is a challenging task for organizations. This research evaluates the impact of five popular IDSs for their efficiency and effectiveness in information security. The authors used the fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS)-based integrated multi-criteria decision-making (MCDM) methodology to evaluate the efficacy of the popular IDSs. The findings of this research suggest that most of the IDSs appear to be highly potential tools. Even though Snort is extensively deployed, Suricata has a substantial advantage over Snort. Suricata uses multi-threading functionality in comparison to Snort to boost the processing performance.

SC-TRUST: A Dynamic Model for Trustworthy Service Composition in the Internet of Things

A future Internet of Things (IoT) will feature a service-oriented architecture consisting of lightweight computing platforms offering individual, loosely coupled microservices. Often, an end-user will request a bespoke service that will require a composition of two or more microservices offered by different service providers. However, the underlying complexities of soft compositions and the increased security risks are inherent in such a massively decentralized and distributed architecture. The use of trust management to secure the IoT is well studied in the literature. However, there are limitations to its use in service compositions in the IoT. Specifically, transparent (agnostic) trust composition and decomposition remain key problems for this area. A novel model for trustworthy service compositions in the IoT, SC-TRUST, is therefore proposed to deal with these challenges. In this study, the trust properties of service compositions and the effect of service workflows on transparent trust composition and decomposition are investigated. Based on the findings, relevant trust evaluation functions are derived to guide the compositions. SC-TRUST was implemented in a suitable application and its performance, in terms of the utility derived and the trust accuracy, convergence, and resiliency, was evaluated. The results show that SC-TRUST improves the quality of service compositions and adequately mitigates trust-related attacks, thus increasing both efficiency and security.

Cloud service recommendation for small and medium-sized enterprises: A context-aware group decision making approach

Recently, the enormous advantages of cloud services make them increasingly appealing to the small and medium-sized enterprises. The growing number of available services makes it challenging to select trustworthy services. Existing approaches focus on user preferences to guide personalized services recommendation for individual users, but lack of the research on trustworthy service recommendation for the small and medium-sized enterprises that represents a group user consisting of multiple individual users. For this type of enterprise, the cloud services recommendation must address the challenges from the diverse client context of individual users, the imprecise quality of experience in an uncertain cloud environment and the invalid or unsatisfactory recommendations. A client context-aware approach is proposed to recommend trustworthy cloud services for the small and medium-sized enterprises based on non-compensatory multi-criteria decision-making. In it, a type of client context is viewed as an independent evaluation criterion, and the interval neutrosophic numbers are employed to measure the fuzzy trustworthiness of cloud services. Based on the investigated outranking relations of interval neutrosophic numbers, a non-compensatory multi-criteria decision-making procedure via an improved ELECTRE III method is developed to rank candidate services. Experimental results demonstrate that this approach could efficiently produces the accurate ranking results of cloud services and effectively recommend the trustworthy service for small and medium-sized enterprises.

Time Series Anomaly Detection for Trustworthy Services in Cloud Computing Systems

As a powerful architecture for large-scale computation, cloud computing has revolutionized the way that computing infrastructure is abstracted and utilized. Coupled with the challenges caused by Big Data, the rocketing development of cloud computing boosts the complexity of system management and maintenance, resulting in weakened trustworthiness of cloud services. To cope with this problem, a compelling method, i.e., Support Vector Data Description (SVDD), is investigated in this paper for detecting anomalous performance metrics of cloud services. Although competent in general anomaly detection, SVDD suffers from unsatisfactory false alarm rate and computational complexity in time series anomaly detection, which considerably hinders its practical applications. Therefore, this paper proposes a relaxed form of linear programming SVDD (RLPSVDD) and presents important insights into parameter selection for practical time series anomaly detection in order to monitor the operations of cloud services. Experiments on the Iris dataset and the Yahoo benchmark datasets validate the effectiveness of our approaches. Furthermore, the comparison of RLPSVDD and the methods obtained from Twitter, Numenta, Etsy and Yahoo, shows the overall preference for RLPSVDD in time series anomaly detection.

BFT in Blockchains: From Protocols to Use Cases

A blockchain is a distributed system that achieves strong security guarantees in storing, managing, and processing data. All blockchains achieve a common goal: building a decentralized system that provides a trustworthy service in an untrustworthy environment. A blockchain builds a Byzantine fault-tolerant (BFT) system in which decentralized nodes run a protocol to reach an agreement on the common system state. In this article, we focus on the research of BFT protocols. In particular, we categorize BFT protocols according to both the system models and workflow. We seek to answer these important questions: How has the research in BFT evolved in the past four decades, especially with the rise of blockchains? What are the driven needs for BFT research in the future?

The Assessment of Cloud Service Trustworthiness State Based on D-S Theory and Markov Chain

The massive cloud service market is full of various services with uneven quality. Even the services that have passed the platform detection will have unknown trustworthiness problems in the actual use process. The risk environment of the cloud service determines that its trustworthiness is random. The static trustworthiness assessment results can only reflect the cloud service trustworthiness at a certain time, not enough to reflect the real trustworthiness of the cloud service. To objectively reflect the trustworthiness of the cloud service, it is necessary to further assess the cloud service trustworthiness state and its changes on the basis of trustworthiness level measurement. To solve this problem, this paper combs the trustworthiness indicators of the cloud service, puts forward an effective assessment method of cloud service trustworthiness level based on D-S theory, and puts forward the representation method of cloud service trustworthiness state and its transition state combined with Markov chain, so as to realize the effective assess of cloud service trustworthiness state and its changes. Finally, through case analysis, it shows that the method proposed in this paper is feasible, can effectively assess the cloud service trustworthiness state and its changes, and provide users with detailed assessment results, so as to help users make reasonable service selection and trustworthiness management. This research has important research significance for ensuring the trustworthiness of the cloud service and improving the security of cloud service market.