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Publications (155)
The growing capacity to handle vast amounts of data, combined with a shift in service delivery models, has improved scalability and efficiency in data analytics, particularly in multi-tenant environments. Data are treated as digital products and processed through orchestrated service-based data pipelines. However, advancements in data analytics do...
Cloud computing has been a driving force for many technological innovations and transformations in various domains and industries. It offers scalable and cost-effective storage and processing capabilities suitable for handling large volumes of structured and unstructured data. Could computing has enabled organizations to leverage data-driven insigh...
Cloud-based service certification extends traditional certification schemes to address the peculiarities of dynamic distributed environments. It pursues three main objectives: (i) greater flexibility of the certification process (i.e., models for certification life cycle, target, and process), (ii) adaptability to service evolution and environmenta...
Modern distributed systems are increasingly based on composite nano-services deployed in complex dynamic environments (e.g., edge-cloud continuum). In this scenario new requirements emerge aiming to (i) increase the quality of the certificate considering multiple factors affecting the final non-functional property to be certified (Sect. 4.1), (ii)...
Since its early introduction in the Eighties, certification has been a primary way to document the verification of systems behavior. Certification schemes and corresponding processes have been defined for software systems, first, and the adapted to service-based and cloud-based systems. Finally their scope has included ML-based systems. Certificati...
Today, computer systems play a central role in all aspects of human life, including in the operation of highly-critical infrastructures, for instance, in the domains of healthcare, transportation, and telecommunication. However, in spite of this pervasive presence of computer systems in our daily activities, many users feel reluctant in trusting th...
Recent advances in artificial intelligence (AI) are radically changing how systems and applications are designed and developed. In this context, new requirements and regulations emerge, such as the AI Act, placing increasing focus on strict non-functional requirements, such as privacy and robustness, and how they are verified. Certification is cons...
Modern malware detection tools rely on special permissions to collect data that can reveal the presence of suspicious software within a machine. Typical data that they collect for this task are the set of system calls, the content of network traffic, file system changes, and API calls. However, giving access to these data to an externally created p...
The implementation of distributed applications is more frequently achieved through the configuration of service-oriented workflows, which are then deployed within the Edge-Cloud Continuum. This approach facilitates the support of distributed processing pipelines. In this context, there is an increasing demand for solutions that can continuously gua...
Existing certification schemes implement continuous verification techniques aiming to prove non-functional (e.g., security) properties of software systems over time. These schemes provide different re-certification techniques for managing the certificate life cycle, though their strong assumptions make them ineffective against modern service-based...
Machine Learning (ML) is increasingly used to implement advanced applications with non-deterministic behavior, which operate on the cloud-edge continuum. The pervasive adoption of ML is urgently calling for assurance solutions assessing applications non-functional properties (e.g., fairness, robustness, privacy) with the aim to improve their trustw...
Machine learning is becoming ubiquitous. From finance to medicine, machine learning models are boosting decision/making processes and even outperforming humans in some tasks. This huge progress in terms of prediction quality does not however find a counterpart in the security of such models and corresponding predictions, where perturbations of frac...
Machine Learning (ML) is increasingly used to drive the operation of complex distributed systems deployed on the cloud-edge continuum enabled by 5G. Correspondingly, distributed systems' behavior is becoming more non-deterministic in nature. This evolution of distributed systems requires the definition of new assurance approaches for the verificati...
Low-light image enhancement is a crucial yet challenging task in computer vision and multimedia applications. Retinex-based approaches have been continuously explored in this domain. However, the Retinex decomposition is an ill-posed problem, as the proper constraints of illumination and reflectance should be considered to regularize the solution s...
Modern (industrial) domains are based on large digital ecosystems where huge amounts of data and information need to be collected, shared, and analyzed by multiple actors working within and across organizational boundaries. This data-driven ecosystem poses strong requirements on data management and data analysis, as well as on data protection and s...
Crowd counting in congested scenarios is an essential yet challenging task in detecting abnormal crowd for contemporary urban planning. The counting accuracy has been significantly improved with the rapid development of deep learning over the last decades. However, current models are fragile in the real-world application mainly due to two inherent...
Machine learning is becoming ubiquitous. From financial to medicine, machine learning models are boosting decision-making processes and even outperforming humans in some tasks. This huge progress in terms of prediction quality does not however find a counterpart in the security of such models and corresponding predictions, where perturbations of fr...
Information-Centric Networking is an emerging alternative to host-centric networking designed for large-scale content distribution and stricter privacy requirements. Recent research on Information-Centric Networking focused on the protection of the network from attacks targeting the content delivery protocols, while assuming genuine content can alw...
Scalable and secure authorization of smart things is of the crucial essence for the successful deployment of the Internet of Things (IoT). Unauthorized access to smart things could exacerbate the security and privacy concern, which could, in turn, lead to the reduced adoption of the IoT, and ultimately to the emergence of severe threats. Even thoug...
This paper presents a counseling (ro)bot called Visual Counseling Agent (VICA) which focuses on remote mental healthcare. It is an agent system leveraging artificial intelligence (AI) to aid mentally distressed persons through speech conversation. The system terminals are connected to servers by the Internet exploiting Cloud-nativeness, so that any...
It is widely recognised that the process of public health policy making (i.e., the analysis, action plan design, execution, monitoring and evaluation of public health policies) should be evidenced based, and supported by data analytics and decision- making tools tailored to it. This is because the management of health conditions and their consequen...
The cloud computing has deeply changed how distributed systems are engineered, leading to the proliferation of ever/evolving and complex environments, where legacy systems, microservices, and nanoservices coexist. These services can severely impact on individuals' security and safety, introducing the need of solutions that properly assess and verif...
Due to limitation of optical lenses, obtaining all-in-focus images is difficult. However, lots of multi-focus image fusion methods cause undesirable artifacts around the focused and defocused boundaries in fusion images. Usually, these boundaries are at the edges of objects in images while the gradient information can reflect edge information intui...
Artificial intelligence (AI), combined with the Internet of Things (IoT), plays a beneficial role in various fields, including intelligent surveillance applications. With IoT and 5G advancement, intelligent sensors, and devices in the surveillance environment collect large amounts of data in the form of videos and images. These collected data requi...
Recently, a very deep convolutional neural network (CNN) has achieved impressive results in image super-resolution (SR). In particular, residual learning techniques are widely used. However, the previously proposed residual block can only extract one single-level semantic feature maps of one single receptive field. Therefore, it is necessary to sta...
Thermal infrared (IR) images are widely used in smart grids for numerous applications. These applications prefer high-resolution (HR) IR images since HR IR images benefit the performance. However, HR IR imaging devices are extremely expensive. To save the cost of upgrading imaging devices, an iterative error reconstruction network (IERN) is propose...
High-resolution (HR) medical images are preferred in clinical diagnoses and subsequent analysis. However, the acquisition of HR medical images is easily affected by hardware devices. As an effective and trusted alternative method, the super-resolution (SR) technology is introduced to improve the image resolution. Compared with traditional SR method...
In this paper we present a dataset of images to test the performance of image processing algorithms, in particular demosaicing and denoising methods. Despite the plethora of demosaicing and denoising algorithms present in the literature, only few benchmarks are available to test their performance, and most of them are quite old, thus inadequate to...
Abstract In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment...
Demosaicking aims to approximate missing color pixels through analysis of the geometric structure between given color pixels and missing color pixels. In this paper, we introduce an efficient adaptive demosaicking method based on back propagation (BP) neural network (BP-NN). We firstly reconstruct the green channel using one BPNN, and then refine t...
Wireless body area networks (WBANs) play an important role in human health monitoring for mobile healthcare. The improvement of service performance and low-power consumption are the two challenges for these medical WBANs, because those energy-limited wireless medical sensors must transmit the monitoring data to the personal server (PS) via intra-WB...
The advent of cloud computing has radically changed the concept of distributed environments, where services can now be composed and reused at high rates. Today, service composition in the cloud is driven by the need of providing stable QoS, where non-functional properties of composite services are proven over time and composite services continuousl...
The advent of the Internet of things (IoT) has radically changed the way in which computations and communications are carried out. People are just becoming another component of IoT environments, and in turn, IoT environments are becoming a mixture of platforms, software, services, things, and people. The price we pay for such dynamic and powerful e...
This paper proposes a new color interpolation method which can be used in embedded devices for IoT system. In this work, we use regression approach for generating and designing filters to restore color image. The filters are designed with four sizes, 5x5 training filter, 7x7 training filter, 9x9 training filter, and 11x11 training filter. The obtai...
In vehicular ad hoc networks (VANETs), one of the important challenges is the lack of precise mathematical modeling taking into account the passive vacation triggered by the zero-arrival state of nodes. Therefore, a polling-based access control is proposed in this paper using a sleeping schema to meet the challenge of quality of service (QoS) and e...
The widespread diffusion of ubiquitous and smart devices is radically changing the environment surrounding the users and brought to the definition of a new ecosystem called Internet of Things (IoT). Users are connected anywhere anytime, and can continuously monitor and interact with the external environment. While devices are becoming more and more...
The diffusion of service-based and cloud-based systems has created a scenario where software is often made available as services, offered as commodities over corporate networks or the global net. This scenario supports the definition of business processes as composite services, which are implemented via either static or runtime composition of offer...
This study presents a Bayesian approach based on a color image demosaicking algorithm. The proposed method is composed of pointwise and patchwise measurements. The estimation of the missing pixel is formulated as a maximum a posteriori and a minimum energy function. By utilizing Bayesian theory and some prior knowledge, the missing color informatio...
Smart cities make use of a variety of technologies, protocols, and devices to support and improve the quality of everyday activities of their inhabitants. An important aspect for the development of smart cities are innovative public policies, represented by requirements, actions, and plans aimed at reaching a specific goal for improving the society...
The Internet of Things (IoT) is increasingly becoming a worldwide network of interconnected things that are uniquely addressable, via standard communication protocols. The use of IoT for continuous monitoring of public health is being rapidly adopted by various countries while generating a massive volume of heterogeneous, multisource, dynamic, and...
Cloud computing proposes a paradigm shift where resources and services are allocated, provisioned, and accessed at runtime and on demand. New business opportunities emerge for service providers and their customers, at a price of an increased uncertainty on how their data are managed and their applications operate once stored/deployed in the cloud....
Aurora is a recurrent feature of the atmosphere, acting as a mirror of otherwise invisible coupling between different atmospheric layers. Advanced processing of auroral images has proven essential to investigate some key physical processes in near-Earth space; in particular, auroral images carry important information for research on power networks,...
This special issue on ‘Real-Time Image and Video Processing in Mobile Embedded Systems’ is intended to
present the current state-of-the-art in the field of mobile embedded systems applications using real-time image
and video processing. Contributions are solicited to this special issue by submitting original and unpublished
papers that illustrate r...
Traditional assurance solutions for software-based systems rely on static verification techniques and assume continuous availability of trusted third parties. With the advent of cloud computing, these solutions become ineffective since services/applications are flexible, dynamic, and change at run time, at high rates. Although several assurance app...
Despite its immense benefits in terms of flexibility, resource consumption, and simplified management, cloud computing raises several concerns due to lack of trust and transparency. Like all computing paradigms based on outsourcing, the use of cloud computing is largely a matter of trust. There is an increasing pressure by cloud customers for solut...
Abstract In this paper, we propose a lossless compression method to resolve the limitations in the real-time transmission of aurora spectral images. This method bi-dimensionally decorrelates the spatial and spectral domains and effectively removes side information of recursively computed coefficients to achieve high quality rapid compression. Exper...
Demosaicking is a digital image process to reconstruct full color digital images from incomplete color samples from an image sensor. It is an unavoidable process for many devices incorporating camera sensor (e.g. mobile phones, tablet, etc.). In this paper, we introduce a new demosaicking algorithm based on polynomial interpolation-based demosaicki...
The cloud computing paradigm provides an environment where services can be composed and reused at high rates. Existing composition techniques focus on providing the desired functionality and at a given deployment cost. In this paper, we focus on the definition of cloud service compositions driven by certified non-functional properties. We define a...
Lack of trust and transparency are among the main reasons hindering adoption of cloud computing. Users in fact can inspect neither their applications nor the treatment of their data, and have little or no guarantees about their security. In this context, there is a pressing need for assurance techniques supporting some key properties of cloud servi...
This paper presents an intra-field scanning format conversion method using two filters: bilinear filter (BF) and fuzzy-based weighted average filter (FWAF). The proposed method is intended for black and white images, luminance component of YIQ color space, or each color component of RGB color space. We start from the notion that pixels to be interp...
Image sensing is generally performed with multiple spectral sensors. For example, combination of three sensors (red, green, and blue) is used for color image reproduction, and electrooptical and infrared sensors are used for surveillance and satellite imaging, respectively. The resolution of each sensor can be intensified by taking the other sensor...
Cloud computing is introducing an architectural paradigm shift that involves a large part of the IT industry. The flexibility in allocating and releasing resources at runtime creates new business opportunities for service providers and their customers. However, despite its advantages, cloud computing is still not showing its full potential. Lack of...
The lack of control on personal data/processes and trust in their management by a third party is a well-known problem that limits the success of the cloud computing paradigm. Organizations and final users are increasingly reluctant to move their assets (i.e., services, business data, and personal information) to the cloud, and to participate in an...
Cloud users and service providers are increasingly concerned about the management of their data and the behavior of the applications they use/own once stored/deployed in the cloud. They therefore ask for enhanced assurance solutions, which partially mitigate the new risks and threats they are facing. Among existing solutions, certification has been...
We present a test-based assurance scheme aimed at incremental security certification. Our scheme assesses the impact of changes at cloud, system, and certification methodology levels on existing certification processes. The proposed solution minimizes the risk of unnecessary certificate revocation and reduces as much as possible the amount of re-ce...
This paper presents a new grassy effect generation approach. The grassy effect changes original image as the one behind the grass. A random number generation function is employed to decide the same of block and location of the pixel. Obtained various block size and pixel location yield unexpected grassy execution to the original image. The subjecti...
This paper proposes a new possible noise model and its application to Bayer color filter array (CFA). We studied effects of several noise models on three Bayer patterns. For instance, current Bayer CFA uses RGGB pattern which contains two green pixels, a red and a blue pixels in a pair. However, one may consider other color combinations such as RRG...
Autonomic cloud computing systems react to events and context changes, preserving a stable quality of service for their tenants. Existing assurance techniques supporting trust relations between parties need to be adapted to scenarios where the assumption of responsibility on trust assertions and related information (e.g., in SLAs and certificates)...
This chapter presents a certification-based assurance solution for the cloud, which has been developed as part of the FP7 EU Project CUMULUS. It provides an overview of the CUMULUS certification models, which are at the basis of the certification processes implemented and managed by the CUMULUS certification framework. Certification models drive th...
The cloud computing paradigm requires solutions supporting customers in the selection of services that satisfy their functional and non-functional requirements. These solutions must i) support the dynamic, multi-cloud nature of service provisioning, ii) manage scenarios where no total preference relation over service properties is available, and ii...
Privacy-aware processing of personal data on the web of services requires managing a number of issues arising both from the technical and the legal domain. Several approaches have been proposed to matching privacy requirements (on the clients side) and privacy guarantees (on the service provider side). Still, the assurance of effective data protect...
Accurate and lightweight evaluation of web service security properties is a key problem, especially when business processes are dynamically built by composing atomic services provided by different suppliers at runtime. In this paper, we tackle this problem by proposing a security certification approach that virtually certifies a composite service f...
The Service-Oriented Architecture (SOA) paradigm is giving rise to a new generation of applications built by dynamically composing loosely coupled autonomous services. Clients (i.e., software agents acting on behalf of human users or service providers) implementing such complex applications typically search and integrate services on the basis of th...
This paper proposes a new interpolation filter for deinterlacing, which is achieved by enhancing the edge preserving ability of the conventional edge-based line average methods. This filter consists of three steps: pre-processing step, fuzzy metric-based weight assignation step, and rank-ordered marginal filter step. The proposed method is able to...