Giuliana Carullo

A triadic closure and homophily-based recommendation system for online social networks

Recommendation systems are popular both commercially and in the research community. For example, Online in Social Networks (OSNs) like Twitter, they are gaining an increasing attention since a lot of connection are established between users without any previous knowledge. This highlights one of the key features of a lot of OSNs: the creation of relationships between users. Therefore, it is important to find new ways to provide interesting friendships suggestions. However, mining and analyzing data from large scale Social Networks can become critical in terms of computational resources. This is particularly true in the context of ubiquitous access, where resource-constrained mobile devices are used to access the social network services. To this end, designing architectures/solutions offering the possibility of operating in a Mobile Cloud scenario is of key importance. Accordingly, we present a new recommendation system scheme that tries to find the right trade-offs between the exploitation of the already existing links/relationships and the interest affinities between users. In particular, such scheme is based on an inherently parallel Hubs And Authorities algorithm together with similarity measures that, for scalability purposes, can be easily transposed in a cloud scenario. The first one let us leverage triadic closures while the second one takes into account homophily. The proposal is supported by an extensive performance analysis on publicly available Twitter data. In particular, we proved the effectiveness of the proposed recommendation system by using several performance metrics available in the literature which include precision, recall, F-measure and G-measure. The results show encouraging perspectives in terms of both effectiveness and scalability, that are driving our future research efforts.

Friendship Recommendations in Online Social Networks

Recommendation systems are popular both commercially and in the research community. For example, Online Social Networks (OSNs), like Twitter, are of special attention since a lot of connection are established between users without any previous knowledge. This highlights one of the key features of a lot of OSNs: the creation of relationships between users. Therefore, it is important to find new ways to provide interesting friendships suggestions.This work is the first step of an in-depth study whose goal is to find the right trade-offs between the number of factors explored in current state-of-the-art research. In particular, our contribution is an approach based on both Hubs And Authorities algorithm and similarity measures. The first one let us leverage triadic closures while the second one takes into account homophily. Even if the interplay between similarity and social ties is still an open issue in the analysis of OSNs, we lean towards the idea that it really counts.In order to support this hypothesis, a preliminary evaluation is performed on an implementation of the presented algorithm on datasets from Twitter. The deriving results show promising perspectives in terms of both effectiveness and scalability. These encouraging results are driving our future research efforts.

Service-oriented mobile malware detection system based on mining strategies

The large number of mobile internet users has highlighted the importance of privacy protection. Traditional malware detection systems that run within mobile devices have numerous disadvantages, such as overconsumption of processing resources, delayed updating, and difficulty in intersection. This study proposed a novel detection system based on cloud computing and packet analysis. The system detects the malicious behavior of the mobile malwares through their packets with the use of data mining methods. This approach completely avoids the defects of traditional methods. The system is service-oriented and can be deployed by mobile operators to send alarms to users who have malwares on their devices. To improve system performance, a new clustering strategy called contraction clustering was created. This strategy uses prior knowledge to reduce dataset size. Moreover, a multi-module detection scheme was introduced to enhance system accuracy. The results of this scheme are produced by integrating the detection results of several algorithms, including Naive Bayes and Decision Tree.

A unifying operating platform for 5G end-to-end and multi-layer orchestration

Heterogeneity of current software solutions for 5G is heading for complex and costly situations, with high fragmentation, which in turn creates uncertainty and the risk of delaying 5G innovations. This context motivated the definition of a novel Operating Platform for 5G (5G-OP), a unifying reference functional framework supporting end-to-end and multi-layer orchestration. 5G-OP aims at integrated management, control and orchestration of computing, storage, memory, networking core and edge resources up to the end-user devices and terminals (e.g., robots and smart vehicles). 5G-OP is an overarching architecture, with agnostic interfaces and well-defined abstractions, offering the seamless integration of current and future infrastructure control and orchestration solutions (e.g., OpenDaylight, ONOS, OpenStack, Apache Mesos, OpenSource MANO, Docker, LXC, etc.) The paper provides also the description of a prototype that can be seen as a simplified version of a 5G-OP, whose feasibility has been demonstrated in Focus Group IMT2020 of ITU-T.

Towards Improving Usability of Authentication Systems Using Smartphones for Logical and Physical Resource Access in a Single Sign-On Environment

The design of authentication methods raises crucial questions on how to solve conflicts between security and usability goals, that are at opposite ends of a “see-saw”. As a matter of fact, the usability of security systems has become a major issue in research on the efficiency and user acceptance of security systems. An authentication is more strong as more tokens are involved in authentication process. The main disadvantage is that users need to purchase and keep with them several tokens and cards. To address the above issues, we propose a two factors authentication scheme that allows users to employ their smartphones as unique authentication token providing access to both online and physical resources in a user-friendly and secure manner.

Software defined storage: Availability modeling and sensitivity analysis

Software Defined Storage (SDS) systems are crucial elements in cloud environments, where huge amount of data managed by content and network providers (multimedia content, social data, gaming data etc.) are typically strongly unstructured. Such data, referred to as objects, are handled along with their metadata allowing a web-based addressing as in the REST paradigm. According to the Software Defined concepts, SDS systems rely on decoupling the software plane (namely the set of management services), from the hardware plane (typically common, inexpensive and vendor unlocked hardware). SWIFT (a part of the OpenStack cloud project) represents a valuable example of an SDS system which, in the present work, we intend to characterize in terms of availability. Through such a characterization the minimum cost configuration can be selected, guaranteeing the so-called “five nines” availability requirement. The availability analysis is here performed by modeling the highlevel architecture of SWIFT as a Stochastic Reward Net (SRN) model. Furthermore, a sensitivity analysis is performed to assess the system robustness with respect to variations of some model parameters.

Object Storage in Cloud Computing Environments: An Availability Analysis

Object Storage Systems (OSSs) have been conceived to manage a bulk of highly unstructured data (videos, images, social resources etc.) by storing them in the form of objects accessible via REST APIs. An interesting implementation of OSS is based on Swift, a component of OpenStack, the most important platform exploited to deploy the Infrastructure as a Service (IaaS) paradigm. The present work is aimed at characterizing a Swift-based OSS from the availability point of view, namely at finding out the best configuration able to guarantee the so-called “five nines” availability requirement allowing a maximum system downtime of a little more than five minutes per year. The availability analysis is faced by exploiting the Stochastic Reward Nets (SRNs) formalism, accounting for the probabilistic behavior of the underlying structure of the Object Storage System. More specifically, the OSS availability has been assessed by performing a steady-state analysis whereas a sensitivity analysis has been carried out to evaluate the robustness of the overall system with respect to variations of some key parameters.

A Unifying Orchestration Operating Platform for 5G

5G will revolutionize the way ICT and Telecommunications infrastructures work. Indeed, businesses can greatly benefit from innovation introduced by 5G and exploit the new deep integration between ICT and networking capabilities to generate new value-added services. Although a plethora of solutions for virtual resources and infrastructures management and orchestration already exists (e.g., OpenDaylight, ONOS, OpenStack, Apache Mesos, Open Source MANO, Docker Swarm, LXD/LXC, etc.), they are still not properly integrated to match the 5G requirements. In this paper, we present the 5G Operating Platform (5G-OP) which has been conceived to fill in this gap and integrate management, control and orchestration of computing, storage and networking resources down to the end-user devices and terminals (e.g., smart phone, machines, robots, drones, autonomous vehicles, etc.). The 5G-OP is an overarching framework capable to provide agnostic interfaces and a universal set of abstractions in order to implement seamless 5G infrastructure control and orchestration. The functional structure of the 5G-OP, including the horizontal and vertical interworking of functions in it, has been designed to allow Network Operators and Service Providers to exploit diverse roles and business strategies. Moreover, the functional decoupling of the 5G-OP from the underneath management, control and orchestration solutions allows pursuing faster innovation cycles, being ready for the emergence of new service models.

Service function chaining deployed in an NFV environment: An availability modeling

Nowadays, network and telecommunication operators require flexible and dynamic models to deploy new services in a fast, reliable and cost saving way. The Service Function Chaining (SFC) design is particularly suited to meet such needs, especially in conjunction with the Network Function Virtualization (NFV) paradigm that adds a noteworthy elasticity during the SFC deployment phase. Accordingly, SFC is realized by means of a composition of Virtualized Network Functions (VNFs) aimed at providing some specific services. We consider, from an availability point of view, an SFC-based architecture with an aim to find out the optimal configuration guaranteeing the so-called “five nines” availability requirement, as demanded in the telecommunication systems. The availability analysis is carried out by exploiting a hierarchical model where a Reliability Block Diagram describes high level dependencies in the SFC implementation, while Stochastic Reward Nets are adopted to model the probabilistic behavior of single blocks. In particular, the SFC availability has been evaluated by performing a steady-state analysis, while a sensitivity analysis of some critical parameters allowed us to analyze in depth the whole system robustness.