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Analytics Solution

The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform

Giuseppe Santucci – 1st expert on this subject based on the ideXlab platform

  • Toward Multidimensional Geographical Performance Analysis for Telecommunications Network
    2019 23rd International Conference Information Visualisation (IV), 2019
    Co-Authors: Marco Angelini, Giorgio Cazzetta, Marina Geymonat, Mario Mirabelli, Giuseppe Santucci

    Abstract:

    Management and maintenance of mobile networks is a challenging activity: key point indicators related to different dimensions need to be evaluated in order to make business decisions and/or to manage problems arising from the network and the relative impact on business. This paper presents a visual Analytics Solution able to geo-reference up to three key point indicators, aiming at supporting operators in charge of analyzing the mobile network, detecting possible mobile network failures and managing resulting business oriented decisions. The proposed system has been developed collaboratively by University of Rome “La Sapienza” and TIM.

  • mad a visual Analytics Solution for multi step cyber attacks detection
    Journal of Computer Languages, 2019
    Co-Authors: Marco Angelini, Giuseppe Santucci, Simone Lenti, Silvia Bonomi, S Taggi

    Abstract:

    Abstract Software vulnerabilities represent one of the main weaknesses of an Information Technology (IT) system w.r.t. cyber attacks and nowadays consolidated official data, like the Common Vulnerability Exposure (CVE) dictionary, provide precise and reliable details about them. This information, together with the identification of priority systems to defend allows for inspecting the network structure and the most probable paths an attacker is likely to follow to reach sensible resources, with the main goal of identify suitable mitigation actions that reduce the risk of an attack. Some of these mitigation actions can be applied without further delay, some of them, instead, imply a high operational impact on the organization business that makes their usage convenient only when an attack is really on the way. Dealing with this issue is particularly challenging in the context of critical infrastructure where, even if patches are available, organization mission constraints create obstacles to their straightforward application. In this scenario, security operators are forced to deal with known vulnerabilities that cannot be patched and they spend a noticeable effort in proactive analysis, devising countermeasures that can mitigate the effect of a possible attack. This paper presents a Multi-step cyber Attack Detection (MAD) Visual Analytics Solution aiming at assisting security operators in improving their network security by analyzing the possible attacks and identifying suitable mitigations. Moreover, during an attack, the system visually presents the security operator with the relevant pieces of information allowing a better comprehension of the attack status and its probable evolution, in order to make decisions on the possible countermeasures.

  • Vulnus: Visual Vulnerability Analysis for Network Security
    IEEE Transactions on Visualization and Computer Graphics, 2019
    Co-Authors: Marco Angelini, Simone Lenti, Graziano Blasilli, Tiziana Catarci, Giuseppe Santucci

    Abstract:

    Vulnerabilities represent one of the main weaknesses of IT systems and the availability of consolidated official data, like CVE (Common Vulnerabilities and Exposures), allows for using them to compute the paths an attacker is likely to follow. However, even if patches are available, business constraints or lack of resources create obstacles to their straightforward application. As a consequence, the security manager of a network needs to deal with a large number of vulnerabilities, making decisions on how to cope with them. This paper presents VULNUS (VULNerabilities visUal aSsessment), a visual Analytics Solution for dynamically inspecting the vulnerabilities spread on networks, allowing for a quick understanding of the network status and visually classifying nodes according to their vulnerabilities. Moreover, VULNUS computes the approximated optimal sequence of patches able to eliminate all the attack paths and allows for exploring sub-optimal patching strategies, simulating the effect of removing one or more vulnerabilities. VULNUS has been evaluated by domain experts using a lab-test experiment, investigating the effectiveness and efficiency of the proposed Solution.

Xavier Sevillano – 2nd expert on this subject based on the ideXlab platform

  • quickspot a video Analytics Solution for on street vacant parking spot detection
    Multimedia Tools and Applications, 2016
    Co-Authors: E. Marmol, Xavier Sevillano

    Abstract:

    Vehicles searching for a vacant parking spot on the street can amount to as much as 40 % of the traffic in certain city areas, thus largely affecting mobility in urban environments. For this reason, it would be desirable to create integrated smart traffic management systems capable of providing real-time information to drivers about the location of available vacant parking spots. A scalable Solution would consist in exploiting the existing and widely-deployed video surveillance camera networks, which requires the development of computer vision algorithms for detecting vacant parking spots. Following this idea, this work introduces QuickSpot, a car-driven video Analytics Solution for on-street vacant parking spot detection designed as a motion detection, object tracking and visual recognition pipeline. One of the main features of QuickSpot is its simplified setup, as it can be trained on external databases to learn the appearances of the objects it is capable of recognizing (pedestrians and vehicles). To test its performance under different daytime lighting conditions, we have recorded, edited, annotated and made available to the research community the QuickSpotDB video database for the vacant parking spot detection problem. In the conducted experiments, we have evaluated the trade-off between the accuracy and the computational complexity of QuickSpot with an eye to its practical applicability. The results show that QuickSpot detects parking spot status with an average accuracy close to 99 % at a 1-second rate regardless of the illumination conditions, outperforming in an indirect comparison the other car-driven approaches reported in the literature.

  • QuickSpot: a video Analytics Solution for on-street vacant parking spot detection
    Multimedia Tools and Applications, 2016
    Co-Authors: E. Marmol, Xavier Sevillano

    Abstract:

    Vehicles searching for a vacant parking spot on the street can amount to as much as 40 % of the traffic in certain city areas, thus largely affecting mobility in urban environ- ments. For this reason, it would be desirable to create integrated smart traffic management systems capable of providing real-time information to drivers about the location of avail- able vacant parking spots. A scalable Solution would consist in exploiting the existing and widely-deployed video surveillance camera networks, which requires the development of computer vision algorithms for detecting vacant parking spots. Following this idea, this work introduces QuickSpot, a car-driven video Analytics Solution for on-street vacant park- ing spot detection designed as a motion detection, object tracking and visual recognition pipeline. One of the main features of QuickSpot is its simplified setup, as it can be trained on external databases to learn the appearances of the objects it is capable of recognizing (pedestrians and vehicles). To test its performance under different daytime lighting condi- tions, we have recorded, edited, annotated and made available to the research community the QuickSpotDB video database for the vacant parking spot detection problem. In the conducted experiments, we have evaluated the trade-off between the accuracy and the com- putational complexity of QuickSpot with an eye to its practical applicability. The results show that QuickSpot detects parking spot status with an average accuracy close to 99 % at a 1-second rate regardless of the illumination conditions, outperforming in an indirect comparison

Marco Angelini – 3rd expert on this subject based on the ideXlab platform

  • Toward Multidimensional Geographical Performance Analysis for Telecommunications Network
    2019 23rd International Conference Information Visualisation (IV), 2019
    Co-Authors: Marco Angelini, Giorgio Cazzetta, Marina Geymonat, Mario Mirabelli, Giuseppe Santucci

    Abstract:

    Management and maintenance of mobile networks is a challenging activity: key point indicators related to different dimensions need to be evaluated in order to make business decisions and/or to manage problems arising from the network and the relative impact on business. This paper presents a visual Analytics Solution able to geo-reference up to three key point indicators, aiming at supporting operators in charge of analyzing the mobile network, detecting possible mobile network failures and managing resulting business oriented decisions. The proposed system has been developed collaboratively by University of Rome “La Sapienza” and TIM.

  • mad a visual Analytics Solution for multi step cyber attacks detection
    Journal of Computer Languages, 2019
    Co-Authors: Marco Angelini, Giuseppe Santucci, Simone Lenti, Silvia Bonomi, S Taggi

    Abstract:

    Abstract Software vulnerabilities represent one of the main weaknesses of an Information Technology (IT) system w.r.t. cyber attacks and nowadays consolidated official data, like the Common Vulnerability Exposure (CVE) dictionary, provide precise and reliable details about them. This information, together with the identification of priority systems to defend allows for inspecting the network structure and the most probable paths an attacker is likely to follow to reach sensible resources, with the main goal of identify suitable mitigation actions that reduce the risk of an attack. Some of these mitigation actions can be applied without further delay, some of them, instead, imply a high operational impact on the organization business that makes their usage convenient only when an attack is really on the way. Dealing with this issue is particularly challenging in the context of critical infrastructure where, even if patches are available, organization mission constraints create obstacles to their straightforward application. In this scenario, security operators are forced to deal with known vulnerabilities that cannot be patched and they spend a noticeable effort in proactive analysis, devising countermeasures that can mitigate the effect of a possible attack. This paper presents a Multi-step cyber Attack Detection (MAD) Visual Analytics Solution aiming at assisting security operators in improving their network security by analyzing the possible attacks and identifying suitable mitigations. Moreover, during an attack, the system visually presents the security operator with the relevant pieces of information allowing a better comprehension of the attack status and its probable evolution, in order to make decisions on the possible countermeasures.

  • Vulnus: Visual Vulnerability Analysis for Network Security
    IEEE Transactions on Visualization and Computer Graphics, 2019
    Co-Authors: Marco Angelini, Simone Lenti, Graziano Blasilli, Tiziana Catarci, Giuseppe Santucci

    Abstract:

    Vulnerabilities represent one of the main weaknesses of IT systems and the availability of consolidated official data, like CVE (Common Vulnerabilities and Exposures), allows for using them to compute the paths an attacker is likely to follow. However, even if patches are available, business constraints or lack of resources create obstacles to their straightforward application. As a consequence, the security manager of a network needs to deal with a large number of vulnerabilities, making decisions on how to cope with them. This paper presents VULNUS (VULNerabilities visUal aSsessment), a visual Analytics Solution for dynamically inspecting the vulnerabilities spread on networks, allowing for a quick understanding of the network status and visually classifying nodes according to their vulnerabilities. Moreover, VULNUS computes the approximated optimal sequence of patches able to eliminate all the attack paths and allows for exploring sub-optimal patching strategies, simulating the effect of removing one or more vulnerabilities. VULNUS has been evaluated by domain experts using a lab-test experiment, investigating the effectiveness and efficiency of the proposed Solution.