IRS II: a framework and infrastructure for semantic web services

In this paper we describe IRS–II (Internet Reasoning Service) a framework and implemented infrastructure, whose main goal is to support the publication, location, composition and execution of heterogeneous web services, augmented with semantic descriptions of their functionalities. IRS–II has three main classes of features which distinguish it from other work on semantic web services. Firstly, it supports one-click publishing of standalone software: IRS–II automatically creates the appropriate wrappers, given pointers to the standalone code. Secondly, it explicitly distinguishes between tasks (what to do) and methods (how to achieve tasks) and as a result supports capability-driven service invocation; flexible mappings between services and problem specifications; and dynamic, knowledge-based service selection. Finally, IRS–II services are web service compatible – standard web services can be trivially published through the IRS–II and any IRS–II service automatically appears as a standard web service to other web service infrastructures. In the paper we illustrate the main functionalities of IRS–II through a scenario involving a distributed application in the healthcare domain

Know Your Enemy: Stealth Configuration-Information Gathering in SDN

Software Defined Networking (SDN) is a network architecture that aims at providing high flexibility through the separation of the network logic from the forwarding functions. The industry has already widely adopted SDN and researchers thoroughly analyzed its vulnerabilities, proposing solutions to improve its security. However, we believe important security aspects of SDN are still left uninvestigated. In this paper, we raise the concern of the possibility for an attacker to obtain knowledge about an SDN network. In particular, we introduce a novel attack, named Know Your Enemy (KYE), by means of which an attacker can gather vital information about the configuration of the network. This information ranges from the configuration of security tools, such as attack detection thresholds for network scanning, to general network policies like QoS and network virtualization. Additionally, we show that an attacker can perform a KYE attack in a stealthy fashion, i.e., without the risk of being detected. We underline that the vulnerability exploited by the KYE attack is proper of SDN and is not present in legacy networks. To address the KYE attack, we also propose an active defense countermeasure based on network flows obfuscation, which considerably increases the complexity for a successful attack. Our solution offers provable security guarantees that can be tailored to the needs of the specific network under consideratio

LineSwitch: Efficiently Managing Switch Flow in Software-Defined Networking while Effectively Tackling DoS Attacks

Software Defined Networking (SDN) is a new networking architecture which aims to provide better decoupling between network control (control plane) and data forwarding functionalities (data plane). This separation introduces several benefits, such as a directly programmable and (virtually) centralized network control. However, researchers showed that the required communication channel between the control and data plane of SDN creates a potential bottleneck in the system, introducing new vulnerabilities. Indeed, this behavior could be exploited to mount powerful attacks, such as the control plane saturation attack, that can severely hinder the performance of the whole network. In this paper we present LineSwitch, an efficient and effective solution against control plane saturation attack. LineSwitch combines SYN proxy techniques and probabilistic blacklisting of network traffic. We implemented LineSwitch as an extension of OpenFlow, the current reference implementation of SDN, and evaluate our solution considering different traffic scenarios (with and without attack). The results of our preliminary experiments confirm that, compared to the state-of-the-art, LineSwitch reduces the time overhead up to 30%, while ensuring the same level of protection.Comment: In Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security (ASIACCS 2015). To appea

An object based algebra for specifying a fault tolerant software architecture

AbstractIn this paper we present an algebra of actors extended with mechanisms to model crash failures and their detection. We show how this extended algebra of actors can be successfully used to specify distributed software architectures. The main components of a software architecture can be specified following an object-oriented style and then they can be composed using asynchronous message passing or more complex interaction patterns. This formal specification can be used to show that several requirements of a software system are satisfied at the architectural level despite failures. We illustrate this process by means of a case study: the specification of a software architecture for intelligent agents which supports a fault tolerant anonymous interaction protocol

COVID-19 Test Positivity Rate as a marker for hospital overload

The use of antigen tests for the diagnosis of COVID-19 in Italy has risen sharply in autumn 2020. Italian regions like Alto Adige, Veneto, Toscana, Lazio, Piemonte and Marche did a large use of these tests for screening and surveillance purposes or for implementing diagnosis protocols in addition to molecular tests. As a consequence of this situation the basic test positivity rate (TPR) definition (i.e. number of new positive cases divided by the number of molecular tests) used at the beginning of the outbreak has lost in accuracy. In this paper, we emphasize the enormous potential of TPR index as a tool for monitoring the COVID-19 pandemic, and we show that the peaks of this index are related to the peaks of patients admitted in hospitals and intensive care units, which occurred on average from 16 and 12 days later approximately, considering all the Italian regions in the first phase of the pandemic. To conduct the study we have defined a novel version of the TPR index which takes into account the number of tests done with respect to the opulation, the number of infected individuals, and the number of patients healed, integrating it with antigen tests. Unfortunately, this index given the lack of data concerning antigen tests, so far cannot be computed for most Italian regions. However, using a limited set of data on antigen tests which were made available in November 2020, we have shown that the TPR forecasting properties are preserved in the second phase. Without any shadow of doubt, we argue that the defined TPR index could be successfully used as a forecasting tool to monitor the impact of COVID-19 in the healthcare system, and that antigen tests data should be standardized soon. We conclude the paper, defining an extended version of the TPR index to be used if more omplete data on antigen tests will be made available, also including vaccinate people

A Novel Stealthy Attack to Gather SDN Configuration-Information

Software Defined Networking (SDN) is a recent network architecture based on the separation of forwarding functions from network logic, and provides high flexibility in the management of the network. In this paper, we show how an attacker can exploit SDN programmability to obtain detailed knowledge about the network behaviour. In particular, we introduce a novel attack, named Know Your Enemy (KYE), which allows an attacker to gather vital information about the configuration of the network. Through the KYE attack, an attacker can obtain information ranging from the configuration of security tools, such as attack detection thresholds for network scanning, to general network policies like QoS and network virtualization. Additionally, we show that the KYE attack can be performed in a stealthy fashion, allowing an attacker to learn configuration secrets without being detected. We underline that the vulnerability exploited by the KYE attack is proper of SDN and is not present in legacy networks. Finally, we address the KYE attack by proposing an active defense countermeasure based on network flows obfuscation, which considerably increases the complexity for a successful attack. Our solution offers provable security guarantees that can be tailored to the needs of the specific network under consideration

Targeting the thyroid gland with thyroid-stimulating hormone (TSH)-nanoliposomes

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Clinical Study Integrated Approaches for the Management of Staple Line Leaks following Sleeve Gastrectomy

Introduction. Aim of the study was trying to draw a final flow chart for the management of gastric leaks after laparoscopic sleeve gastrectomy, based on the review of our cases over 10 years' experience. Material and Methods. We retrospectively reviewed all patients who underwent LSG as a primary operation at the Bariatric Unit of Tor Vergata University Hospital in Rome from 2007 to 2015. Results. Patients included in the study were 418. There were 6 staple line leaks (1.44%). All patients with diagnosis of a leak were initially discharged home in good clinical conditions and then returned to A&E because of the complication. The mean interval between surgery and readmission for leak was 13,4 days (range 6-34 days, SD ± 11.85). We recorded one death (16.67%) due to sepsis. The remaining five cases were successfully treated with a mean healing time of the gastric leak of 55,5 days (range 26-83 days; SD ± 25.44). Conclusion. Choosing the proper treatment depends on clinical stability and on the presence or not of collected abscess. Our treatment protocol showed being associated with low complication rate and minor discomfort to the patients, reducing the need for more invasive procedures

Multiphase Powerful Outflows Detected in High-z Quasars

We present results from a comprehensive study of ultrafast outflows (UFOs) detected in a sample of 14 quasars, 12 of which are gravitationally lensed, in a redshift range of 1.41-3.91, near the peak of the active galactic nucleus (AGN) and star formation activity. New XMM-Newton observations are presented for six of them, which were selected to be lensed and contain a narrow absorption line (NAL) in their UV spectra. Another lensed quasar was added to the sample, albeit already studied because it was not searched for UFOs. The remaining seven quasars of our sample are known to contain UFOs. The main goals of our study are to infer the outflow properties of high-z quasars, constrain their outflow induced feedback, study the relationship between the outflow properties and the properties of the ionizing source, and compare these results to those of nearby AGN. Our study adds six new detections (> 99% confidence) of UFOs at z > 1.4, almost doubling the current number of cases. Based on our survey of six quasars selected to contain a NAL and observed with XMM-Newton, the coexistence of intrinsic UV NALs and UFOs is found to be significant in >83% of these quasars suggesting a link between multiphase AGN feedback properties of the meso- and microscale. The kinematic luminosities of the UFOs of our high-z sample are large compared to their bolometric luminosities (median of L K/L Bol ⪆ 50%). This suggests they provide efficient feedback to influence the evolution of their host galaxies and that magnetic driving may be a significant contributor to their acceleration

Visualization and analysis of cellular & Twitter data using qgis

The study is to understand individual presence and movement in Friuli Venezia Giulia region. It is important for tourism planning, hazard management, business marketing, implementing government lifetime policies and benefit. The aim of this study is achieved by advanced web 2.0 applications. We need real time and geo-located data to monitor the inflow of tourist and to come up with effective promoting and benefiting plans for tourism, the evacuation and mitigation strategies during hazards to protect social life and environment with less infrastructure damage, marketing plans for advertising or selling of products. Despite wide spread success in predicting specific aspects of human behavior by social media information, a little attention is given to twitter and cell phone data. Accessibility to detailed human movements with fine spatial and temporal granularity is challenging due to confidentiality and safety reasons. With rapid development of web2.0 applications people can post about events, share opinion and emotions online. Using twitter data, how short term travelers, such as tourists, can be recognized and how their travel pattern can be analyzed. Study of finding tourist dynamics such as arriving and outgoing of tourist, sum of trips, sum of days and night spent, number of unique visitors, country of residence, main destination, secondary destination, transits pass through, repeat visits are achieved using CDR (call detail records) and DDR (data detail records)