Using SIP as P2P Technology

Nowadays peer-to-peer (p2p) technologies are widely adopted and used for building even more sophisticated services: from ubiquitous file-sharing systems to the even more popular Internet telephony. In addition, the Session Initiation Protocol (SIP) has been used for different purposes. Due to its intrinsic generality and flexibility, it could be adopted to build and manage also p2p applications. Moreover, the p2p philosophy could be applied to the existing SIP architecture, to cope with issues such as Denial of Service (DoS). In this paper, we survey the state of the art of the joint use of p2p and SIP. Some hints and examples in using SIP as a core technological component of the p2p world are also presented

Traffic Engineering with Segment Routing: SDN-based Architectural Design and Open Source Implementation

Traffic Engineering (TE) in IP carrier networks is one of the functions that can benefit from the Software Defined Networking paradigm. By logically centralizing the control of the network, it is possible to "program" per-flow routing based on TE goals. Traditional per-flow routing requires a direct interaction between the SDN controller and each node that is involved in the traffic paths. Depending on the granularity and on the temporal properties of the flows, this can lead to scalability issues for the amount of routing state that needs to be maintained in core network nodes and for the required configuration traffic. On the other hand, Segment Routing (SR) is an emerging approach to routing that may simplify the route enforcement delegating all the configuration and per-flow state at the border of the network. In this work we propose an architecture that integrates the SDN paradigm with SR-based TE, for which we have provided an open source reference implementation. We have designed and implemented a simple TE/SR heuristic for flow allocation and we show and discuss experimental results.Comment: Extended version of poster paper accepted for EWSDN 2015 (version v4 - December 2015

A Balanced Trust-Based Method to Counter Sybil and Spartacus Attacks in Chord

A Sybil attack is one of the main challenges to be addressed when securing peer-to-peer networks, especially those based on Distributed Hash Tables (DHTs). Tampering routing tables by means of multiple fake identities can make routing, storing, and retrieving operations significantly more difficult and time-consuming. Countermeasures based on trust and reputation have already proven to be effective in some contexts, but one variant of the Sybil attack, the Spartacus attack, is emerging as a new threat and its effects are even riskier and more difficult to stymie. In this paper, we first improve a well-known and deployed DHT (Chord) through a solution mixing trust with standard operations, for facing a Sybil attack affecting either routing or storage and retrieval operations. This is done by maintaining the least possible overhead for peers. Moreover, we extend the solution we propose in order for it to be resilient also against a Spartacus attack, both for an iterative and for a recursive lookup procedure. Finally, we validate our findings by showing that the proposed techniques outperform other trust-based solutions already known in the literature as well

Teachers\u27 Perceptions of Manipulatives During Middle School Math Instruction

In a Colorado school district, school personnel and parents were concerned that middle school math proficiency levels were low for 2011-2014 and math teachers were not using manipulatives in their classes to increase math performance. The district\u27s math coordinator did not foresee providing specific professional development (PD) for math manipulative use to address these concerns. Without this PD, math teachers may be ill-quipped to teach math concepts when using manipulatives, which, in turn, could lead to further poor math performance. The purpose of this qualitative bounded collective case study was to explore middle school teachers\u27 perceptions of PD and perceived self-efficacy regading the implementation of manipulatives. Knowles\u27s andragogy and Piaget\u27s cognitive development theories framed this study. A homogeneous sample of 12 voluntary participants with more than 5 years teaching middle school math, both with and without access to manipulatives, volunteered to participate in this study. Data from observations, interviews, and archival documents were analyzed using comparative and inductive analyses and were analytically coded. Participants reported a need for PD that focused on physical and virtual manipulatives (PM and VM) and a low perceived self-efficacy regarding manipulatives use during math instruction. A blended PD using face-to-face and distance learning formats was designed to increase math teachers\u27 knowledge of and perceived self-efficacy with PM and VM for math instruction. This endeavor may contribute to positive social change by reforming PD opportunities to support teachers\u27 practice and self-efficacy using manipulatives during math instruction, ultimately increasing student performance

NEMO: A flexible and highly scalable network EMulatOr

Evaluating novel applications and protocols in realistic scenarios has always been a very important task for all stakeholders working in the networking field. Network emulation, being a trade-off between actual deployment and simulations, represents a very powerful solution to this issue, providing a working network platform without requiring the actual deployment of all network components. We present NEMO, a flexible and scalable Java-based network emulator, which can be used to emulate either only a single link, a portion of a network, or an entire network. NEMO is able to work in both real and virtual time, depending on the tested scenarios and goals, and it can be run as either a stand-alone instance on a single machine, or distributed among different network-connected machines, leading to distributed and highly scalable emulation infrastructures. Among different features, NEMO is also capable of virtualizing the execution of third-party Java applications by running them on top of virtual nodes, possibly attached to an emulated or external network. Keywords: Network emulation, Protocol stack, Jav

PMSR - Poor Man's Segment Routing, a minimalistic approach to Segment Routing and a Traffic Engineering use case

The current specification of the Segment Routing (SR) architecture requires enhancements to the intra-domain routing protocols (e.g. OSPF and IS-IS) so that the nodes can advertise the Segment Identifiers (SIDs). We propose a simpler solution called PMSR (Poor Man's Segment Routing), that does not require any enhancement to routing protocol. We compare the procedures of PMSR with traditional SR, showing that PMSR can reduce the operation and management complexity. We analyze the set of use cases in the current SR drafts and we claim that PMSR can support the large majority of them. Thanks to the drastic simplification of the Control Plane, we have been able to develop an Open Source prototype of PMSR. In the second part of the paper, we consider a Traffic Engineering use case, starting from a traditional flow assignment optimization problem which allocates hop-by-hop paths to flows. We propose a SR path assignment algorithm and prove that it is optimal with respect to the number of segments allocated to a flow.Comment: September 2015 - Paper accepted to the Mini-conference track of NOMS 201

Effective Anomaly Detection Using Deep Learning in IoT Systems

Anomaly detection in network traffic is a hot and ongoing research theme especially when concerning IoT devices, which are quickly spreading throughout various situations of people's life and, at the same time, prone to be attacked through different weak points. In this paper, we tackle the emerging anomaly detection problem in IoT, by integrating five different datasets of abnormal IoT traffic and evaluating them with a deep learning approach capable of identifying both normal and malicious IoT traffic as well as different types of anomalies. The large integrated dataset is aimed at providing a realistic and still missing benchmark for IoT normal and abnormal traffic, with data coming from different IoT scenarios. Moreover, the deep learning approach has been enriched through a proper hyperparameter optimization phase, a feature reduction phase by using an autoencoder neural network, and a study of the robustness of the best considered deep neural networks in situations affected by Gaussian noise over some of the considered features. The obtained results demonstrate the effectiveness of the created IoT dataset for anomaly detection using deep learning techniques, also in a noisy scenario

A novel batch-based group key management protocol applied to the Internet of Things

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Concomitant mutations G12D and G13D on the exon 2 of the KRAS gene. Two cases of women with colon adenocarcinoma

Colorectal cancer (CRC) is rapidly increasing representing the second most frequent cause of cancer-related deaths. From a clinical-molecular standpoint the therapeutically management of CRC focuses on main alterations found in the RAS family protein, where single mutations of KRAS are considered both the hallmark and the target of this tumor. Double and concomitant alterations of KRAS are still far to be interpreted as molecular characteristics which could potentially address different and more personalized treatments for patients. Here, we firstly describe the case of two patients at different stages (pT2N0M0 and pT4cN1cM1) but similarly showing a double concurrent mutations G12D and G13D in the exon 2 of the KRAS gene, normally mutually exclusive. We also evaluated genetic testing of dihydropyrimidine dehydrogenase (DPYD) and microsatellite instability (MSI) by real-time PCR and additional molecular mutations by next generation sequencing (NGS) which resulted coherently to the progression of the disease. Accordingly, we reinterpreted and discuss the clinical history of both cases treated as single mutations of KRAS but similarly progressing towards a metastatic asset. We concluded that double mutations of KRAS cannot be interpreted as univocal genomic alterations and that they could severely impact the clinical outcome in CRC, requiring a tighter monitoring of patients throughout the time.Abstract: Colorectal cancer (CRC) is rapidly increasing representing the second most frequent cause of cancer-related deaths. From a clinical-molecular standpoint the therapeutically management of CRC focuses on main alterations found in the RAS family protein, where single mutations of KRAS are considered both the hallmark and the target of this tumor. Double and concomitant alterations of KRAS are still far to be interpreted as molecular characteristics which could potentially address different and more personalized treatments for patients. Here, we firstly describe the case of two patients at different stages (pT2N0M0 and pT4cN1cM1) but similarly showing a double concurrent mutations G12D and G13D in the exon 2 of the KRAS gene, normally mutually exclusive. We also evaluated genetic testing of dihydropyrimidine dehydrogenase (DPYD) and microsatellite instability (MSI) by real-time PCR and additional molecular mutations by next generation sequencing (NGS) which resulted coherently to the progression of the disease. Accordingly, we reinterpreted and discuss the clinical history of both cases treated as single mutations of KRAS but similarly progressing towards a metastatic asset. We concluded that double mutations of KRAS cannot be interpreted as univocal genomic alterations and that they could severely impact the clinical outcome in CRC, requiring a tighter monitoring of patients throughout the time