4,481 research outputs found

    GT: Picking up the Truth from the Ground for Internet Traffic

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    Much of Internet traffic modeling, firewall, and intrusion detection research requires traces where some ground truth regarding application and protocol is associated with each packet or flow. This paper presents the design, development and experimental evaluation of gt, an open source software toolset for associating ground truth information with Internet traffic traces. By probing the monitored host's kernel to obtain information on active Internet sessions, gt gathers ground truth at the application level. Preliminary exper- imental results show that gt's effectiveness comes at little cost in terms of overhead on the hosting machines. Furthermore, when coupled with other packet inspection mechanisms, gt can derive ground truth not only in terms of applications (e.g., e-mail), but also in terms of protocols (e.g., SMTP vs. POP3

    iTeleScope: Intelligent Video Telemetry and Classification in Real-Time using Software Defined Networking

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    Video continues to dominate network traffic, yet operators today have poor visibility into the number, duration, and resolutions of the video streams traversing their domain. Current approaches are inaccurate, expensive, or unscalable, as they rely on statistical sampling, middle-box hardware, or packet inspection software. We present {\em iTelescope}, the first intelligent, inexpensive, and scalable SDN-based solution for identifying and classifying video flows in real-time. Our solution is novel in combining dynamic flow rules with telemetry and machine learning, and is built on commodity OpenFlow switches and open-source software. We develop a fully functional system, train it in the lab using multiple machine learning algorithms, and validate its performance to show over 95\% accuracy in identifying and classifying video streams from many providers including Youtube and Netflix. Lastly, we conduct tests to demonstrate its scalability to tens of thousands of concurrent streams, and deploy it live on a campus network serving several hundred real users. Our system gives unprecedented fine-grained real-time visibility of video streaming performance to operators of enterprise and carrier networks at very low cost.Comment: 12 pages, 16 figure

    An individually verifiable voting protocol with complete recorded-as-intended and counted-as-recorded guarantees

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    Democratic principles demand that every voter should be able to individually verify that their vote is recorded as intended and counted as recorded, without having to trust any authorities. However, most end-to-end (E2E) verifiable voting protocols that provide universal verifiability and voter secrecy implicitly require to trust some authorities or auditors for the correctness guarantees that they provide. In this paper, we explore the notion of individual verifiability. We evaluate the existing E2E voting protocols and propose a new protocol that guarantees such verifiability without any trust requirements. Our construction depends on a novel vote commitment scheme to capture voter intent that allows voters to obtain a direct zero-knowledge proof of their vote being recorded as intended. We also ensure protection against spurious vote injection or deletion post eligibility verification, and polling-booth level community profiling
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