It has been long observed that communication between a client and a content server using overlay detours may result in substantially better performance than a native path offered by IP routing. Yet the use of detours has been limited to distributed platforms such as Akamai. This paper poses a question - how can clients practically take advantage of overlay detours without modification to content servers (which are obviously outside clients' control)? We have posited elsewhere that the emergence of gigabit-to-the-home access networks would precipitate a new home network appliance, which would maintain permanent presence on the Internet for the users and have general computing and storage capabilities. Given such an appliance, our vision is that Internet users may form cooperatives in which members agree to serve as waypoints points to each other to improve each other's Internet experience. To make detours transparent to the server, we leverage MPTCP, which normally allows a device to communicate with the server on several network interfaces in parallel but we use it to communicate through external waypoint hosts. The waypoints then mimic MPTCP's subflows to the server, making the server oblivious to the overlay detours as long as it supports MPTCP.
more »
« less
Rethinking Home Networks in the Ultrabroadband Era
The advent of ultrabroadband Internet connectivity
brings a 2-3 orders of magnitude jump in the capacity of access
networks (a.k.a. the “last mile”). Beyond mere capacity increase,
this leap represents a qualitative shift in the overall Internet
environment. Therefore, we argue that only by seizing the opportunity
to re-think the way we structure network applications
and services can we realize the full potential ultrabroadband
provides.
Specifically, with ultrabroadband residential networks, we
have the opportunity to re-center our digital lives around our
residence, similar to how our physical lives generally center
around our homes. To this end, we introduce a new appliance
in home networks–a “home point of presence”–that provides a
variety of services to the users in the house regardless of where
they are physically located and connected to the network. We
illustrate the utility of this appliance by discussing a range of
new services that both bring new functionality to the users and
improve performance of existing applications.
more »
« less
- Award ID(s):
- 1647145
- PAR ID:
- 10149775
- Date Published:
- Journal Name:
- IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
- Page Range / eLocation ID:
- 1868 to 1877
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Significant growth of internet applications in recent years has raised a lot of challenges to networks. One of the important applications is smart and connected health (SCH), which utilizes sensing, communication networks and artificial intelligent (AI) techniques to offer healthcare services to the users. In SCH applications, Wireless Body Area Networks (WBANs) consisting of a group of Lightweight and wearable devices designed for use within the proximity of the human body, is a key infrastructure. In this short paper, we discussed the possibility of exploring AI techniques for WBANs to improve network performance and enhance health services. In addition, we present the literature review of AI driven networks for SCH, its related challenges and future directions.more » « less
-
Home networks lack the powerful security tools and trained personnel available in enterprise networks. This compli- cates efforts to address security risks in residential settings. While prior efforts explore outsourcing network traffic to cloud or cloudlet services, such an approach exposes that network traffic to a third party, which introduces privacy risks, particularly where traffic is decrypted (e.g., using Transport Layer Security Inspection (TLSI)). To enable security screening locally, home networks could introduce new physical hardware, but the capital and deployment costs may impede deployment. In this work, we explore a system to leverage existing available devices, such as smartphones, tablets and laptops, already inside a home network to create a platform for traffic inspection. This software-based solution avoids new hardware deployment and allows decryption of traffic without risk of new third parties. Our investigation compares on-router inspection of traffic with an approach using that same router to direct traffic through smartphones in the local network. Our performance evaluation shows that smartphone middleboxes can substantially increase the throughput of communication from around 10 Mbps in the on-router case to around 90 Mbps when smartphones are used. This approach increases CPU usage at the router by around 15%, with a 20% CPU usage increase on a smartphone (with single core processing). The network packet latency increases by about 120 milliseconds.more » « less
-
null (Ed.)Abstract The proliferation of smart home Internet of things (IoT) devices presents unprecedented challenges for preserving privacy within the home. In this paper, we demonstrate that a passive network observer (e.g., an Internet service provider) can infer private in-home activities by analyzing Internet traffic from commercially available smart home devices even when the devices use end-to-end transport-layer encryption . We evaluate common approaches for defending against these types of traffic analysis attacks, including firewalls, virtual private networks, and independent link padding, and find that none sufficiently conceal user activities with reasonable data overhead. We develop a new defense, “stochastic traffic padding” (STP), that makes it difficult for a passive network adversary to reliably distinguish genuine user activities from generated traffic patterns designed to look like user interactions. Our analysis provides a theoretical bound on an adversary’s ability to accurately detect genuine user activities as a function of the amount of additional cover traffic generated by the defense technique.more » « less
-
null (Ed.)Smart-home devices promise to make users’ lives more convenient. However, at the same time, such devices increase the possibility of breaching users’ privacy as they are tightly connected to the users’ daily lives and activities. To address privacy invasion through smart-home devices, we present ChatterHub. This novel approach accurately identifies smart-home devices’ activities with minimal monitoring of encrypted traffic in the home network. ChatterHub targets devices that can only connect to the Internet through a centralized smart-home hub (e.g., Samsung SmartThings) using Zigbee or Z-wave. Specifically, ChatterHub passively eavesdrops on encrypted network traffic from the hub and leverages machine learning techniques to classify events and states of smart-home devices. Using ChatterHub, an adversary can identify smart-home devices’ specific activities without prior knowledge of the target smart home (e.g., list of deployed devices, types of communication protocols). We evaluated the accuracy and efficiency of ChatterHub in three real-world smart-home environments, and the evaluation results show that an attacker can successfully disclose smart-home devices’ behaviors with over 88% F1 score. We further demonstrate that ChatterHub successfully recognizes privacy-sensitive activities, including open and close of a smart door lock and turn on and off of smart LED. Additionally, to mitigate the threats posed by ChatterHub, we introduce two approaches, packet padding and random sequence injection. These mitigation approaches can effectively prevent threats from ChatterHub with only 9.2MB of additional network traffic per day.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICDCS.2019.00185
