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Schematic representation of an MNO's network deployment connected to the Internet, including control-and data-plane. The GTP tunnel hides the control-plane elements.
Source publication
Cellular network performance is often viewed as primarily dominated by the radio technology. However, reality proves more complex: mobile operators deploy and configure their networks in different ways, and sometimes establish network sharing agreements with other mobile carriers. Moreover, regulators have encouraged newer operational models such a...
Context in source publication
Context 1
... data plane, represented by the yellow pipe in Figure 1, consists of a direct IP tunnel created by the GPRS Tunneling Protocol (GTP) [13] between the handset and a gateway specified in the APN settings on the device. To connect to the Internet, a mobile device must possess an APN configuration provided by its operator. ...
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Citations
... Many times the existence of network devices is also ignored. [24] covers the variation in the middleboxes. Note that the tool implementation often overlooks this aspect as it is not part of its core methodology. ...
The debate on "Net-neutrality" and events pointing towards its possible violations have led to the development of tools to detect deliberate traffic discrimination on the Internet. Given the complex nature of the Internet, neutrality violations are not easy to detect, and tools developed so far suffer from various limitations. In this paper, we study many challenges in detecting the violations and discuss possible approaches to mitigate them. As a case study, we focus on the tool Wehe \cite{wehe} and discuss its limitations and propose the aspects that need to be strengthened. Wehe is the most recent tool to detect neutrality violations. Despite Wehe's vast utility and possible influences over policy decisions, its mechanisms are not yet fully validated by researchers other than original tool developers. We seek to fill this gap by conducting a thorough and in-depth validation of Wehe. Our validation uses the Wehe App, a client-server setup mimicking Wehe's behavior and its theoretical arguments. We validated the Wehe app for its methodology, traffic discrimination detection, and operational environments. We found that the critical weaknesses of the Wehe App are due to its design choices of using port number 80, overlooking the effect of background traffic, and the direct performance comparison.
... • Crowdsourcing tools: Previous research studies developed crowdsourcing measurements platforms to execute active measurements through the proactive participation of the user. These studies leveraged different techniques such as purpose-built java-applets, mobile apps, or browser extensions [4], [7], [14]- [16]. Due to the crowdsourcing nature of these tools and the limitations of each platform, the data collected by these studied is sparse both in space and time. ...
... Depending on the budget, 7 it is possible to obtain between millions to hundreds of millions of daily ad impressions (i.e., DNS measurement samples) in real end-users' devices. ...
... 3) Our NS records the public IP address of the recursive resolver and end user connecting, but it only supports IPv4. Additionally, we only record the public IP address reported by our server, so we are unable to pinpoint the actual location of those DNS resolvers 7 The cost of an ad display campaign is defined based on the cost per thousand ad impressions (a.k.a CPM). CPM can be as low as $0.01. ...
The Domain Name System (DNS) is one of the most critical Internet subsystems. While the majority of ISPs deploy and operate their own DNS infrastructure, many end users resort to third-party DNS providers with hopes of enhancing their privacy, security, and web performance. However, bad user choices and the uneven geographical deployment of DNS providers could render insecure and inefficient DNS configurations for millions of users. In this paper, we propose a novel and flexible measurement method to (1) study the infrastructure of recursive DNS resolvers, including both ISP’s and third-party DNS providers’ deployment strategies; and (2) study end-user DNS choices, both in a timely manner and at a global scale. For that, we leverage the outreach capacity of online advertising networks to distribute lightweight JavaScript-based DNS measurement scripts. To showcase the potential of our technique, we launch two separate ad campaigns that triggered more than 3M DNS lookups, which allow us to identify and study more than 76k recursive DNS resolvers giving support to more than 25k eyeball ASes in 178 countries. The analysis of the data offers new insights into the DNS infrastructure, such as user preferences towards third-party DNS providers (namely, Google, OpenDNS, Level3, and Cloudflare recursive DNS resolvers account for ~13% of the total DNS requests triggered by our campaigns), and into deployment decisions of many ISPs providing both mobile and fixed access networks to separate the DNS infrastructure serving each type of access technology.
... Summarizing, robustness to both faults and targeted attacks, as well as the limits on performance, highly depend on topology: its knowledge and control is of paramount importance that further increases with the envisioned evolution towards I4.0 requirements. Despite this, neither topology [227], [228], not network performance guarantees [229], [230] nor network neutrality [231], [232], nor censorship [233], nor malicious actors [220] are easy to detect and assess, thus requiring specialized monitoring tools, systems, and infrastructures to be designed and deployed [230], [234]- [237]. The impact of such factors on the effectiveness of I4.0, and ultimately on its possibility of expansion to different geopolitical areas, is an uncertainty hardly addressable beforehand, and cannot be understated. ...
A new industrial revolution is undergoing, based on a number of technological paradigms. The will to foster and guide this phenomenon has been summarized in the expression “Industry 4.0” (I4.0). Initiatives under this term share the vision that many key technologies underlying Cyber-Physical Systems and Big Data Analytics are converging to a new distributed, highly automated, and highly dynamic
production network
, and that this process needs regulatory and cultural advancements to effectively and timely develop. In this work, we focus on the technological aspect only, highlighting the unprecedented complexity of I4.0 emerging from the scientific literature. While previous works have focused on one or up to four related enablers, we consider ten technological enablers, including besides the most cited Big Data, Internet of Things, and Cloud Computing, also others more rarely considered as Fog and Mobile Computing, Artificial Intelligence, Human-Computer Interaction, Robotics, down to the often overlooked, very recent, or taken for granted Open-Source Software, Blockchain, and the Internet. For each we explore the main characteristics in relation to I4.0 and its interdependencies with other enablers. Finally we provide a detailed analysis of challenges in leveraging each of the enablers in I4.0, evidencing possible roadblocks to be overcome and pointing at possible future directions of research. Our goal is to provide a reference for the experts in some of the technological fields involved, for a reconnaissance of integration and hybridization possibilities with other fields in the endeavor of I4.0, as well as for the laymen, for a high-level grasp of the variety (and often deep history) of the scientific research backing I4.0.
... It has about 1 million users and fully operates on top of China Telecom 2 (abbreviated as B-Mobile), a nationwide base carrier in China which has over 300 million users. V-Mobile is a representative light MVNO ( §2), the most popular type of MVNOs that fully rely on the base carrier's cellular infrastructure [35], while having the capability of designing their own data plans independently of the base carriers. In other words, V-Mobile resells data plans purchased from B-Mobile to its users. ...
... According to their degrees of dependence on base carriers, today's MVNOs can be classified into three categories [10,35]: skinny MVNOs, light MVNOs, and thick MVNOs. Skinny and light MVNOs do not have their own radio infrastructures; the former are mainly devoted to marketing and sales, and are thus also known as "branded resellers, " while the latter further have the ability to design specialized data plans independently of the base carriers. ...
... In contrast, thick MVNOs have their own infrastructures to exert more control over their offerings, which however are not permitted in many countries. Among the three categories, light MVNOs are the most common and are permitted in most countries [35]. In this paper, our studied V-Mobile is a typical light MVNO. ...
Recent years have witnessed the rapid growth of mobile virtual network operators (MVNOs), which operate on top of the existing cellular infrastructures of base carriers while offering cheaper or more flexible data plans compared to those of the base carriers. In this paper, we present a nearly two-year measurement study towards understanding various key aspects of today's MVNO ecosystem, including its architecture, performance, economics, customers, and the complex interplay with the base carrier. Our study focuses on a large commercial MVNO with \reviseabout 1 million customers, operating atop a nation-wide base carrier. Our measurements clarify several key concerns raised by MVNO customers, such as inaccurate billing and potential performance discrimination with the base carrier. We also leverage big data analytics and machine learning to optimize an MVNO's key businesses such as data plan reselling and customer churn mitigation. Our proposed techniques can help achieve %will lead to higher revenues and improved services for commercial MVNOs.
... Middleboxes are known to introduce a series of issues and hinder the evolution of protocols such as TCP. Since middleboxes are ubiquitous in MBB networks [34,36,37], in collaboration with the H2020 MAMI project [16] we aim to observe and characterize middlebox operations in the context of real-world MBB deployments. MONROE further enables assessment of existing protocols, paving the way for protocol innovation. ...
Open experimentation with operational Mobile Broadband (MBB) networks in the wild is currently a fundamental requirement of the research community in its endeavor to address the need of innovative solutions for mobile communications. Even more, there is a strong need for objective data about stability and performance of MBB (e.g., 3G/4G) networks, and for tools that rigorously and scientifically assess their status. In this paper, we introduce the MONROE measurement platform: an open access and flexible hardware-based platform for measurements and custom experimentation on operational MBB networks. The MONROE platform enables accurate, realistic and meaningful assessment of the performance and reliability of 11 MBB networks in Europe. We report on our experience designing, implementing and testing the solution we propose for the platform. We detail the challenges we overcame while building and testing the MONROE testbed and argue our design and implementation choices accordingly. We describe and exemplify the capabilities of the platform and the wide variety of experiments that external users already perform using the system.
... MobiPerf, the successor of 4GTest and 3GTest, has been deployed to uncover the RRC state dynamics in cellular networks [38], [40] and study the network performance from end users' perspectives [37], [39]. Netalyzr, another measurement app in Android, is used to characterize middlebox behavior and business relationships in cellular networks [56]. These existing apps are designed with more concern on privacy issues or energy consumption, but their accuracy has not received any attention. ...
... For instance, a short list of publications surveying 3G networks can be found on the TMA portal [2]. A taxonomy of these publications could be structured in three main categories, based on the type of data they collect and analyse: 1) Passive Sub-IP data: data relevant for the physical layer of the Radio Access Network (RAN), namely signal strength (RSSI, ASU), cellular operator identification (MCC, MNC, LAC, Cell ID) and radio technology (2G/3G/4G) [3], [4], [5], [6]; 2) Passive Super-IP data: data relevant for the assessment of the Quality of Experience (QoE) of the end-user, namely the latency, measured with ICMP and/or HTTP traffic [7], [8], [9], [10]; 3) Active data, where one attempts to collect data revealing the insight of the cellular network architecture, in particular the deployment of web proxies, DNS caches or CGN [11], [12], [13]. Most often, target servers in active measurements fall under the control of the authors of the study (i.e. ...
... For instance, a short list of publications surveying 3G networks can be found on the TMA portal [2]. A taxonomy of these publications could be structured in three main categories, based on the type of data they collect and analyze: 1) Passive Sub-IP data: data relevant for the physical layer of the Radio Access Network (RAN), namely signal strength (RSSI, ASU), cellular operator identification (MCC, MNC, LAC, Cell ID) and radio technology (2G/3G/4G) [3], [4], [5], [6]; 2) Passive Super-IP data: data relevant for the assessment of the Quality of Experience of the end-user, namely the latency, measured with ICMP and/or HTTP traffic [7], [8], [9], [10]; 3) Active data, where one attempts to collect data revealing the insight of the cellular network architecture, in particular the deployment of web proxies, DNS or CGN [11], [12], [13]. Most often, target servers in active measurements fall under the control of the authors of the study (i.e. ...
... In-path proxies allow VPN services to gain control over users traffic and to manipulate traffic on the fly [109,110,98]. Moreover, many proxy features can provide an economic benefit for ISPs and network providers as in the case of HTTP header injection [108] or traffic redirection for advertising purposes [111]. ...
... In a nutshell, Netalyzr controls both client and server side and crafts packets and HTTP requests in a way that would allow identifying non-transparent proxies along the path [110]. We refer the reader to Netalyzr-related bibliography for further implementation details [89,110,109]. ...
... In-path proxies may have additional negative effects on user's traffic which are beyond the scope of this study. Many of them may have their own particular or incomplete interpretation of transport-layer protocols [109]. In the case of HTTP proxies, Netalyzr test revealed that 47% and 55% of free and premium VPN apps actively modify HTTP traffic by default. ...
Millions of users worldwide resort to mobile VPN clients to either circumvent censorship or to access geo-blocked content, and more generally for privacy and security purposes. In practice, however, users have little if any guarantees about the corresponding security and privacy settings, and perhaps no practical knowledge about the entities accessing their mobile traffic.
In this paper we provide a first comprehensive analysis of 283 Android apps that use the Android VPN permission, which we extracted from a corpus of more than 1.4 million apps on the Google Play store. We perform a number of passive and active measurements designed to investigate a wide range of security and privacy features and to study the behavior of each VPN-based app. Our analysis includes investigation of possible malware presence, third-party library embedding, and traffic manipulation, as well as gauging user perception of the security and privacy of such apps. Our experiments reveal several instances of VPN apps that expose users to serious privacy and security vulnerabilities, such as use of insecure VPN tunneling protocols, as well as IPv6 and DNS traffic leakage. We also report on a number of apps actively performing TLS interception. Of particular concern are instances of apps that inject JavaScript programs for tracking, advertising, and for redirecting e-commerce traffic to external partners.
... We show how data can be shared with different levels of privacy in light of untrusted infrastructure. We use findings identified in [14,15] that show widespread use of transparent middle boxes such as HTTP and DNS proxies in the cellular infrastructure which are able to analyse and actively modify user traffic and thus compromise user privacy and security. In [4] we provided rich set of simulation based experiments with real world traces of middle boxes [14], connectivity [7], interests [7] and friendships [7]. ...
... We use findings identified in [14,15] that show widespread use of transparent middle boxes such as HTTP and DNS proxies in the cellular infrastructure which are able to analyse and actively modify user traffic and thus compromise user privacy and security. In [4] we provided rich set of simulation based experiments with real world traces of middle boxes [14], connectivity [7], interests [7] and friendships [7]. This paper addresses these scenarios and proposes a way of integrating different layers within our MODiToNeS platform and exploring how different intelligent routing can exploit maximally trusted routes based on the real time probes and collaboration with the MODiToNeS nodes that may be infrastructure nodes or fully ad hoc local nodes based on the local context sensing. ...
... We base our deployment on the real-world data traces of different probes for mobile networks across 112 countries and over 200 mobile providers obtained by netalyzr in [14,15]. We select traces from Germany as its number of mobile networks providers best suits our real world user communication trace [7]. ...
Fast emerging mobile edge computing, mobile clouds, Internet of Things (IoT) and cyber physical systems require many novel realistic real time multi-layer algorithms for a wide range of domains, such as intelligent content provision and processing, smart transport, smart manufacturing systems and mobile end user applications. This paper proposes a low cost open source platform, MODiToNeS, which uses commodity hardware to support prototyping and testing of fully distributed multi-layer complex algorithms over real world (or pseudo real) traces. MODiToNeS platform is generic and comprises multiple interfaces that allow real time topology and mobility control, deployment and analysis of different self-organised and self-adaptive routing algorithms, real time content processing, and real time environment sensing with predictive analytics. Our platform also allows rich interactivity with the user. We show deployment and analysis of two vastly different complex networking systems: fault and disconnection aware smart manufacturing sensor network and cognitive privacy for personal clouds. We show that our platform design can integrate both contexts transparently and organically and allows a wide range of analysis.
