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Domenico Giustiniano

Publications and source records attributed to Domenico Giustiniano.

13 recordsLinked to original sources
arXiv2024

Demystifying Privacy in 5G Stand Alone Networks

Ensuring user privacy remains critical in mobile networks, particularly with the rise of connected devices and denser 5G infrastructure. Privacy concerns have persisted across 2G, 3G, and 4G/LTE networks. Recognizing these concerns, the 3rd Generation Partnership Project (3GPP) has made privacy enhancements in 5G Release 15. However, the extent of operator adoption remains unclear, especially as most networks operate in 5G Non Stand Alone (NSA) mode, relying on 4G Core Networks. This study provides the first qualitative and experimental comparison between 5G NSA and Stand Alone (SA) in real operator networks, focusing on privacy enhancements addressing top eight pre-5G attacks based on recent academic literature. Additionally, it evaluates the privacy levels of OpenAirInterface (OAI), a leading open-source software for 5G, against real network deployments for the same attacks. The analysis reveals two new 5G privacy vulnerabilities, underscoring the need for further research and stricter standards.

cs.NI↗
arXiv2024

SoK: Evaluating 5G Protocols Against Legacy and Emerging Privacy and Security Attacks

Ensuring user privacy remains a critical concern within mobile cellular networks, particularly given the proliferation of interconnected devices and services. In fact, a lot of user privacy issues have been raised in 2G, 3G, 4G/LTE networks. Recognizing this general concern, 3GPP has prioritized addressing these issues in the development of 5G, implementing numerous modifications to enhance user privacy since 5G Release 15. In this systematization of knowledge paper, we first provide a framework for studying privacy and security related attacks in cellular networks, setting as privacy objective the User Identity Confidentiality defined in 3GPP standards. Using this framework, we discuss existing privacy and security attacks in pre-5G networks, analyzing the weaknesses that lead to these attacks. Furthermore, we thoroughly study the security characteristics of 5G up to the new Release 19, and examine mitigation mechanisms of 5G to the identified pre-5G attacks. Afterwards, we analyze how recent 5G attacks try to overcome these mitigation mechanisms. Finally, we identify current limitations and open problems in security of 5G, and propose directions for future work.

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arXiv2020

Electrosense+: Crowdsourcing Radio Spectrum Decoding using IoT Receivers

Web spectrum monitoring systems based on crowdsourcing have recently gained popularity. These systems are however limited to applications of interest for governamental organizationsor telecom providers, and only provide aggregated information about spectrum statistics. Theresult is that there is a lack of interest for layman users to participate, which limits its widespreaddeployment. We present Electrosense+ which addresses this challenge and creates a general-purpose and open platform for spectrum monitoring using low-cost, embedded, and software-defined spectrum IoT sensors. Electrosense+ allows users to remotely decode specific parts ofthe radio spectrum. It builds on the centralized architecture of its predecessor, Electrosense, forcontrolling and monitoring the spectrum IoT sensors, but implements a real-time and peer-to-peercommunication system for scalable spectrum data decoding. We propose different mechanismsto incentivize the participation of users for deploying new sensors and keep them operational inthe Electrosense network. As a reward for the user, we propose an incentive accounting systembased on virtual tokens to encourage the participants to host IoT sensors. We present the newElectrosense+ system architecture and evaluate its performance at decoding various wireless sig-nals, including FM radio, AM radio, ADS-B, AIS, LTE, and ACARS.

cs.NI↗
arXiv2019

Research in Visible Light Communication Systems with OpenVLC1.3

In this paper, we present the design and implementation of our latest OpenVLC1.3 platform to perform research in Visible Light Communication Systems. We retain the advantages of the previous versions such as TCP/IP layers support, software programmability and low-cost front-end. We re-design the transceiver to support higher modulation rates and sensitivity. This allows us to reach a throughput of 400 kb/s (a factor of 4 with respect to the previous version) and increase the distance by a factor of 3.5. We further improve the software robustness of the system and reduce the form factor at similar hardware cost.

cs.NI↗
arXiv2018

Statistical Location and Rotation-Aware Beam Search for Millimeter-Wave Networks

Beam training in dynamic millimeter-wave (mm-wave) networks with mobile devices is highly challenging as devices must scan a large angular domain to maintain alignment of their directional antennas under mobility. Device rotation is particularly challenging, as a handheld device may rotate significantly over a very short period of time, causing it to lose the connection to the Access Point (AP) unless the rotation is accompanied by immediate beam realignment. We study how to maintain the link to a mm-wave AP under rotation and without any input from inertial sensors, exploiting the fact that mm-wave devices will typically be multi-band. We present a model that maps Time-of-Flight measurements to rotation and propose a method to infer the rotation speed of the mobile terminal using only measurements from sub-6 GHz WiFi. We also use the same sub-6 GHz WiFi system to reduce the angle error estimate for link establishment, exploiting the spatial geometry of the deployed APs and a statistical model that maps the user position's spatial distribution to an angle error distribution. We leverage these findings to introduce SLASH, a Statistical Location and rotation-Aware beam SearcH algorithm that adaptively narrows the sector search space and accelerates both link establishment and maintenance between mm-wave devices. We evaluate SLASH with experiments conducted indoors with a sub-6 GHz WiFi Time-of-Flight positioning system and a 60-GHz testbed. SLASH can increase the data rate by more than 41% for link establishment and 67% for link maintenance with respect to prior work.

cs.NI↗
arXiv2018

Distributed Deep Learning Models for Wireless Signal Classification with Low-Cost Spectrum Sensors

This paper looks into the technology classification problem for a distributed wireless spectrum sensing network. First, a new data-driven model for Automatic Modulation Classification (AMC) based on long short term memory (LSTM) is proposed. The model learns from the time domain amplitude and phase information of the modulation schemes present in the training data without requiring expert features like higher order cyclic moments. Analyses show that the proposed model yields an average classification accuracy of close to 90% at varying SNR conditions ranging from 0dB to 20dB. Further, we explore the utility of this LSTM model for a variable symbol rate scenario. We show that a LSTM based model can learn good representations of variable length time domain sequences, which is useful in classifying modulation signals with different symbol rates. The achieved accuracy of 75% on an input sample length of 64 for which it was not trained, substantiates the representation power of the model. To reduce the data communication overhead from distributed sensors, the feasibility of classification using averaged magnitude spectrum data, or online classification on the low cost sensors is studied. Furthermore, quantized realizations of the proposed models are analyzed for deployment on sensors with low processing power.

cs.NI↗
arXiv2018

Electrosense: Open and Big Spectrum Data

While the radio spectrum allocation is well regulated, there is little knowledge about its actual utilization over time and space. This limitation hinders taking effective actions in various applications including cognitive radios, electrosmog monitoring, and law enforcement. We introduce Electrosense, an initiative that seeks a more efficient, safe and reliable monitoring of the electromagnetic space by improving the accessibility of spectrum data for the general public. A collaborative spectrum monitoring network is designed that monitors the spectrum at large scale with low-cost spectrum sensing nodes. The large set of data is stored and processed in a big data architecture and provided back to the community with an open spectrum data as a service model, that allows users to build diverse and novel applications with different requirements. We illustrate useful usage scenarios of the Electrosense data.

cs.NI↗
arXiv2018

Nanosecond-precision Time-of-Arrival Estimation for Aircraft Signals with low-cost SDR Receivers

Precise Time-of-Arrival (TOA) estimations of aircraft and drone signals are important for a wide set of applications including aircraft/drone tracking, air traffic data verification, or self-localization. Our focus in this work is on TOA estimation methods that can run on low-cost software-defined radio (SDR) receivers, as widely deployed in Mode S / ADS-B crowdsourced sensor networks such as the OpenSky Network. We evaluate experimentally classical TOA estimation methods which are based on a cross-correlation with a reconstructed message template and find that these methods are not optimal for such signals. We propose two alternative methods that provide superior results for real-world Mode S / ADS-B signals captured with low-cost SDR receivers. The best method achieves a standard deviation error of 1.5 ns.

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arXiv2017

Passive Communication with Ambient Light

In this work, we propose a new communication system for illuminated areas, indoors and outdoors. Light sources in our environments -such as light bulbs or even the sun- are our signal emitters, but we do not modulate data at the light source. We instead propose that the environment itself modulates the ambient light signals: if mobile elements 'wear' patterns consisting of distinctive reflecting surfaces, single photodiode could decode the disturbed light signals to read passive information. Achieving this vision requires a deep understanding of a new type of communication channel. Many parameters can affect the performance of passive communication based on visible light: the size of reflective surfaces, the surrounding light intensity, the speed of mobile objects, the field-of-view of the receiver, to name a few. In this paper, we present our vision for a passive communication channel with visible light, the design challenges and the evaluation of an outdoor application where our receiver decodes information from a car moving at 18 km/h.

cs.NI↗
arXiv2015

An Open-Source Research Platform for Embedded Visible Light Networking

Despite the growing interest in Visible Light Communication (VLC), a reference networking platform based on commercial off-the-shelf components is not available yet. An open-source platform would lower the barriers to entry to VLC network research and help the VLC community gain momentum. We introduce OpenVLC, an open-source VLC research platform based on software-defined implementation. Built around a credit-card-sized embedded Linux platform with a simple opto-electronic transceiver front-end, OpenVLC offers a basic physical layer, a set of essential medium access primitives, as well as interoperability with Internet protocols. We investigate the performance of OpenVLC and show examples of how it can be used along with standard network diagnostics tools. Our software-defined implementation can currently reach throughput in the order of the basic rate of IEEE 802.15.7 standard. We discuss several techniques that researchers and engineers could introduce to improve the performance of OpenVLC and envision several directions that can benefit from OpenVLC by adopting it as a reference platform.

cs.NI↗
arXiv2014

Offloading Cellular Traffic through Opportunistic Communications: Analysis and Optimization

Offloading traffic through opportunistic communications has been recently proposed as a way to relieve the current overload of cellular networks. Opportunistic communication can occur when mobile device users are (temporarily) in each other's proximity, such that the devices can establish a local peer-to-peer connection (e.g., via Bluetooth). Since opportunistic communication is based on the spontaneous mobility of the participants, it is inherently unreliable. This poses a serious challenge to the design of any cellular offloading solutions, that must meet the applications' requirements. In this paper, we address this challenge from an optimization analysis perspective, in contrast to the existing heuristic solutions. We first model the dissemination of content (injected through the cellular interface) in an opportunistic network with heterogeneous node mobility. Then, based on this model, we derive the optimal content injection strategy, which minimizes the load of the cellular network while meeting the applications' constraints. Finally, we propose an adaptive algorithm based on control theory that implements this optimal strategy without requiring any data on the mobility patterns or the mobile nodes' contact rates. The proposed approach is extensively evaluated with both a heterogeneous mobility model as well as real-world contact traces, showing that it substantially outperforms previous approaches proposed in the literature.

cs.NI↗
arXiv2013

Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Mini-Slot Access

The high bandwidth demand of Internet applications has recently driven the need of increasing the residential download speed. A practical solution to the problem has been proposed aggregating the bandwidth of 802.11 Access Points (APs) backhauls in range via 802.11 connections. Since 802.11 devices are usually single-radio, the communication to multiple APs on different radio-channels requires the introduction of a time-division multiple access (TDMA) policy at the client station. Current investigation in this area supposes that there is a sufficient number of TCP flows to saturate the Asymmetric Digital Subscriber Line (ADSL) behind the APs. However, this may be not guaranteed according to the user traffic pattern. As a consequence, a TDMA policy introduces additional delays in the end-to-end transmissions that will cause degradation of the TCP throughput and an under-utilization of the AP backhauls. In this paper, we first perform an in-depth experimental analysis with a customized 802.11 driver of how the usage of multi-AP TDMA affects the observed Round-Trip-Time (RTT) of TCP flows. Then, we introduce a simple analytical model that accurately predicts the TCP RTT when accessing the wireless medium with a Multi-AP TDMA policy. Based on this model, we propose a resource allocation algorithm that runs locally at the station and it greatly reduces the observed TCP RTT with a very low computational cost. Our proposed scheme can improve up to 1:5 times the aggregate throughput observed by the station compared to state-of-the-art multi-AP TDMA allocations. We also show that the throughput performance of the algorithm is very close to the theoretical upper-bound in key simulation scenarios.

cs.NI↗