Resource Allocation for Secure Gaussian Parallel Relay Channels with Finite-Length Coding and Discrete Constellations

We investigate the transmission of a secret message from Alice to Bob in the presence of an eavesdropper (Eve) and many of decode-and-forward relay nodes. Each link comprises a set of parallel channels, modeling for example an orthogonal frequency division multiplexing transmission. We consider the impact of discrete constellations and finite-length coding, defining an achievable secrecy rate under a constraint on the equivocation rate at Eve. Then we propose a power and channel allocation algorithm that maximizes the achievable secrecy rate by resorting to two coupled Gale-Shapley algorithms for stable matching problem. We consider the scenarios of both full and partial channel state information at Alice. In the latter case, we only guarantee an outage secrecy rate, i.e., the rate of a message that remains secret with a given probability. Numerical results are provided for Rayleigh fading channels in terms of average outage secrecy rate, showing that practical schemes achieve a performance quite close to that of ideal ones

Information-theoretic security techniques for data communications and storage

Negli ultimi anni il bisogno di sicurezza e privacy è cresciuto in maniera esponenziale in molti aspetti delle comunicazioni, parallelamente allo sviluppo tecnologico. La maggior parte dei sistemi di sicurezza attualmente implementati sono basati sulla nozione di sicurezza computazionale, e devono essere continuamente tenuti aggiornati per affrontare il miglioramento degli attacchi e l’avanzamento tecnologico. Allo scopo di soddisfare requisiti sempre più stringenti e rigorosi, di recente è cresciuto l’interesse verso soluzioni appartenenti al paradigma della teoria dell’informazione a supporto di schemi di segretezza prettamente crittografici, in particolare grazie alla capacità di queste soluzioni di garantire sicurezza indipendentemente dalla capacità dell’attaccante, altrimenti nota come sicurezza incondizionata. In questo lavoro di tesi il nostro scopo è quello di analizzare come metriche di segretezza relative alla teoria dell’informazione possono essere applicate in sistemi pratici con lo scopo di garantire la sicurezza e la privacy dei dati. Per iniziare, vengono definite delle metriche di tipo information-teoretiche per valutare le prestazioni di segretezza di sistemi realistici di comunicazione wireless sotto vincoli pratici, e con esse un protocollo che combina tecniche di codifica per sicurezza a livello fisico con soluzioni crittografiche. Questo schema è in grado di raggiungere un dato livello di sicurezza semantica in presenza di un attaccante passivo. Allo stesso tempo vengono presi in considerazione molteplici scenari: viene fornita un’analisi di sicurezza per canali paralleli con nodi relay, trovando l’allocazione ottima di risorse che massimizza il secrecy rate. Successivamente, sfruttando un model checker probabilistico, vengono definiti i parametri per sistemi di storage distribuiti ed eterogenei che permettono di raggiungere la segretezza perfetta in condizioni pratiche. Per garantire la privacy, proponiamo inoltre uno schema che garantisce il recupero privato delle informazioni in uno scenario di caching wireless in presenza di nodi malevoli. Definiamo infine il piazzamento ottimale dei contenuti tale minimizzare l’uso del canale di backhaul, riducendo così il costo delle comunicazioni del sistema.The last years have seen a growing need of security and privacy in many aspects of communications, together with the technological progress. Most of the implemented security solutions are based on the notion of computational security, and must be kept continuously updated to face new attacks and technology advancements. To meet the more and more strict requirements, solutions based on the information-theoretic paradigm are gaining interest to support pure cryptographic techniques, thanks to their capacity to achieve security independently on the attacker’s computing resources, also known as unconditional security. In this work we investigate how information-theoretic security can be applied to practical systems in order to ensure data security and privacy. We first start defining information-theoretic metrics to assess the secrecy performance of realistic wireless communication settings under practical conditions, together with a protocol that mixes coding techniques for physical layer security and cryptographic solutions. This scheme is able to achieve some level of semantic security at the presence of a passive attacker. At the same time, multiple scenarios are considered. We provide a security analysis for parallel relay channels, thus finding an optimal resource allocation that maximizes the secrecy rate. Successively, by exploiting a probabilistic model checker, we define the parameters for heterogeneous distributed storage systems that permit us to achieve perfect secrecy in practical conditions. For privacy purposes, we propose a scheme which guarantees private information retrieval of files for caching at the wireless edge against multiple spy nodes. We find the optimal content placement that minimizes the backhaul usage, thus reducing the communication cost of the system

Semantic security with practical transmission schemes over fading wiretap channels

We propose and assess an on–off protocol for communication over wireless wiretap channels with security at the physical layer. By taking advantage of suitable cryptographic primitives, the protocol we propose allows two legitimate parties to exchange confidential messages with some chosen level of semantic security against passive eavesdroppers, and without needing either pre-shared secret keys or public keys. The proposed method leverages the noisy and fading nature of the channel and exploits coding and all-or-nothing transforms to achieve the desired level of semantic security. We show that the use of fake packets in place of skipped transmissions during low channel quality periods yields significant advantages in terms of time needed to complete transmission of a secret message. Numerical examples are provided considering coding and modulation schemes included in the WiMax standard, thus showing that the proposed approach is feasible even with existing practical devices

Comparison of Statistical and Machine Learning Techniques for Physical Layer Authentication

In this paper we consider authentication at the physical layer, in which the authenticator aims at distinguishing a legitimate supplicant from an attacker on the basis of the characteristics of a set of parallel wireless channels, which are affected by time-varying fading. Moreover, the attacker's channel has a spatial correlation with the supplicant's one. In this setting, we assess and compare the performance achieved by different approaches under different channel conditions. We first consider the use of two different statistical decision methods, and we prove that using a large number of references (in the form of channel estimates) affected by different levels of time-varying fading is not beneficial from a security point of view. We then consider classification methods based on machine learning. In order to face the worst case scenario of an authenticator provided with no forged messages during training, we consider one-class classifiers. When instead the training set includes some forged messages, we resort to more conventional binary classifiers, considering the cases in which such messages are either labelled or not. For the latter case, we exploit clustering algorithms to label the training set. The performance of both nearest neighbor (NN) and support vector machine (SVM) classification techniques is evaluated. Through numerical examples, we show that under the same probability of false alarm, one-class classification (OCC) algorithms achieve the lowest probability of missed detection when a small spatial correlation exists between the main channel and the adversary one, while statistical methods are advantageous when the spatial correlation between the two channels is large

Contactless Walking Recognition based on mmWave RADAR

Analysis of a person's movement provides important information about his or her health status. This analysis can be performed with wearable devices or with contactless technologies. These latter in particular are of some interest, since the subject is free to move and the analysis of the movement is realistic. Despite being designed for other purposes, automotive mmWaves radars represent a powerful low-cost technology for detecting people's movements without contact which finds interesting applications as a support for home monitoring of health conditions. In this paper it is shown how to exploit commercial radars to distinguish with high precision the way of walking of a subject and the position of his hands during the activity carried out. The application of Principal Component Analysis (PCA) for feature extraction from raw data is considered, together with supervised machine learning algorithms for the actual classification of the various activities carried out during the experiments

Statistical and Machine Learning-Based Decision Techniques for Physical Layer Authentication

In this paper we assess the security performance of key-less physical layer authentication schemes in the case of time-varying fading channels, considering both partial and no channel state information (CSI) on the receiver's side. We first present a generalization of a well-known protocol previously proposed for flat fading channels and we study different statistical decision methods and the corresponding optimal attack strategies in order to improve the authentication performance in the considered scenario. We then consider the application of machine learning techniques in the same setting, exploiting different one-class nearest neighbor (OCNN) classification algorithms. We observe that, under the same probability of false alarm, one-class classification (OCC) algorithms achieve the lowest probability of missed detection when a low spatial correlation exists between the main channel and the adversary one, while statistical methods are advantageous when the spatial correlation between the two channels is higher.Comment: To be presented at IEEE Globecom 201

On the security of transmissions over fading wiretap channels in realistic conditions

Transmissions over the wiretap channel have been studied for a long time from the information theory standpoint. This has allowed to assess the secrecy performance against eavesdropping while ensuring reliable transmission towards the legitimate receiver. However, most previous studies rely on a number of assumptions which are far from practical wireless communications, like infinite length codewords, random coding, discrete channels or continuous channels with Gaussian signaling. In this paper, we show how the level of security at the physical layer can be assessed from the information theoretic standpoint while taking into account the constraints of practical transmissions over realistic wireless wiretap channels, i.e., by considering practical codes with finite length, discrete modulation formats and continuous channels with fading. For this purpose, we consider the notion of mutual information security, which is provably equivalent to semantic security. Our target is to show that classical and already implemented coding and modulation schemes can be used to achieve some level of security at the physical layer, opposed to approaches resorting to completely new designs tailored to secure transmissions. To corroborate this thesis, we consider some coding and modulation schemes compliant with the IEEE 802.16e (WiMax) standard and show how they can be used to achieve some given security level