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Researcher profile

Arsenia Chorti

Arsenia Chorti contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
eess.SPCryptography and SecurityInformation Theorymath.ITArtificial IntelligenceMachine LearningNetworking and Internet Architecture

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Published work

17 published item(s)

preprint2026arXiv

Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Framework

Localization in 5G and 6G networks is essential for important use cases such as intelligent transportation, smart factories, and smart cities. Although deep learning has enabled improving localization accuracy, depending on the deployment scenario and the effort required for dataset collection campaigns on a given infrastructure, the training process for localization models can vary significantly. Furthermore, with respect to feature selection, recent works have demonstrated the robustness of angle-of-arrival (AoA) based localization. In view of these two points, we propose an adaptive framework for AoA-based localization that consists of two alternative learning strategies, each suited either for large or small training datasets. The proposed framework is evaluated on a real, massive multiple input multiple output (mMIMO) orthogonal frequency division multiplexing (OFDM) outdoor channel state information (CSI) dataset. First, we investigate offline learning when large training datasets are available; we propose a hierarchical framework that first distinguishes between line of sight (LoS) and non line of sight (NLoS) regions and then moves to more fine grained localization in the respective region. This approach provides high-performance localization through accumulated batch retraining and an integrated hyperparameter optimization mechanism. Second, when only a small training dataset is available, an online learning framework is proposed, using incremental tree-based and ensemble-based models for handling streaming data and continuously updating mode, as well as an online few-shot learning model for rapidly initializing new classes from a limited labeled support set. These results showcase that highly accurate robust localization can be achieved incrementally during network operation by exploiting online learning, alleviating the need for large dataset collection campaigns.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Context-Aware Security for 6G Wireless The Role of Physical Layer Security

Sixth generation systems are expected to face new security challenges, while opening up new frontiers towards context awareness in the wireless edge. The workhorse behind this projected technological leap will be a whole new set of sensing capabilities predicted for 6G devices, in addition to the ability to achieve high precision localization. The combination of these enhanced traits can give rise to a new breed of context-aware security protocols, following the quality of security (QoSec) paradigm. In this framework, physical layer security solutions emerge as competitive candidates for low complexity, low-delay and low-footprint, adaptive, flexible and context aware security schemes, leveraging the physical layer of the communications in genuinely cross-layer protocols, for the first time.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Physical Layer Security for 6G Systems why it is needed and how to make it happen

Sixth generations (6G) systems will be required to meet diverse constraints in an integrated ground-air-space global network. In particular, meeting overly aggressive latency constraints, operating in massive connectivity regimes, with low energy footprint and low computational effort, while providing explicit security guarantees, can be challenging. In this setting, quality of security (QoSec) is envisioned as a flexible security framework for future networks with highly diverse non-functional requirements. Mirroring the differentiated services (DiffServ) networking paradigm, different security levels could be conceptualized, moving away from static security controls, captured currently in zero-trust security architectures. In parallel, the integration of communications and sensing, along with embedded (on-device) AI, can provide the foundations for building autonomous and adaptive security controls, orchestrated by a vertical security plane in coordination with a vertical semantic plane. It is in this framework, that we envision the incorporation of physical layer security (PLS) schemes in 6G security protocols, introducing security controls at all layers, for the first time.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Smart Channel State Information Pre-processing for Joint Authentication and Secret Key Distillation

While the literature on RF fingerprinting-based authentication and key distillation is vast, the two topics have customarily been studied separately. In this paper, starting from the observation that the wireless channel is a composite, deterministic / stochastic process, we propose a power domain decomposition that allows performing the two tasks simultaneously. We devise intelligent pre-processing schemes to decompose channel state information (CSI) observation vectors into "predictable" and "unpredictable" components. The former, primarily due to large-scale fading, can be used for node authentication through RF fingerprinting. The latter, primarily due to small-scale fading, could be used for semantically secure secret key generation (SKG). To perform the decomposition, we propose: (i) a fingerprint "separability" criterion, expressed through the maximisation of the total variation distance between the empirical fingerprint measures; (ii) a statistical independence metric for observations collected at different users, expressed through a normalised version of the $d$-dimensional Hilbert Schmidt independence criterion (dHSIC) test statistic. We propose both explicit implementations, using principal component analysis (PCA) and kernel PCA and black-box, unsupervised learning, using autoencoders. Our experiments on synthetic and real CSI datasets showcase that the incorporation of RF fingerprinting and SKG, with explicit security guarantees, is tangible in future generations of wireless.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Centralized and Distributed Intrusion Detection for Resource Constrained Wireless SDN Networks

Software-defined networking (SDN) was devised to simplify network management and automate infrastructure sharing in wired networks. These benefits motivated the application of SDN in wireless sensor networks to leverage solutions for complex applications. However, some of the core SDN traits turn the networks prone to denial of service attacks (DoS). There are proposals in the literature to detect DoS in wireless SDN networks, however, not without shortcomings: there is little focus on resource constraints, high detection rates have been reported only for small networks, and the detection is disengaged from the identification of the type of the attack or the attacker. Our work targets these shortcomings by introducing a lightweight, online change point detector to monitor performance metrics that are impacted when the network is under attack. A key novelty is that the proposed detector is able to operate in either centralized or distributed mode. The centralized detector has very high detection rates and can further distinguish the type of the attack (from a list of known attacks). On the other hand, the distributed detector provides information that allows to identify the nodes launching the attack. Our proposal is tested over IEEE 802.15.4 networks. The results show detection rates exceeding $96\%$ in networks of 36 and 100 nodes and identification of the type of the attack with a probability exceeding $0.89$ when using the centralized approach. Additionally, for some types of attack it was possible to pinpoint the attackers with an identification probability over $0.93$ when using distributed detectors.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Multi-factor Physical Layer Security Authentication in Short Blocklength Communication

Lightweight and low latency security schemes at the physical layer that have recently attracted a lot of attention include: (i) physical unclonable functions (PUFs), (ii) localization based authentication, and, (iii) secret key generation (SKG) from wireless fading coefficients. In this paper, we focus on short blocklengths and propose a fast, privacy preserving, multi-factor authentication protocol that uniquely combines PUFs, proximity estimation and SKG. We focus on delay constrained applications and demonstrate the performance of the SKG scheme in the short blocklength by providing a numerical comparison of three families of channel codes, including half rate low density parity check codes (LDPC), Bose Chaudhuri Hocquenghem (BCH), and, Polar Slepian Wolf codes for n=512, 1024. The SKG keys are incorporated in a zero-round-trip-time resumption protocol for fast re-authentication. All schemes of the proposed mutual authentication protocol are shown to be secure through formal proofs using Burrows, Abadi and Needham (BAN) and Mao and Boyd (MB) logic as well as the Tamarin-prover.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Rate Analysis and Deep Neural Network Detectors for SEFDM FTN Systems

In this work we compare the capacity and achievable rate of uncoded faster than Nyquist (FTN) signalling in the frequency domain, also referred to as spectrally efficient FDM (SEFDM). We propose a deep residual convolutional neural network detector for SEFDM signals in additive white Gaussian noise channels, that allows to approach the Mazo limit in systems with up to 60 subcarriers. Notably, the deep detectors achieve a loss less than 0.4-0.7 dB for uncoded QPSK SEFDM systems of 12 to 60 subcarriers at a 15% spectral compression.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Scheduling Optimization of Heterogeneous Services by Resolving Conflicts

Fifth generation (5G) new radio introduced flexible numerology to provide the necessary flexibility for accommodating heterogeneous services. However, optimizing the scheduling of heterogeneous services with differing delay and throughput requirements over 5G new radio is a challenging task. In this paper, we investigate near optimal, low complexity scheduling of radio resources for ultra-reliable low-latency communications (URLLC) when coexisting with enhanced mobile broadband (eMBB) services. We demonstrate that maximizing the sum throughput of eMBB services while servicing URLLC users, is, in the long-term, equivalent to minimizing the number of URLLC placements in the time-frequency grid; this result stems from reducing the number of infeasible placements for eMBB, to which we refer to as "conflicts". To meet this new objective, we propose and investigate new conflict-aware heuristics; a family of "greedy" and a lightweight heuristic inspired by bin packing optimization, all of near optimal performance. Moreover, having shed light on the impact of conflict in layer-2 scheduling, non-orthogonal multiple access (NOMA) emerges as a competitive approach for conflict resolution, in addition to the well established increased spectral efficiency with respect to OMA. The superior performance of NOMA, thanks to alleviating conflicts,is showcased by extensive numerical results.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Asymptotic Performance Analysis of NOMA Uplink Networks Under Statistical QoS Delay Constraints

In this paper, we study the performance of an uplink non-orthogonal multiple access (NOMA) network under statistical quality of service (QoS) delay constraints, captured through each user s effective capacity (EC). We first propose novel closed-form expressions for the EC in a two-user NOMA network and show that in the high signal-to-noise ratio (SNR) region, the 'strong' NOMA user, referred to as U2, has a limited EC, assuming the same delay constraint as the 'weak' user, referred to as U1. We demonstrate that for the weak userU1, OMA and NOMA have comparable performance at low transmit SNRs, while NOMA outperforms OMA in terms of EC at high SNRs. On the other hand, for the strong user U2, NOMA achieves higher EC than OMA at small SNRs, while OMA becomes more beneficial at high SNRs. Furthermore, we show that at high transmit SNRs, irrespective of whether the application is delay tolerant, or not, the performance gains of NOMA over OMA for U1, and OMA over NOMA for U2 remain unchanged. When the delay QoS of one user is fixed, the performance gap between NOMA and OMA in terms of total EC increases with decreasing statistical delay QoS constraints for the other user. Next, by introducing pairing, we show that NOMA with user-pairing outperforms OMA, in terms of total uplink EC. The best pairing strategies are given in the cases of four and six users NOMA, raising once again the importance of power allocation in the optimization of NOMA s performance.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Authenticated Secret Key Generation in Delay Constrained Wireless Systems

With the emergence of 5G low latency applications, such as haptics and V2X, low complexity and low latency security mechanisms are sought. Promising lightweight mechanisms include physical unclonable functions (PUF) and secret key generation (SKG) at the physical layer, as considered in this paper. In this framework we propose i) a novel authenticated encryption using SKG; ii) a combined PUF / SKG authentication to reduce computational overhead; iii) a 0-RTT resumption authentication protocol; iv) pipelining of the SKG and the encrypted data transfer. With respect to the latter, we investigate a parallel SKG approach for multi-carrier systems, where a subset of the subcarriers are used for SKG and the rest for data transmission. The optimal resource allocation is identified under security, power and delay constraints, by formulating the subcarrier allocation as a subset-sum $0-1$ knapsack optimization problem. A heuristic approach of linear complexity is proposed and shown to incur negligible loss with respect to the optimal dynamic programming solution. All of the proposed mechanisms, have the potential to pave the way for a new breed of latency aware security protocols.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Denial of Service Attacks Detection in Software-Defined Wireless Sensor Networks

Software-defined networking (SDN) is a promising technology to overcome many challenges in wireless sensor networks (WSN), particularly with respect to flexibility and reuse. Conversely, the centralization and the planes' separation turn SDNs vulnerable to new security threats in the general context of distributed denial of service (DDoS) attacks. State-of-the-art approaches to identify DDoS do not always take into consideration restrictions in typical WSNs e.g., computational complexity and power constraints, while further performance improvement is always a target. The objective of this work is to propose a lightweight but very efficient DDoS attack detection approach using change point analysis. Our approach has a high detection rate and linear complexity, so that it is suitable for WSNs. We demonstrate the performance of our detector in software-defined WSNs of 36 and 100 nodes with varying attack intensity (the number of attackers ranges from 5% to 20% of nodes). We use change point detectors to monitor anomalies in two metrics: the data packets delivery rate and the control packets overhead. Our results show that with increasing intensity of attack, our approach can achieve a detection rate close to100% and that the type of attack can also be inferred.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Flexible Multiple Access Enabling Low-Latency Communications: Introducing NOMA-R

Various verticals in 5G and beyond (B5G) networks require very stringent latency guarantees, while at the same time envisioning massive connectivity. As a result, choosing the optimal multiple access (MA) technique to achieve low latency is a key enabler of B5G. In particular, this issue is more acute in uplink transmissions due to the potentially high number of collisions. On this premise, in the present contribution we discuss the issue of delay-sensitive uplink connectivity using optimized MA techniques; to this end, we perform a comparative analysis of various MA approaches with respect to the achievable effective capacity (EC). As opposed to standard rate (PHY) or throughput (MAC) analyses, we propose the concept of the effective capacity as a suitable metric for characterizing jointly PHY-MAC layer delays. The palette of investigated MA approaches includes standard orthogonal MA (OMA) and power domain non orthogonal MA (NOMA) in uplink scenarios, both considering random pairing and optimized pairing alternatives. It further extends to encompass a recently proposed third alternative, referred to as NOMA-Relevant (NOMA-R), which extends OMA and NOMA approaches by flexibly selecting the MA technique. We show that optimizing both user pairing and MA selection increases the network EC, especially when stringent delay constraints are in place; thus a flexible MA is a potentially preferable strategy for future low latency applications

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Man-in-the-Middle and Denial of Service Attacks in Wireless Secret Key Generation

Wireless secret key generation (W-SKG) from shared randomness (e.g., from the wireless channel fading realizations), is a well established scheme that can be used for session key agreement. W-SKG approaches can be of particular interest in delay constrained wireless networks and notably in the context of ultra reliable low latency communications (URLLC) in beyond fifth generation (B5G) systems. However, W-SKG schemes are known to be malleable over the so called "advantage distillation" phase, during which observations of the shared randomness are obtained at the legitimate parties. As an example, an active attacker can act as a man-in-the-middle (MiM) by injecting pilot signals and/or can mount denial of service attacks (DoS) in the form of jamming. This paper investigates the impact of injection and reactive jamming attacks in W-SKG. First, it is demonstrated that injection attacks can be reduced to - potentially less harmful - jamming attacks by pilot randomization; a novel system design with randomized QPSK pilots is presented. Subsequently, the optimal jamming strategy is identified in a block fading additive white Gaussian noise (BF-AWGN) channel in the presence of a reactive jammer, using a game theoretic formulation. It is shown that the impact of a reactive jammer is far more severe than that of a simple proactive jammer

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Performance Analysis of NOMA Uplink Networks under Statistical QoS Delay Constraints

In the fifth generation and beyond (B5G), delayconstraints emerge as a topic of particular interest, e.g. forultra-reliable low latency communications (URLLC) such asautonomous vehicles and enhanced reality. In this paper, westudythe performance of a two-user uplink NOMA network understatistical quality of service (QoS) delay constraints, capturedthrough each user s effective capacity (EC). We propose novelclosed-form expressions for the EC of the NOMA users andshow that in the high signal to noise ratio (SNR) region, the 'strong' NOMA user has a limited EC, assuming the same delayconstraint as the 'weak' user. We demonstrate that for the weakuser, OMA achieves higher EC than NOMA at small values ofthe transmit SNR, while NOMA outperforms OMA in terms ofEC at high SNRs. On the other hand, for the strong user theopposite is true, i.e., NOMA achieves higher EC than OMA atsmall SNRs, while OMA becomes more beneficial at high SNRs.This result raises the question of introducing 'adaptive' OMA /NOMA policies, based jointly on the users delay constraints aswell as on the available transmit power.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Performance Analysis of Uplink NOMA-Relevant Strategy Under Statistical Delay QoS Constraints

A new multiple access (MA) strategy, referred to as non orthogonal multiple access - Relevant (NOMA-R), allows selecting NOMA when this increases all individual rates, i.e., it is beneficial for both strong(er) and weak(er) individual users. This letter provides a performance analysis of the NOMA-R strategy in uplink networks with statistical delay constraints. Closed-form expressions of the effective capacity (EC) are provided in two-users networks, showing that the strong user always achieves a higher EC with NOMA-R. Regarding the network's sum EC, there are distinctive gains with NOMA-R, particularly under stringent delay constraints.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Physical Layer Security: Authentication, Integrity and Confidentiality

The goal of physical layer security (PLS) is to make use of the properties of the physical layer, including the wireless communication medium and the transceiver hardware, to enable critical aspects of secure communications. In particular, PLS can be employed to provide i) node authentication, ii) message authentication, and, iii) message confidentiality. Unlike the corresponding classical cryptographic approaches which are all based on computational security, PLS's added strength is that it is based on information theoretic security, in which no limitation with respect to the opponent's computational power is assumed and is therefore inherently quantum resistant. In this survey, we review the aforementioned fundamental aspects of PLS, starting with node authentication, moving to the information theoretic characterization of message integrity, and finally, discussing message confidentiality both in the secret key generation from shared randomness and from the wiretap channel point of view. The aim of this review is to provide a comprehensive roadmap on important relevant results by the authors and other contributors and discuss open issues on the applicability of PLS in sixth generation systems.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Real-Time Video Content Popularity Detection Based on Mean Change Point Analysis

Video content is responsible for more than 70% of the global IP traffic. Consequently, it is important for content delivery infrastructures to rapidly detect and respond to changes in content popularity dynamics. In this paper, we propose the employment of on-line change point (CP) analysis to implement real-time, autonomous and low-complexity video content popularity detection. Our proposal, denoted as real-time change point detector (RCPD), estimates the existence, the number and the direction of changes on the average number of video visits by combining: (i) off-line and on-line CP detection algorithms; (ii) an improved time-series segmentation heuristic for the reliable detection of multiple CPs; and (iii) two algorithms for the identification of the direction of changes. The proposed detector is validated against synthetic data, as well as a large database of real YouTube video visits. It is demonstrated that the RCPD can accurately identify changes in the average content popularity and the direction of change. In particular, the success rate of the RCPD over synthetic data is shown to exceed 94% for medium and large changes in content popularity. Additionally,the dynamic time warping distance, between the actual and the estimated changes, has been found to range between20sampleson average, over synthetic data, to52samples, in real data.The rapid responsiveness of the RCPD is instrumental in the deployment of real-time, lightweight load balancing solutions, as shown in a real example.

0 citations0 reviewsNo code linkedOpen access