arXiv subjects

Waqas Aman

Publications and source records attributed to Waqas Aman.

At least 19 recordsLinked to original sources

arXiv2025

Effective Capacity Analysis of Joint Near and Far-Field Communication in 6G URLLC Networks

The emergence of 6G networks enables simultaneous near-field and far-field communications through extremely large antenna arrays and high carrier frequencies. While these regimes enhance spatial multiplexing and link capacity, their coexistence poses new challenges in ensuring quality-of-service (QoS) guarantees for delay-sensitive applications. This paper presents an effective capacity (EC) analysis framework that jointly models near- and far-field communication regimes under distance estimation uncertainty. The user location is modeled as a random variable spanning both propagation regions, and tractable closed-form expression for the EC is derived to quantify delay performance. Numerical results illustrate the impact of estimation variance, QoS exponent, far-field boundary and near-field boundary (Fraunhofer distance) on EC performance.

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arXiv2025

Integrating Communication, Sensing, and Security: Progress and Prospects of PLS in ISAC Systems

The sixth generation of wireless networks defined several key performance indicators (KPIs) for assessing its networks, mainly in terms of reliability, coverage, and sensing. In this regard, remarkable attention has been paid recently to the integrated sensing and communication (ISAC) paradigm as an enabler for efficiently and jointly performing communication and sensing using the same spectrum and hardware resources. On the other hand, ensuring communication and data security has been an imperative requirement for wireless networks throughout their evolution. The physical-layer security (PLS) concept paved the way to catering to the security needs in wireless networks in a sustainable way while guaranteeing theoretically secure transmissions, independently of the computational capacity of adversaries. Therefore, it is of paramount importance to consider a balanced trade-off between communication reliability, sensing, and security in future networks, such as the 5G and beyond, and the 6G. In this paper, we provide a comprehensive and system-wise review of designed secure ISAC systems from a PLS point of view. In particular, the impact of various physical-layer techniques, schemes, and wireless technologies to ensure the sensing-security trade-off is studied from the surveyed work. Furthermore, the amalgamation of PLS and ISAC is analyzed in a broader impact by considering attacks targeting data confidentiality, communication covertness, and sensing spoofing. The paper also serves as a tutorial by presenting several theoretical foundations on ISAC and PLS, which represent a practical guide for readers to develop novel secure ISAC network designs.

cs.ET↗

arXiv2025

On the Vulnerability of Underwater Magnetic Induction Communication

Typical magnetic induction (MI) communication is commonly considered a secure underwater wireless communication (UWC) technology due to its non-audible and non-visible nature compared to acoustic and optical UWC technologies. However, vulnerabilities in communication systems inevitably exist and may lead to different types of attacks. In this paper, we investigate the eavesdropping attack in underwater MI communication to quantitatively measure the system's vulnerability under this attack. We consider different potential eavesdropping configuration setups based on the positions and orientations of the eavesdropper node to investigate how they impact the received voltage and secrecy at the legitimate receiver node. To this end, we develop finite-element-method-based simulation models for each configuration in an underwater environment and evaluate the received voltage and the secrecy capacity against different system parameters such as magnetic flux, magnetic flux density, distance, and orientation sensitivity. Furthermore, we construct an experimental setup within a laboratory environment to replicate the simulation experiments. Both simulation and lab experimental confirm the susceptibility of underwater MI communication to eavesdropping attacks. However, this vulnerability is highly dependent on the position and orientation of the coil between the eavesdropper and the legitimate transmitter. On the positive side, we also observe a unique behavior in the received coil reception that might be used to detect malicious node activities in the vicinity, which might lead to a potential security mechanism against eavesdropping attacks.

cs.CR↗

arXiv2025

Benchmarking Online Object Trackers for Underwater Robot Position Locking Applications

Autonomously controlling the position of Remotely Operated underwater Vehicles (ROVs) is of crucial importance for a wide range of underwater engineering applications, such as in the inspection and maintenance of underwater industrial structures. Consequently, studying vision-based underwater robot navigation and control has recently gained increasing attention to counter the numerous challenges faced in underwater conditions, such as lighting variability, turbidity, camera image distortions (due to bubbles), and ROV positional disturbances (due to underwater currents). In this paper, we propose (to the best of our knowledge) a first rigorous unified benchmarking of more than seven Machine Learning (ML)-based one-shot object tracking algorithms for vision-based position locking of ROV platforms. We propose a position-locking system that processes images of an object of interest in front of which the ROV must be kept stable. Then, our proposed system uses the output result of different object tracking algorithms to automatically correct the position of the ROV against external disturbances. We conducted numerous real-world experiments using a BlueROV2 platform within an indoor pool and provided clear demonstrations of the strengths and weaknesses of each tracking approach. Finally, to help alleviate the scarcity of underwater ROV data, we release our acquired data base as open-source with the hope of benefiting future research.

cs.RO↗

arXiv2024

Cyber Risk Assessment for Cyber-Physical Systems: A Review of Methodologies and Recommendations for Improved Assessment Effectiveness

Cyber-Physical Systems (CPS) integrate physical and embedded systems with information and communication technology systems, monitoring and controlling physical processes with minimal human intervention. The connection to information and communication technology exposes CPS to cyber risks. It is crucial to assess these risks to manage them effectively. This paper reviews scholarly contributions to cyber risk assessment for CPS, analyzing how the assessment approaches were evaluated and investigating to what extent they meet the requirements of effective risk assessment. We identify gaps limiting the effectiveness of the assessment and recommend real-time learning from cybersecurity incidents. Our review covers twenty-eight papers published between 2014 and 2023, selected based on a three-step search. Our findings show that the reviewed cyber risk assessment methodologies revealed limited effectiveness due to multiple factors. These findings provide a foundation for further research to explore and address other factors impacting the quality of cyber risk assessment in CPS.

cs.CR↗

arXiv2024

Performance Analysis of Underwater Acoustic Channel Amid Jamming by Random Jammers

Underwater communication networks are increasingly popularized by various important maritime applications. However, this also leads to an increased threat landscape. This letter presents the first study that considers jamming attacks by random jammers present in the surroundings of legitimate transceivers in underwater acoustic communication systems. We investigate the impact of jamming attacks on various performance parameters of the legitimate underwater acoustic communication link. In particular, we investigate the legitimate link using stochastic geometry for important performance parameters, namely coverage probability, average rate, and energy efficiency of the link between two legitimate nodes, i.e., underwater and surface nodes. We then derive and present tractable expressions for these performance parameters. Finally, we performed a Monte Carlo simulation to validate our analysis. We plot the performance metrics against the transmit power, and jamming power for different intensities of the jammers in shallow, mid, and deep water scenarios. Results reveal that on average, jamming in deep water has a relatively high impact on the performance of legitimate link than in shallow water.

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arXiv2024

On the Potential of Re-configurable Intelligent Surface (RIS)-assisted Physical Layer Authentication (PLA)

Re-configurable Intelligent Surfaces (RIS) technology is increasingly becoming a potential component for next-generation wireless networks, offering enhanced performance in terms of throughput, spectral, and energy efficiency. However, the broadcast nature of RIS-assisted wireless communication makes it vulnerable to malicious attacks at the physical layer. At the same time, physical layer authentication is gaining popularity as a solution to secure wireless networks, thwarting different attacks such as cloning, spoofing, and impersonation by using the random features of the physical layer. In this paper, we investigate RIS-assisted wireless communication systems to unlock the potential of using RIS for physical layer authentication (PLA). In particular, we exploit two distinct features of the physical layer: pathloss and channel impulse response (CIR) for PLA in RIS-assisted wireless communication. We construct hypothesis tests for the estimated features and derive closed-form error expressions. Further, we consider the critical error, i.e., missed detection, as our objective function to minimize by optimizing the phase shift of the RIS pannel. We compare the performance of our proposed mechanisms with PLA schemes using the same features but with no RIS. Furthermore, we thoroughly evaluate our proposed schemes using performance metrics such as the probability of false alarm (PFA), the probability of missed detection (PMD), and the receiver operating characteristic (ROC) curves. The results demonstrate a clear positive impact of RIS on PLA, as it effectively reduces PMD values to zero when determining the optimal phase shift.

cs.CR↗

arXiv2024

Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing

Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home. This work proposes a novel deep-learning and edge computing approach to solve the NILM problem and a few related problems as follows. 1) We build upon the reputed seq2-point convolutional neural network (CNN) model to come up with the proposed seq2-[3]-point CNN model to solve the (home) NILM problem and site-NILM problem (basically, NILM at a smaller scale). 2) We solve the related problem of appliance identification by building upon the state-of-the-art (pre-trained) 2D-CNN models, i.e., AlexNet, ResNet-18, and DenseNet-121, which are fine-tuned two custom datasets that consist of Wavelets and short-time Fourier transform (STFT)-based 2D electrical signatures of the appliances. 3) Finally, we do some basic qualitative inference about an individual appliance's health by comparing the power consumption of the same appliance across multiple homes. Low-frequency REDD dataset is used for all problems, except site-NILM where REFIT dataset has been used. As for the results, we achieve a maximum accuracy of 94.6\% for home-NILM, 81\% for site-NILM, and 88.9\% for appliance identification (with Resnet-based model).

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arXiv2023

On the Downlink Coverage Performance of RIS-Assisted THz Networks

This letter provides a stochastic geometry (SG)-based coverage probability (CP) analysis of an indoor terahertz (THz) downlink assisted by a single reconfigurable intelligent surface (RIS) panel. Specifically, multiple access points (AP) deployed on the ceiling of a hall (each equipped with multiple antennas) need to serve multiple user equipment (UE) nodes. Due to presence of blockages, a typical UE may either get served via a direct link, the RIS, or both links (the composite link). The locations of the APs and blockages are modelled as a Poisson point process (PPP) and SG framework is utilized to compute the CP, at a reference UE for all the three scenarios. Monte-Carlo simulation results validate our theoretical analysis.

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arXiv2023

Hybrid PLS-ML Authentication Scheme for V2I Communication Networks

Vehicular communication networks are rapidly emerging as vehicles become smarter. However, these networks are increasingly susceptible to various attacks. The situation is exacerbated by the rise in automated vehicles complicates, emphasizing the need for security and authentication measures to ensure safe and effective traffic management. In this paper, we propose a novel hybrid physical layer security (PLS)-machine learning (ML) authentication scheme by exploiting the position of the transmitter vehicle as a device fingerprint. We use a time-of-arrival (ToA) based localization mechanism where the ToA is estimated at roadside units (RSUs), and the coordinates of the transmitter vehicle are extracted at the base station (BS).Furthermore, to track the mobility of the moving legitimate vehicle, we use ML model trained on several system parameters. We try two ML models for this purpose, i.e., support vector regression and decision tree. To evaluate our scheme, we conduct binary hypothesis testing on the estimated positions with the help of the ground truths provided by the ML model, which classifies the transmitter node as legitimate or malicious. Moreover, we consider the probability of false alarm and the probability of missed detection as performance metrics resulting from the binary hypothesis testing, and mean absolute error (MAE), mean square error (MSE), and coefficient of determination $\text{R}^2$ to further evaluate the ML models. We also compare our scheme with a baseline scheme that exploits the angle of arrival at RSUs for authentication. We observe that our proposed position-based mechanism outperforms the baseline scheme significantly in terms of missed detections.

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arXiv2023

Pathloss-based non-Line-of-Sight Identification in an Indoor Environment: An Experimental Study

This paper reports the findings of an experimental study on the problem of line-of-sight (LOS)/non-line-of-sight (NLOS) classification in an indoor environment. Specifically, we deploy a pair of NI 2901 USRP software-defined radios (SDR) in a large hall. The transmit SDR emits an unmodulated tone of frequency 10 KHz, on a center frequency of 2.4 GHz, using three different signal-to-noise ratios (SNR). The receive SDR constructs a dataset of pathloss measurements from the received signal as it moves across 15 equi-spaced positions on a 1D grid (for both LOS and NLOS scenarios). We utilize our custom dataset to estimate the pathloss parameters (i.e., pathloss exponent) using the least-squares method, and later, utilize the parameterized pathloss model to construct a binary hypothesis test for NLOS identification. Further, noting that the pathloss measurements slightly deviate from Gaussian distribution, we feed our custom dataset to four machine learning (ML) algorithms, i.e., linear support vector machine (SVM) and radial basis function SVM (RBF-SVM), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and logistic regression (LR). It turns out that the performance of the ML algorithms is only slightly superior to the Neyman-Pearson-based binary hypothesis test (BHT). That is, the RBF-SVM classifier (the best performing ML classifier) and the BHT achieve a maximum accuracy of 88.24% and 87.46% for low SNR, 83.91% and 81.21% for medium SNR, and 87.38% and 86.65% for high SNR.

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arXiv2023

Expanding Boundaries: Cross-Media Routing for Seamless Underwater and Aerial Communication

The colossal evolution of wireless communication technologies over the past few years has driven increased interest in its integration in a variety of less-explored environments, such as the underwater medium. In this magazine paper, we present a comprehensive discussion on a novel concept of routing protocol known as cross-media routing, incorporating the marine and aerial interfaces. In this regard, we discuss the limitation of single-media routing and advocate the need for cross-media routing along with the current status of research development in this direction. To this end, we also propose a novel cross-media routing protocol known as bubble routing for autonomous marine systems where different sets of AUVs, USVs, and airborne nodes are considered for the routing problem. We evaluate the performance of the proposed routing protocol by using the two key performance metrics, i.e., packet delivery ratio (PDR) and end-to-end delay. Moreover, we delve into the challenges encountered in cross-media routing, unveiling exciting opportunities for future research and innovation. As wireless communication expands its horizons to encompass the underwater and aerial domains, understanding and addressing these challenges will pave the way for enhanced cross-media communication and exploration.

cs.NI↗

arXiv2023

Location-based Physical Layer Authentication in Underwater Acoustic Communication Networks

Research in underwater communication is rapidly becoming attractive due to its various modern applications. An efficient mechanism to secure such communication is via physical layer security. In this paper, we propose a novel physical layer authentication (PLA) mechanism in underwater acoustic communication networks where we exploit the position/location of the transmitter nodes to achieve authentication. We perform transmitter position estimation from the received signals at reference nodes deployed at fixed positions in a predefined underwater region. We use time of arrival (ToA) estimation and derive the distribution of inherent uncertainty in the estimation. Next, we perform binary hypothesis testing on the estimated position to decide whether the transmitter node is legitimate or malicious. We then provide closed-form expressions of false alarm rate and missed detection rate resulted from binary hypothesis testing. We validate our proposal via simulation results, which demonstrate errors' behavior against the link quality, malicious node location, and receiver operating characteristic (ROC) curves. We also compare our results with the performance of previously proposed fingerprint mechanisms for PLA in underwater acoustic communication networks, for which we show a clear advantage of using the position as a fingerprint in PLA.

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arXiv2022

Hand-breathe: Non-Contact Monitoring of Breathing Abnormalities from Hand Palm

In post-covid19 world, radio frequency (RF)-based non-contact methods, e.g., software-defined radios (SDR)-based methods have emerged as promising candidates for intelligent remote sensing of human vitals, and could help in containment of contagious viruses like covid19. To this end, this work utilizes the universal software radio peripherals (USRP)-based SDRs along with classical machine learning (ML) methods to design a non-contact method to monitor different breathing abnormalities. Under our proposed method, a subject rests his/her hand on a table in between the transmit and receive antennas, while an orthogonal frequency division multiplexing (OFDM) signal passes through the hand. Subsequently, the receiver extracts the channel frequency response (basically, fine-grained wireless channel state information), and feeds it to various ML algorithms which eventually classify between different breathing abnormalities. Among all classifiers, linear SVM classifier resulted in a maximum accuracy of 88.1\%. To train the ML classifiers in a supervised manner, data was collected by doing real-time experiments on 4 subjects in a lab environment. For label generation purpose, the breathing of the subjects was classified into three classes: normal, fast, and slow breathing. Furthermore, in addition to our proposed method (where only a hand is exposed to RF signals), we also implemented and tested the state-of-the-art method (where full chest is exposed to RF radiation). The performance comparison of the two methods reveals a trade-off, i.e., the accuracy of our proposed method is slightly inferior but our method results in minimal body exposure to RF radiation, compared to the benchmark method.

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arXiv2022

Underwater and Air-Water Wireless Communication: State-of-the-art, Channel Characteristics, Security, and Open Problems

We present a first detailed survey on underwater and air-water (A-W) wireless communication networks (WCNs) that mainly focuses on the security challenges and the countermeasures proposed to date. For clarity of exposition, this survey paper is mainly divided into two parts. The first part of the paper focuses on the state-of-the-art underwater and A-W WCNs whereby we outline the benefits and drawbacks of the four promising underwater and A-W candidate technologies: radio frequency (RF), acoustic, optical and magnetic induction (MI), along with their channel characteristics. To this end, we also describe the indirect (relay-aided) and direct mechanisms for the A-W WCNs along with their channel characteristics. This sets the stage for the second part of the paper whereby we provide a thorough comparative discussion of a vast set of works that have reported the security breaches (as well as viable countermeasures) for many diverse configurations of the underwater and A-W WCNs. Specifically, we provide a detailed literature review of the various kinds of active and passive attacks which hamper the confidentiality, integrity, authentication and availability of both underwater and A-W WCNs. Finally, we highlight some research gaps in the open literature and identify security related some open problems for the future work.

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arXiv2022

Countering Active Attacks on RAFT-based IoT Blockchain Networks

This paper considers an Internet of Thing (IoT) blockchain network consisting of a leader node and various follower nodes which together implement the RAFT consensus protocol to verify a blockchain transaction, as requested by a blockchain client. Further, two kinds of active attacks, i.e., jamming and impersonation, are considered on the IoT blockchain network due to the presence of multiple {\it active} malicious nodes in the close vicinity. When the IoT network is under the jamming attack, we utilize the stochastic geometry tool to derive the closed-form expressions for the coverage probabilities for both uplink and downlink IoT transmissions. On the other hand, when the IoT network is under the impersonation attack, we propose a novel method that enables a receive IoT node to exploit the pathloss of a transmit IoT node as its fingerprint to implement a binary hypothesis test for transmit node identification. To this end, we also provide the closed-form expressions for the probabilities of false alarm, missed detection and miss-classification. Finally, we present detailed simulation results that indicate the following: i) the coverage probability improves as the jammers' locations move away from the IoT network, ii) the three error probabilities decrease as a function of the link quality.

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arXiv2021

On the Effective Capacity of IRS-assisted wireless communication

We consider futuristic, intelligent reflecting surfaces (IRS)-aided communication between a base station (BS) and a user equipment (UE) for two distinct scenarios: a single-input, single-output (SISO) system whereby the BS has a single antenna, and a multi-input, single-output (MISO) system whereby the BS has multiple antennas. For the considered IRS-assisted downlink, we compute the effective capacity (EC), which is a quantitative measure of the statistical quality-of-service (QoS) offered by a communication system experiencing random fading. For our analysis, we consider the two widely-known assumptions on channel state information (CSI) -- i.e., perfect CSI and no CSI, at the BS. Thereafter, we first derive the distribution of the signal-to-noise ratio (SNR) for both SISO and MISO scenarios, and subsequently derive closed-form expressions for the EC under perfect CSI and no CSI cases, for both SISO and MISO scenarios. Furthermore, for the SISO and MISO systems with no CSI, it turns out that the EC could be maximized further by searching for an optimal transmission rate $r^*$, which is computed by exploiting the iterative gradient-descent method. We provide extensive simulation results which investigate the impact of the various system parameters, e.g., QoS exponent, power budget, number of transmit antennas at the BS, number of reflective elements at the IRS etc., on the EC of the system.

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arXiv2020

Preventing Identity Attacks in RFID Backscatter Communication Systems: A Physical-Layer Approach

This work considers identity attack on a radio-frequency identification (RFID)-based backscatter communication system. Specifically, we consider a single-reader, single-tag RFID system whereby the reader and the tag undergo two-way signaling which enables the reader to extract the tag ID in order to authenticate the legitimate tag (L-tag). We then consider a scenario whereby a malicious tag (M-tag)---having the same ID as the L-tag programmed in its memory by a wizard---attempts to deceive the reader by pretending to be the L-tag. To this end, we counter the identity attack by exploiting the non-reciprocity of the end-to-end channel (i.e., the residual channel) between the reader and the tag as the fingerprint of the tag. The passive nature of the tag(s) (and thus, lack of any computational platform at the tag) implies that the proposed light-weight physical-layer authentication method is implemented at the reader. To be concrete, in our proposed scheme, the reader acquires the raw data via two-way (challenge-response) message exchange mechanism, does least-squares estimation to extract the fingerprint, and does binary hypothesis testing to do authentication. We also provide closed-form expressions for the two error probabilities of interest (i.e., false alarm and missed detection). Simulation results attest to the efficacy of the proposed method.

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