Browsing by Author "Kaveh, Masoud"

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APAuth: Authenticate an Access Point by Backscatter Devices
(2024-06-13) Chang, Jingdong; Li, Jiajun; Yang, Yishan; Zhang, Yifan; Kaveh, Masoud; Yan, Zheng
A4 Artikkeli konferenssijulkaisussa
Backscatter communication (BC) represents a wireless communication technology that facilitates the transmission of data by low-power devices, referred to as backscatter devices (BDs), through the modulation or reflection of pre-existing wireless signals, typically sourced from an access point (AP). The advent of the Internet of Things (IoT) has garnered significant attention and witnessed the widespread adoption of BC, primarily due to its exceptional energy- efficiency characteristics. Nevertheless, the security of BC systems faces substantial threats when deployed in practical scenarios due to their inherent openness. Specifically, wireless BDs, which directly engage with users, are susceptible to detrimental consequences in the event of interactions with counterfeit wireless APs. Owing to their non-authenticated and unconditional reflection properties, BDs are vulnerable to spoofing attacks orchestrated by malicious APs. Moreover, their limited computing capabilities make it challenging to employ intricate cryptographic algorithms. To tackle these challenges, we introduce APAuth, a lightweight authentication scheme that leverages the power value of BD to establish AP authentication. In this scheme, BDs and APs share a confidential key and engage in negotiations to determine a key generation algorithm. Subsequently, the current stored power value of BD is utilized to calculate the power value that must be delivered to BD from AP. If the computed charging power value aligns with the value determined by the key generation algorithm, the AP successfully passes the authentication of BD. We perform a thorough theoretical analysis of the security aspects inherent in our proposed scheme. We further conduct numerical simulations to validate the practical viability and desired performance of APAuth in diverse real-world scenarios.
BatAu: A Batch Authentication Scheme for Backscatter Devices in a Smart Home Network
(2023) Yang, Yishan; Kaveh, Masoud; Li, Jiajun; Zhang, Yifan; Yan, Zheng; Zeng, Kai
A4 Artikkeli konferenssijulkaisussa
With the maturity of the Internet of Things (IoT), many IoT applications have been popularized and promoted. As one of the IoT technology, backscatter communication (BC) has aroused research interest due to its low-cost and ultra-low power consumption characteristics. Due to their simple design and battery-less functionalities, backscatter devices (BDs) have been introduced as the main candidates for deploying in smart home networks (SHN). Although batch authentication in BC systems is crucial and efficient for SHN security, existing schemes have only focused on radio frequency identification (RFID) devices and no literature has given a general solution for BD batch authentication. In this paper, we propose a scheme named BatAu for authenticating batch BDs applied in SHN by extracting physical layer features in multiplexing signals. We conduct numerical simulations with various settings to show its desirable performance.
An efficient authentication protocol for smart grid communication based on on-chip-error-correcting physical unclonable function
(2023-12) Kaveh, Masoud; Mosavi, Mohammad Reza; Martín, Diego; Aghapour, Saeed
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Security has become a main concern for the smart grid to move from research and development to industry. Central to this security paradigm is the concept of resistance to threats, whether emanating from an active adversary seeking to disrupt operations or a passive entity covertly intercepting sensitive data. In this dynamic landscape, smart meters (SMs) stand as the sentinels at the edge of the grid, silently gathering and transmitting invaluable data. Yet, this very placement often leaves them vulnerable in unprotected areas, underscoring the paramount importance of physical security in the smart grid. It is here that Physical Unclonable Functions (PUFs) have emerged as a formidable ally. These unique constructs serve as guardians of physical security, leveraging the inherent unpredictability of manufacturing processes to create cryptographic keys. PUFs, however, are not without their own conundrums, primarily in the realm of reliability. This challenge has prevented their widespread integration into cryptographic applications. Fuzzy extractors have been considered as a solution to solve the reliability problem of PUFs, albeit at the cost of imposing significant computational burdens. To that end, we first propose an on-chip-error-correcting (OCEC) PUF that efficiently generates stable digits for the authentication process. Afterward, we introduce a lightweight authentication protocol between the SMs and neighborhood gateway (NG) based on the proposed PUF. The provable security analysis shows that not only the proposed protocol can stand secure in the Canetti–Krawczyk (CK) adversary model but also provides additional security features. Also, the performance evaluation demonstrates the significant improvement of the proposed scheme in comparison with the state-of-the-art.
EPUF: An Entropy-derived Latency-Based DRAM Physical Unclonable Function for Lightweight Authentication in Internet of Things
(2024-11-07) Najafi, Fatemeh; Kaveh, Masoud; Mosavi, Mohammad Reza; Brighente, Alessandro; Conti, Mauro
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Physical Unclonable Functions (PUFs) are hardware-based mechanisms that exploit inherent manufacturing variations to generate unique identifiers for devices. Dynamic Random Access Memory (DRAM) has emerged as a promising medium for implementing PUFs, providing a cost-effective solution without the need for additional circuitry. This makes DRAM PUFs ideal for use in resource-constrained environments such as Internet of Things (IoT) networks. However, current DRAM PUF implementations often either disrupt host system functions or produce unreliable responses due to environmental sensitivity. In this paper, we present EPUF, a novel approach to extracting random and unique features from DRAM cells to generate reliable PUF responses. We leverage bitmap images of binary DRAM values and their entropy features to enhance the robustness of our PUF. Through extensive real-world experiments, we demonstrate that EPUF is approximately 1.7 times faster than existing solutions, achieves 100% reliability, produces features with 47.79% uniqueness, and supports a substantial set of Challenge-Response Pairs (CRPs). These capabilities make EPUF a powerful tool for DRAM PUF-based authentication. Based on EPUF, we then propose a lightweight authentication protocol that not only offers superior security features but also surpasses state-of-the-art authentication schemes in terms of communication overhead and computational efficiency.
MCRO-PUF: A Novel Modified Crossover RO-PUF with an Ultra-Expanded CRP Space
(2023) Rabiei, Hassan; Kaveh, Masoud; Mosavi, Mohammad Reza; Martín, Diego
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
With the expanding use of the Internet of Things (IoT) devices and the connection of humans and devices to the Internet, the need to provide security in this field is constantly growing. The conventional cryptographic solutions need the IoT device to store secret keys in its non-volatile memory (NVM) leading the system to be vulnerable to physical attacks. In addition, they are not appropriate for IoT applications due to their complex calculations. Thus, physically unclonable functions (PUFs) have been introduced to simultaneously address these issues. PUFs are lightweight and easy-toaccess hardware security primitives which employ the unique characteristics of integrated circuits (ICs) to generate secret keys. Among all proposed PUFs, ring oscillator PUF (RO-PUF) has had amore suitable structure for hardware implementation because of its high reliability and easier providing of circuital symmetry. However, RO-PUF has not been so attractive for authentication purposes due to its limited supported challenge-response pairs (CRPs). A few efforts have been made in recent years that could successfully improve the RO-PUF CRP space, such as configurable RO-PUF (CRO-PUF). In this paper, by considerably improving the CRO-PUF structure and adding spare paths, we propose a novel strong RO-PUF structure that exponentially grows the CRP space and dramatically reduces the hardware cost. We implement our design on a simple and low-cost FPGA chip named XC6SLX9-2tqg144, stating that the proposed design can be used in IoT applications. In addition, to improve the CRP space, our design creates a suitable improvement in different security/performance terms of the generated responses, and dramatically outperforms the state-of-the-art. The average reliability, uniqueness, and uniformity of the responses generated are 99.55%, 48.49%, and 50.99%, respectively.
A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batteryless IoT Networks
(2024-12) Shoeibi, Mehrdad; Oskouei, Anita Ershadi; Kaveh, Masoud
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The rapid advancement of Internet of Things (IoT) networks has revolutionized modern connectivity by integrating many low-power devices into various applications. As IoT networks expand, the demand for energy-efficient, batteryless devices becomes increasingly critical for sustainable future networks. These devices play a pivotal role in next-generation IoT applications by reducing the dependence on conventional batteries and enabling continuous operation through energy harvesting capabilities. However, several challenges hinder the widespread adoption of batteryless IoT devices, including the limited transmission range, constrained energy resources, and low spectral efficiency in IoT receivers. To address these limitations, reconfigurable intelligent surfaces (RISs) offer a promising solution by dynamically manipulating the wireless propagation environment to enhance signal strength and improve energy harvesting capabilities. In this paper, we propose a novel deep reinforcement learning (DRL) algorithm that optimizes the phase shifts of RISs to maximize the network’s achievable rate while satisfying IoT devices’ energy harvesting constraints. Our DRL framework leverages a novel six-dimensional chimp optimization algorithm (6DChOA) to fine-tune the hyper-parameters, ensuring efficient and adaptive learning. The proposed 6DChOA-DRL algorithm optimizes RIS phase shifts to enhance the received power of IoT devices while mitigating interference from direct and RIS-cascaded links. The simulation results demonstrate that our optimized RIS design significantly improves energy harvesting and achievable data rates under various system configurations. Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.
Performance Analysis of RIS/STAR-IOS-Aided V2V NOMA/OMA Communications Over Composite Fading Channels
(2024-02-23) Ghadi, Farshad Rostami; Kaveh, Masoud; Martin, Diego
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In this article, we explore the communication performance of vehicle-to-vehicle (V2V) networks assisted by a reconfigurable intelligent surface (RIS) and a simultaneous transmitting and reflecting intelligent omni-surface (STAR-IOS) under non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes. In particular, we consider that the RIS is close to the transmitter vehicle while the STAR-IOS is near the receiver vehicles. In addition, it is assumed that the STAR-IOS exploits the energy-splitting (ES) protocol for communication and the fading channels between the RIS and STAR-IOS follow composite Fisher-Snedecor mathcal {F} distribution. Under such assumptions, we first use the central limit theorem (CLT) to derive the PDF and the CDF of equivalent channels at receiver vehicles, and then, we derive the closed-form expression of outage probability (OP) under NOMA/OMA scenarios. Additionally, by exploiting Jensen's inequality, we propose an upper bound of the ergodic capacity (EC) and subsequently develop an analytical expression of the energy efficiency (EE) for both NOMA and OMA cases. Further, our analytical results, which are double-checked with the Monte-Carlo simulation, reveal that applying RIS/STAR-RIS in V2V communications significantly enhances the communication performance of intelligent transportation systems (ITS). Besides, the results indicate that considering the NOMA scheme provides better performance in terms of the OP, EC, and EE as compared with the OMA case for the considered V2V communication system.
SecrecyPerformance Analysis of Backscatter Communications with Side Information
(2023-10-10) Kaveh, Masoud; Rostami Ghadi, Farshad; Jäntti, Riku; Yan, Zheng
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Backscatter communication (BC) systems are a promising technology for internet of things (IoT) applications that allow devices to transmit information by modulating ambient radio signals without the need for a dedicated power source. However, the security of BC systems is a critical concern due to the vulnerability of the wireless channel. This paper investigates the impact of side information (SI) on the secrecy performance of BC systems. SI mainly refers to the additional knowledge that is available to the communicating parties beyond transmitted data, which can be used to enhance reliability, efficiency, security, and quality of service in various communication systems. In particular, in this paper, by considering a non-causally known SI at the transmitter, we derive compact analytical expressions of average secrecy capacity (ASC) and secrecy outage probability (SOP) for the proposed system model to analyze how SI affects the secrecy performance of BC systems. Moreover, a Monte Carlo simulation validates the accuracy of our analytical results and reveals that considering such knowledge at the transmitter has constructive effects on the system performance and ensures reliable communication with higher rates than the conventional BC systems without SI, namely, lower SOP and higher ASC are achievable.
Secure Wireless Powered Communications Under Fisher-Snedecor F Fading Channels
(2024-05-30) Ghadi, Farshad Rostami; Kaveh, Masoud; Yan, Zheng; Jäntti, Riku
A4 Artikkeli konferenssijulkaisussa
This paper investigates the performance of wireless powered communication (WPC) systems from a physical layer security (PLS) viewpoint. With that aim, By considering the Fisher-Snedecor F distribution as the underlying fading model for all channels, we derive closed-form expressions for the average secrecy capacity (ASC) and the secrecy outage probability (SOP). The derived expressions are formulated using the bivariate Fox's If-function, providing a mathematical framework to analyze the secrecy performance of WPC systems. The accuracy of the obtained analytical results is further validated by Monte-Carlo simulation, which provides valuable insights for the design and optimization of WPC systems under Fisher-Snedecor F fading model.
A Survey on AI-Enabled Attacks and AI-Empowered Countermeasures in Physical Layer
(2024-05-30) Chang, Jingdong; Li, Zhao; Kaveh, Masoud; Zhang, Yifan; Li, Jiajun; Yan, Zheng
A4 Artikkeli konferenssijulkaisussa
As artificial intelligence (AI) continues to integrated into our daily lives, it becomes increasingly crucial to prioritize the security of these systems, particularly at the physical layer. The physical layer is the foundational level of communication systems, responsible for transmitting data over a communication medium. The advent of AI has brought about significant advancements in the field of cybersecurity, introducing new attack methodologies and empowering countermeasures at the physical layer of communication systems. This dual aspect of AI has made it a critical component in maintaining the security and integrity of these systems. However, despite many existing efforts to apply AI into physical layer security, there is still a lack of comprehensive overview of attacks and countermeasures regarding AI-based attacks and countermeasures in this domain. In this article, we provide a general survey on AI -enabled attacks and AI-empowered countermeasures in the physical layer, and analyze its performance using two sets of proposed standards: evaluation criteria for AI -enabled attacks and AI -empowered countermeasures. Through this review, we aim to identify the key challenges that require extensive investigation and propose suggestions for future research directions.
TDMBBO: a novel three-dimensional migration model of biogeography-based optimization (case study: facility planning and benchmark problems)
(2023-06) Kaveh, Mehrdad; Mesgari, Mohammad Saadi; Martín, Diego; Kaveh, Masoud
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The ability to respond quickly to emergency patients depends on the distribution of ambulance stations. Therefore, the location of these stations is an important issue in urban planning. Health center location-allocation is considered as an NP-hard problem. Due to the long computation time, exact methods will not be effective in solving these problems. On the contrary, many meta-heuristic algorithms have been introduced as promising solutions in various engineering applications. But, it is realized that adaptation of the exploration and exploitation for solving complex optimization problems are challenging tasks. To cope with these challenges, a novel three-dimensional migration model of biogeography-based optimization (TDMBBO) has been introduced to optimize the constrained linear p-median problem. In TDMBBO, nonlinear migration rates based on quadratic, cubic, sinusoidal, and hyperbolic tangent functions have been proposed. In most of the previous migration models, one function for the migration rate has been used. The main disadvantage of these models is that emigration and immigration rates follow a single mathematical function. In the proposed model, for the migration rates of each habitat, a special mathematical model is considered that can apply the appropriate migration rate. The behavior of TDMBBO has been examined on two allocation datasets, IEEE CEC benchmark problems, three random datasets, and two real-world optimization problems. To evaluate the performance of TDMBBO, 31 competitive and state-of-the-art meta-heuristics and five BBO algorithms with different migration models (previous studies) have been used. In allocation datasets, geographic information system has been used to select candidate sites. Parametric and nonparametric tests have also been used to evaluate the performance of algorithms. Overall, TDMBBO yields far better results in many aspects than the other algorithms. The TDMBBO results show a high potential for a location-allocation problems. In IEEE CEC problems, TDMBBO showed rapid convergence compared to other algorithms. The results show the TDMBBO’s superiority and this algorithm’s capability in solving real-world optimization problems. In the end, some open problems related to TDMBBO are highlighted encouraging future research in this area.