Signal Processing and Learning for Near-Field 6G SystemsContact person
MAROUAN MIZMIZIEmail:
marouan.mizmizi@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
As 6G networks evolve to use higher frequencies and larger MIMO arrays, communication will increasingly occur in the near-field, unlike today’s far-field systems. This shift has significant implications for how channels are modeled, estimated, and how communication systems are designed. Near-field communication introduces unique challenges, such as the need for new channel models that account for spatial variations over short distances and more complex, yet critical, channel estimation techniques. Precoding and equalization strategies must also be reimagined to address the non-uniform distribution of signals and the potential for increased interference in dense network environments.
This thesis will explore these challenges by developing advanced signal processing techniques tailored for near-field conditions in 6G networks. It will focus on improving channel modeling, estimation, precoding, and equalization for high-frequency, dense scenarios. Additionally, the research will investigate the use of machine learning to enhance these techniques, offering more adaptive and robust solutions. The goal is to make a significant contribution to 6G technology by addressing the critical challenges of near-field communication with both traditional and machine learning-based approaches.
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Exploring Security Vulnerabilities in the OpenTitan Framework: A Comprehensive Analysis and Testing ApproachContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Elia LazzeriWeb page:
https://cassano.faculty.polimi.it/Description
Description:
This work focuses on an in-depth security evaluation of the OpenTitan framework which is an open-source silicon root of trust designed to reinforce trusted computing on hardware-level systems. The research will begin with a thorough review of OpenTitan’s architecture, security features, and implementation details to identify potential weakness points. Building on this understanding, the project will employ systematic testing methods, including static code analysis, fuzzing, and hardware penetration testing, to uncover vulnerabilities and assess the impact of any discovered flaws on system integrity.
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Analysis of NASA's Core Flight System (cFS) Framework: An Application Case Study for Electro-Optical Payload Management on CubeSatsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
in collaboration with TDS-Space and the European Space AgencyWeb page:
https://cassano.faculty.polimi.it/Description
Description:
The Core Flight System is an advanced software architecture based on the mission operation services of the CCSDS (Consultative Committee for Space Data Systems). Developed by NASA, this software is designed to support space operations and system integration for various aerospace missions, thanks to its modularity that allows updates similar to smartphone applications. NASA's cFS is a software framework intended to support space operations and system integration across diverse aerospace missions. Thesis/Internship Objectives: The thesis and internship activities are designed to investigate the effectiveness of NASA's Core Flight System (cFS) in managing electro-optical payloads on CubeSat platforms. This evaluation specifically focuses on the performance of the cFS when operational on a representative target computing platform for data handling and processing, developed by TSD-Space. Specifically, the focus will be on implementing a cFS application that manages image acquisition operations, integrating monitoring and control services performed through the cFS framework and the C programming language.
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Real-Time Onboard 2D Image Correlation System for Estimating and Compensating Instantaneous Focal Plane Motion: An FPGA implementationContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
in collaboration with TDS-Space and the European Space AgencyWeb page:
https://cassano.faculty.polimi.it/Description
Description:
The activities will be conducted in the framework of the FOPAC project, led by TSD-Space and founded by the Italian Space Agency. The FOPAC’s goal is to develop an active motion control system for the focal plane of electro-optical payloads adopted in Earth observation applications to enhance image quality in terms of spatial resolution and Signal-to-Noise Ratio (SNR). These platforms often feature telescopes with limited focal length and aperture, and less accurate attitude control systems. FOPAC can be utilized for implementing active focal plane stabilization techniques and pixel-shifting acquisition mode. Active stabilization mitigates motion blur effects due to platform instability and enables the adoption of advanced Time Delay Integration (TDI) techniques for SNR improvements. The FOPAC project incorporates the implementation of real-time onboard 2D image correlation algorithms to estimate the instantaneous motion of the focal plane and stabilize it. This compensates for the limited attitude control performance of small platforms, which significantly impacts image quality. Focal plane stabilization, capable of compensating for platform jitter—a source of instability—allows for increased exposure times, thereby enhancing the SNR. Alternatively, with the same exposure time, it reduces motion blur, thus improving the Modulation Transfer Function (MTF). The primary activity of the candidate will be to explore and survey different approaches in 2D image correlation and motion estimation, focusing on new algorithms based on AI. The selected algorithm will be accelerated on an FPGA platform for real-time execution.
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Real-time onboard satellite image registration for Digital TDI: An FPGA ImplementationContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
In collaboration with TDS-Space and the European Space AgencyWeb page:
https://cassano.faculty.polimi.it/Description
Description:
In the field of Earth observation, the digital Time-Delay Integration (TDI) acquisition technique is crucial for enhancing the quality of satellite images. This method utilizes electro-optical payloads to capture sub-stripes or partially overlapping images. By digitally summing the signals encoded in the pixels of different sub-stripes that correspond to the same ground point, it
is possible to reduce uncorrelated noise and significantly increase signal amplitude. This process leads to a substantial improvement in the signal-to-noise ratio (SNR) and, consequently, the overall quality of the image. However, the digital TDI technique requires capturing multiple images of the same sample, thereby increasing the resources needed for data storage and transmission to ground stations. By performing digital TDI operations directly onboard the spacecraft, it is possible to drastically minimize the volume of data to be stored and maximize the efficiency of bandwidth use for downlink.
Digital TDI activity essentially includes image alignment, which is a prerequisite to ensure that the sum of signals occurs exclusively among pixels corresponding to the same ground sample. During the internship at TSD-Space, the candidate will explore various methods for digital image registration, including advanced approaches that incorporate artificial intelligence. The selected algorithm will be accelerated on an FPGA platform for real-time execution, significantly enhancing the effectiveness of the TDI process.
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Rete Ferroviaria ItalianaContact person
NICOLA LUSARDIEmail:
nicola.lusardi@polimi.itStudy course: Electronics Engineering
Other members of the research group:
Fabio Garzetti, Angelo GeraciDescription
Description:
DigiLAB collaborates with other laboratories from Politecnico di Milano and various Italian universities on research and development projects with Rete Ferroviaria Italiana (RFI) to create secure embedded systems for railway applications.
DigiLAB focuses on developing electronic boards based on FPGAs, SoCs, and next-generation processors, necessary for executing the secure code of RFI’s railway algorithms. The large volume of exchanged data requires high-speed communication interfaces (such as Ethernet and HDMI). Additionally, using SoCs is crucial, allowing the creation of embedded systems with dedicated hardware integrated directly into FPGAs.
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European XFELContact person
NICOLA LUSARDIEmail:
nicola.lusardi@polimi.itStudy course: Electronics Engineering
Other members of the research group:
Fabio Garzetti, Angelo GeraciDescription
Description:
DigiLAB, together with other laboratories from Politecnico di Milano, collaborates with European XFEL, DESY, the University of Heidelberg, the University of Bergamo, and INFN to develop the DSSC X-Ray Imager (DSSC).
https://fe.desy.de/fec/projects/photon_science/dssc_x_ray_imager/
https://www.xfel.eu/
DSSC is a specialized 1-Mpixel X-ray camera for images generated by EuXFEL. It uses a nonlinear sensor (DepFET) capable of capturing up to 8,000 frames per second. DepFET sensors are managed in groups of 4 kpixels by dedicated ASICs that digitize the acquired data.
DigiLAB’s challenge is developing the firmware for the data acquisition (DAQ) system, which must handle data flows in the tens of Gbps. Specifically, the 1-Mpixel camera is divided into four quadrants, each featuring four Spartan-6 FPGAs for managing 16×4 ASICs, and a Kintex-7 FPGA for transmitting data to EuXFEL servers.
https://ieeexplore.ieee.org/document/10210050
Currently, measurements are being taken on the second version of the DSSC.
https://ieeexplore.ieee.org/document/10657049
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Elettra Sincrotrone di TriesteContact person
NICOLA LUSARDIEmail:
nicola.lusardi@polimi.itStudy course: Electronics Engineering
Other members of the research group:
Fabio Garzetti, Angelo GeraciDescription
Description:
DigiLAB has a decade-long collaboration with the “Instrumentation & Detectors Labs” at Elettra Sincrotrone di Trieste S.C.p.A.
https://www.elettra.eu/it/index.html
As part of this collaboration, we develop the firmware required for the readout electronics of Cross Delay-Line (CDL) detectors and instrumentation for pump-and-probe time-resolved experiments.
CDL detectors are systems used in synchrotrons for 3D imaging, capable of providing each frame with spatial details at a resolution of tens of micrometers in x-y coordinates, while simultaneously offering time-of-arrival (t) information for each pixel with a precision of a few tens of picoseconds. The main challenge of these systems, besides high resolution, is minimizing dead-time (in the nanosecond range), ensuring the ability to acquire signals spaced only a few nanoseconds apart without degrading image quality.
https://ieeexplore.ieee.org/document/9855502
Pump-and-probe experiments are essential for material analysis. In synchrotrons, a laser is used as the “pump” source to excite the sample, while X-rays from the synchrotron serve as the “probe,” scanning different energy levels. The challenge is detecting the pulses emitted by the tested sample and correctly correlating them with the synchrotron and laser triggers, enabling beamline scientists to perform data analysis.
https://www.mdpi.com/1424-8220/24/16/5233
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Intrabody Communication: Exploring different technologies for Biomedical Data TransmissionContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio MagariniDescription
Description:
Intrabody communication (IBC) is a promising technique for secure and energy-efficient data transmission within the human body, with applications in biomedical devices, wearable sensors, and implantable systems. The exploration of different transmission methods, including terahertz (THz) waves, galvanic coupling, and ultrasounds, presents an opportunity to optimize performance for diverse medical and health monitoring applications. This research seeks to analyze the feasibility and efficiency of these communication techniques through a combination of simulations and experimental validation.
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UAV Trajectory Planning and Synchronization for Efficient Search and Rescue OperationsContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio Magarini, Francesco Linsalata, Davide ScazzoliDescription
Description:
This research focuses on advanced trajectory planning and synchronization techniques for Unmanned Aerial Vehicles (UAVs), commonly known as drones, in search and rescue operations. By optimizing flight paths, real-time communication, and coordinated movement, the study aims to enhance efficiency in locating and assisting individuals in distress. The thesis aims to integrate path optimization algorithms, obstacle avoidance mechanisms, and cooperative control strategies to ensure seamless multi-drone collaboration, even in complex and unpredictable environments. The findings will contribute to improving autonomous drone operations for emergency response and disaster management.
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Development of a Multi-Core RISC-V SoC for Harsh EnvironmentsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Dr. Luigi Dilillo (University of Montpellier, France)Web page:
https://cassano.faculty.polimi.it/Description
Description:
Radiation-induced effects, such as Single Event Upsets (SEU) and Total Ionizing Dose (TID), pose significant challenges for electronic systems operating in space and other harsh environments. This internship will focus on extending an existing RISC-V-based System-on-Chip to a multi-core architecture in order to enhance performance and fault tolerance against radiation effects. The work involves modifying the existing VHDL design to support multiple cores, implementing inter-core communication and synchronization, and integrating fault-mitigation techniques. Candidates should have experience in VHDL, processor architecture, C programming, and microcontrollers.
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Exploiting GPU Microarchitectures for Novel Hardware Attacks: Investigating Memory Leaks and Arbitrary Code Execution Without Physical AccessContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Elia LazzeriWeb page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis will investigate how modern Graphics Processing Units (GPUs) can be exploited to reveal sensitive data or run unauthorized code, all without requiring physical access or elevated permissions. By studying GPU-specific features, such as caching techniques, memory management, and parallel processing pipelines, the project aims to uncover new attack vectors and demonstrate them through proof-of-concept exploits. Finally, the research will suggest countermeasures and improved design strategies to enhance GPU security against these emerging threats.
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Exploiting Software Obfuscation to prevent Transient Execution Attacks in RISC-V processorsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Other members of the research group:
Elia LazzeriWeb page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis focuses on the design and development of software obfuscation engine to enhance the security of computing systems. The idea is to modify the control and data flows of a program in order to make Transient Execution Attacks like Spectre and Meltdown more difficult to be executed or even impossible.
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Real-Time Heart Signal Anomaly Detection and Prevention Using Radar TechnologyContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Francesco LinsalataDescription
Description:
This thesis focuses on developing algorithms to detect anomalies in heartbeat signals captured by radar, with an emphasis on decoupling cardiac signals from respiration to enhance detection accuracy. The research incorporates Integrated Sensing and Communication (ISAC), enabling radar systems to seamlessly combine physiological monitoring with communication functionality.
The student will design and implement methods for detecting or preventing heart rate anomalies, such as arrhythmias, and validate their performance through measurement campaigns using real radar data. The ultimate goal is to deliver a low-complexity, real-time solution for healthcare applications and preventative monitoring.
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Semantic Signal Reconstruction for Restoring Nerve Signal PropagationContact person
SILVIA MURAEmail:
silvia.mura@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Maurizio MagariniDescription
Description:
This thesis explores a novel approach to restoring nerve function through semantic signal reconstruction, designed to act as a relay system for damaged nerves. By focusing on the "semantic meaning" of neural signals—the critical information necessary for physiological responses—this method bypasses the need to replicate the entire signal, enabling efficient and targeted signal propagation across injured sections. The work emphasizes low-complexity algorithms and real-time processing, making the approach suitable for implantable devices like cuff electrodes. These devices capture, interpret, and regenerate nerve signals, ensuring seamless communication despite nerve damage.
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5G-enabled passive radar for detecting unauthorized dronesContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Automation Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Davide ScazzoliDescription
Description:
The goal of the proposed master's thesis is to investigate the detection of unauthorized drones using a passive bistatic radar (PBR) system that leverages a 5G base station as the transmitter. This method utilizes existing infrastructure, making it a cost-effective solution for drone surveillance. The detection process involves modeling the communication environment between the 5G base station and the drone, and analyzing the signals reflected from the drone. A crucial aspect of the study is calculating the Radar Cross Section (RCS) to measure how the drone scatters radar signals. By combining signal analysis with RCS calculations, the system can detect small, agile drones in complex environments. The thesis evaluates the system's performance with a specific drone model under various conditions, demonstrating that integrating PBR with 5G networks can effectively detect and track unauthorized drones, enhancing security in critical areas.
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Cellular infrastructure for weather monitoringContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
The thesis aims at studying the potential of the cellular infrastructure for the retrieval and monitoring of rain.
The goal of the work is to investigate the potential of the cellular network to be use for weather forecasting, towards greener environments.
The student will learn how to model and process the cellular signals to estimate the rain precipitation rate, and validate the simulations on experimental data acquired with a 5G cellular base station.
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LEO satellites for communication and environment monitoringContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Francesco LinsalataDescription
Description:
Low Earth orbit (LEO) satellites, e.g., Starlink, will be a keystone in future 6G non-terrestrial wireless networks. In addition to the communication functionality, LEO fleets can also serve for accurate Earth monitoring, with applications ranging from infrastucture monitoring, public security, surveillance and environmental reconstruction.
The thesis consists of exploring the use of LEO satellites to jointly ensure broadcast connectivity while obtain an accurate environment mapping.
The work will involve practical activities within the framework of the PNRR project "RESTART".
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AI for Cooperative Perception in Vehicular Radar NetworksContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Automation Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Description
Description:
The road towards autonomous driving expects vehicles will be equipped with more and more heterogeneous sensors (cameras, lidars, radars, sonars) to perceive the surroundings. Cameras and lidars are the golden standard for autonomous driving, providing high-resolution representations of the environment, but they are sensitive to illumination levels and weather conditions (fog, rain,etc).
Radars, instead, are robust to adverse weather conditions, but are typically characterized by low spatial resolution in the description of the environment and they are currently used for limited purpose (emergency braking).
To improve the reliability of the perception of the environment, future autonomous vehicles are expected to mutually cooperate, exchanging local measurements and features to augment perception.
The thesis aims at using artificial intelligence for cooperative perception based on radars. In particular, the goal of the thesis is to investigate novel AI architectures for aligning, synchronizing and fusing radar images generated at the single vehicles. The proposed thesis can be specialized to generic distributed radar networks, e.g., made of drones.
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Integrated sensing and communication for future 6G wireless systems in the upper mid-bandContact person
DARIO TAGLIAFERRIEmail:
dario.tagliaferri@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Marco MezzavillaWeb page:
Pi-Radio website: https://www.pi-rad.io/homeDescription
Description:
Integrated Sensing and Communication (ISAC) systems combine wireless communication and radar sensing capabilities within the same infrastructure. These systems leverage shared hardware, spectrum, and signal processing techniques to perform tasks like data transmission and environmental sensing simultaneously. ISAC enables applications such as autonomous driving, smart cities, publoc safety and surveillance. It is acquainted that the next generation (6G) of wireless systems will use the so-called upper mid-band (6-24 GHz), currently not used for communication systems. The upper mid-band that offer large bandwidth over a wide range of frequencies, opening the striking possibility of centimeter-level environment sensing and unprecedented .
The thesis aims at addressing the innovative design of an ISAC systems in the future 6G frequencies. The student can choose to address the 6G ISAC from the methodological perspective , finding new ways to integrate communication and sensing over multiple disaggregated bandwidths, or developing custom signal processing algorithms that can be validated with in-lab experimental measurements with the Pi-Radio hardware.
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DEFINIZIONE DI UN PROTOCOLLO PER PRODURRE UNA INTERFACCIA NEURALEContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Antonio CovielloDescription
Description:
La tesi si concentra sulla progettazione e la manifattura di una cuff electrode, un’interfaccia neurale da posizionare attorno a un nervo periferico per il campionamento del segnale nervoso. Lo studente sarà coinvolto in attività pratiche di laboratorio, con focus su biomateriali avanzati, tecniche di produzione, parziale progettazione circuitale e aspetti normativi. L’obiettivo è sviluppare un protocollo e un metodo di produzione che garantiscano un campionamento stabile ed efficace del segnale nel tempo.
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REALIZZAZIONE HARDWARE DI UN CHIP IMPIANTABILE PER APPLICAZIONI MEDICALIContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Biomedical Engineering, Electrical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Antonio CovielloDescription
Description:
La tesi si concentra sulla progettazione e sviluppo hardware di un chip impiantabile, con focus sull’acquisizione e trasferimento dei segnali biomedicali. Lo studente sarà coinvolto nella scelta, configurazione e integrazione delle componenti elettroniche per la realizzazione del dispositivo. L’ottimizzazione si orienterà verso applicazioni mediche future sull’uomo, puntando a miniaturizzazione del segnale medicale, efficienza energetica e affidabilità a lungo termine.
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Design of an eye tracking device exploiting mmWaves radarContact person
MAURIZIO MAGARINIEmail:
maurizio.magarini@polimi.itStudy course: Biomedical Engineering, Electrical Engineering, Electronics Engineering, Telecommunications Engineering
Other members of the research group:
Davide ScazzoliDescription
Description:
Eye-tracking capabilities have applications across a wide range of fields, including entertainment, medicine, and security. This thesis proposes the development of novel algorithms and devices that exploit mmWave radars for visual gaze analysis. The candidate will focus on both the practical aspects and the more abstract algorithmic components of the problem. The work includes an experimental phase involving the design of PCBs using commercial sensors to validate the developed algorithms. Additional extensions of this thesis will explore integrated sensing and communication using the same device.
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Predictive Smart Irrigation Systems for Optimizing Plant Health Using Electrophysiological and Environmental Sensors with Deep LearningContact person
IMEN BEKKARIEmail:
imen.bekkari@polimi.itStudy course: Automation Engineering, Biomedical Engineering, Electrical Engineering, Electronics Engineering, Computer Science and Engineering, Telecommunications Engineering
Other members of the research group:
Imen BekkariDescription
Description:
This thesis aims to develop a predictive smart irrigation system by integrating electrophysiological sensors, electronic noses, and environmental sensors to monitor and analyze plant health. The model will optimize irrigation practices through neural networks to enhance water efficiency and promote sustainable agriculture in controlled and natural environments.
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Development of Novel Transient Execution Attacks (TEAs): Exploiting Microarchitectural VulnerabilitiesContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis investigates the development of new transient execution attacks (TEAs) that exploit microarchitectural vulnerabilities in modern processors. The research will focus on identifying weaknesses in the execution pipeline, speculative execution mechanisms, and related hardware features, demonstrating how these can be leveraged to bypass traditional security measures. Additionally, the thesis will aim to propose countermeasures and mitigations to defend against these emerging threats, enhancing the security of future processor architectures.
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Development of Novel Trusted Execution Environments (TEEs)Contact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis focuses on the design and development of new Trusted Execution Environments (TEEs) to enhance the security of computing systems. The research will explore innovative TEE architectures that provide improved protection for sensitive data and operations, particularly in embedded systems, ensuring that security is maintained even in the presence of malicious attacks (Transient Execution Attacks like Spectre and Meltdown, for example) or software vulnerabilities.
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Design of Integrated GPU Architectures for RISC-V System-on-Chip (SoC) PlatformsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis explores the development of new integrated GPU architectures within RISC-V SoC platforms. By designing GPU modules that are seamlessly integrated with the RISC-V architecture, the research will focus on improving graphical processing efficiency and enabling more powerful and energy-efficient SoC solutions for diverse applications.
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Analysis and Improvement of RISC-V Memory Models: Performance Limitations and BottlenecksContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis will conduct a comprehensive study of the RISC-V memory models, identifying potential performance limitations and bottlenecks. The research will aim to propose improvements that can enhance memory management, consistency, and overall system performance, with a focus on scalability and reliability in complex computing environments.
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Development of Machine Learning for Real-Time Error Detection and Attack Prevention in RISC-V Processors Based on System MeasurementsContact person
LUCA CASSANOEmail:
luca.cassano@polimi.itStudy course: Electronics Engineering, Computer Science and Engineering
Web page:
https://cassano.faculty.polimi.it/Description
Description:
This thesis focuses on developing a machine learning (ML) system for detecting errors and potential attacks in real-time by analyzing various system measurements, including microarchitectural data. The research will explore which system metrics are most effective for accurate detection and how the ML system can interact directly with hardware to perform error correction, reconfiguration, or deactivation in response to detected issues.
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