PassGAN: A Deep Learning Approach for Password Guessing

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Accurately estimating model performance poses a significant challenge, particularly in scenarios where the source and target domains follow different data distributions. Most existing performance prediction methods heavily rely on the source data in their ...

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a geant-based simulation of the detect ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Since the advent of internet and mass communication, two public-key cryptographic algorithms have shared the monopoly of data encryption and authentication: Diffie-Hellman and RSA. However, in the last few years, progress made in quantum physics -- and mo ...

Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Post-quantum cryptography is a branch of cryptography which deals with cryptographic algorithms whose hardness assumptions are not based on problems known to be solvable by a quantum computer, such as the RSA problem, factoring or discrete logarithms. This ...

Current cryptographic solutions will become obsolete with the arrival of large-scale universal quantum computers. As a result, the National Institute of Standards and Technology supervises a post-quantum standardization process which involves evaluating ca ...

Side-channel CPU disassembly is a side-channel attack that allows an adversary to recover instructions executed by a processor. Not only does such an attack compromise code confidentiality, it can also reveal critical information on the system’s internals. ...

Orthogonal frequency-division multiplexing (OFDM) is widely used to mitigate inter-symbol interference (ISI) from multipath fading. However, the open nature of wireless OFDM systems makes them vulnerable to jamming attacks. In this context, pilot jamming i ...

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

Billions of people now have conversations daily over the Internet. A large portion of this communication takes place via secure messaging protocols that offer "end-to-end encryption'" guarantees and resilience to compromise like the widely-used Double Ratc ...

Public knowledge about the structure of a cryptographic system is a standard assumption in the literature and algorithms are expected to guarantee security in a setting where only the encryption key is kept secret. Nevertheless, undisclosed proprietary cry ...

Vision Transformers (ViTs) demonstrate remarkable performance in image classification through visual-token interaction learning, particularly when equipped with local information via region attention or convolutions. Although such architectures improve the ...

Progress in computing capabilities has enhanced science in many ways. In recent years, various branches of machine learning have been the key facilitators in forging new paths, ranging from categorizing big data to instrumental control, from materials desi ...

Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry. This paper studies distributed learnin ...

Deep learning algorithms are responsible for a technological revolution in a variety oftasks including image recognition or Go playing. Yet, why they work is not understood.Ultimately, they manage to classify data lying in high dimension – a feat generical ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Touch is commonly used to mediate human-machine interactions, notably in the setting of Digital Musical Instruments (DMIs), where touch screens are prevalent. The lack of rich haptic feedback has an impact on the richness and quality of the interaction. Pi ...

We present the design and implementation of SafetyPin, a system for encrypted mobile-device backups. Like existing cloud-based mobile-backup systems, including those of Apple and Google, SafetyPin requires users to remember only a short PIN and defends aga ...

PassGAN: A Deep Learning Approach for Password Guessing

Chat with Graph Search

Source-Free Domain-Invariant Performance Prediction

Reweighting simulated events using machine-learning techniques in the CMS experiment

Deep-Learning Reconstruction for 7T MP2RAGE and SPACE MRI: Improving Image Quality at High Acceleration Factors

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Secure and Efficient Cryptographic Algorithms in a Quantum World

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Attacks on some post-quantum cryptographic protocols: The case of the Legendre PRF and SIKE

Side-channel analysis of isogeny-based key encapsulation mechanisms and hash-based digital signatures

A Deep-Learning Approach to Side-Channel Based CPU Disassembly at Design Time

Adversarial Training for Jamming-Robust Channel Estimation in OFDM Systems

Deep Learning Approaches for Auditory Perception in Robotics

On the Theory and Practice of Modern Secure Messaging

Complete Practical Side-Channel-Assisted Reverse Engineering of AES-Like Ciphers

AdaNCA: Neural Cellular Automata as Adaptors for More Robust Vision Transformer

The role of convolutional neural networks in scanning probe microscopy: a review

One-Bit Byzantine-Tolerant Distributed Learning via Over-The-Air Computation

Landscape and training regimes in deep learning

Predicting the long-term collective behaviour of fish pairs with deep learning

Reinforcement Learning and Hardware in the Loop for Localized Vibrotactile Feedback in Haptic Surfaces

SafetyPin: Encrypted Backups with Human-Memorable Secrets