Related papers: Gameful Introduction to Cryptography for Dyslexic …

Machine learning on encrypted data has received a lot of attention thanks to recent breakthroughs in homomorphic encryption and secure multi-party computation. It allows outsourcing computation to untrusted servers without sacrificing…

Securing a secret master key is a non-trivial task, we even argue it is impossible to fully secure it, hence we must make it as difficult as possible for any powerful adversary to steal or use the key. We introduce the reader to interesting…

Federated Learning is a machine learning approach that enables the training of a deep learning model among several participants with sensitive data that wish to share their own knowledge without compromising the privacy of their data. In…

This paper analyses the feasibility of including emerging IT-topics into secondary education (K9-12). We developed a class on Blockchain for K9-12 students which delivers relevant content but is also indented to motivate them to further…

Cryptography is the study of securing information. It is the physical process that scrambles the information by rearrangement and substitution of content, so that it becomes difficult for anyone to understand. In today's world, security has…

Computer games are motivating and beneficial in learning different educational skills. Most people use their fingers, hands, and arms when using a computer game. However, for people with motor disabilities this task can be a barrier. We…

Learning in the presence of label noise is a challenging yet important task: it is crucial to design models that are robust in the presence of mislabeled datasets. In this paper, we discover that a new class of loss functions called the…

Rising advancements and ICT have changed the way of life of society, every single logical zone are exploiting innovation to get a genuine improvement. Specialists understand the advantages of utilizing genuine games as a dependable device…

Growing interest in utilizing the wireless spectrum by heterogeneous devices compels us to rethink the physical layer security to protect the transmitted waveform from an eavesdropper. We propose an end-to-end symmetric key neural…

Cryptography is an art and science of secure communication. Here the sender and receiver are guaranteed the security through encryption of their data, with the help of a common key. Both the parties should agree on this key prior to…

The increased use of digital devices and applications has led to a rise in phishing attacks. We develop a serious game to raise awareness about phishing attacks and help people avoid these threats in a risk-free learning environment. This…

Teaching assembly programming is a fundamental component of undergraduate computer science education, yet many students struggle with its abstract and low-level concepts. Existing learning tools, such as simulators and visualisers, support…

Dysgraphia is a neurodevelopmental condition in which children encounter difficulties in handwriting. Dysgraphia is not a disorder per se, but is secondary to neurodevelopmental disorders, mainly dyslexia, Developmental Coordination…

Diffraction drastically limits the bit density in optical data storage. To increase the storage density, alternative strategies involving supplementary recording dimensions and robust read-out schemes must be explored. Here, we propose to…

Despite extensive safety measures, LLMs are vulnerable to adversarial inputs, or jailbreaks, which can elicit unsafe behaviors. In this work, we introduce bijection learning, a powerful attack algorithm which automatically fuzzes LLMs for…

An unsolved challenge in distributed or federated learning is to effectively mitigate privacy risks without slowing down training or reducing accuracy. In this paper, we propose TextHide aiming at addressing this challenge for natural…

Cryptography is the science of using mathematics to encrypt and decrypt data. Cryptography enables you to store sensitive information or transmit it across insecure networks so that it cannot be read by anyone except the intended recipient.…

Recent works have suggested that In-Context Learning (ICL) operates in dual modes, i.e. task retrieval (remember learned patterns from pre-training) and task learning (inference-time ''learning'' from demonstrations). However, disentangling…

Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more…

The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relevant knowledge from previous learning experiences when…