Related papers: SRSS: A New Chaos-Based Single-Round Single S-Box …
Steganography is the practice of encoding secret information into innocuous content in such a manner that an adversarial third party would not realize that there is hidden meaning. While this problem has classically been studied in security…
We propose SANSCrypt, a novel sequential logic encryption scheme to protect integrated circuits against reverse engineering. Previous sequential encryption methods focus on modifying the circuit state machine such that the correct…
Localization is a computer vision task by which the position and orientation of a camera is determined from an image and environmental map. We propose a method for performing localization in a privacy preserving manner supporting two…
The increase in data traffic on the internet has significantly increased the relevance of data and image encryption. Among the techniques most used in cryptography, chaotic systems have received great attention due to their easy…
This paper proposes a new block scrambling encryption scheme that enhances the security of encryption-then-compression (EtC) systems for JPEG images, which are used, for example, to securely transmit images through an untrusted channel…
We introduce the Stochastic Correlated Obstacle Scene (SCOS) problem, a navigation setting with spatially correlated obstacles of uncertain blockage status, realistically constrained sensors that provide noisy readings and costly…
A new grayscale-based block scrambling image encryption scheme is presented to enhance the security of Encryption-then-Compression (EtC) systems, which are used to securely transmit images through an untrusted channel provider. The proposed…
This paper presents a novel approach to range-based cooperative localization for robot swarms in GPS-denied environments, addressing the limitations of current methods in noisy and sparse settings. We propose a robust multi-layered…
Multimodal hearing aids (HAs) aim to deliver more intelligible audio in noisy environments by contextually sensing and processing data in the form of not only audio but also visual information (e.g. lip reading). Machine learning techniques…
Image harmonization aims to improve the quality of image compositing by matching the "appearance" (\eg, color tone, brightness and contrast) between foreground and background images. However, collecting large-scale annotated datasets for…
Sparse Representation (SR) techniques encode the test samples into a sparse linear combination of all training samples and then classify the test samples into the class with the minimum residual. The classification of SR techniques depends…
Sparse subspace clustering (SSC) is one of the current state-of-the-art methods for partitioning data points into the union of subspaces, with strong theoretical guarantees. However, it is not practical for large data sets as it requires…
Self-supervised learning (SSL) methods targeting scene images have seen a rapid growth recently, and they mostly rely on either a dedicated dense matching mechanism or a costly unsupervised object discovery module. This paper shows that…
Steganography is the process of embedding secret information discreetly within a carrier, ensuring secure exchange of confidential data. The Adaptive Pixel Value Differencing (APVD) steganography method, while effective, encounters certain…
The study of sending and receiving secret messages is called cryptography. Generally, senders and receivers are unaware about the process of encryption and decryption. Hence, encryption plays an important role in data communication and data…
Single-pixel cameras based on the concepts of compressed sensing (CS) leverage the inherent structure of images to retrieve them with far fewer measurements and operate efficiently over a significantly broader spectral range than…
Cloud computing is emerging as a revolutionary computing paradigm, while security and privacy become major concerns in the cloud scenario. For which Searchable Encryption (SE) technology is proposed to support efficient retrieval of…
By combining the one-way coupled chaotic map lattice system with a bit-reverse operation, we construct a new cryptosystem which is extremely sensitive to the system parameters even for low-dimensional systems. The security of this new…
We present a method for detecting objects in images using a single deep neural network. Our approach, named SSD, discretizes the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature…
The security of learnable image encryption schemes for image classification using deep neural networks against several attacks has been discussed. On the other hand, block scrambling image encryption using the vision transformer has been…