44 research outputs found
Towards the Development of a Cyber Analysis & Advisement Tool (CAAT) for Mitigating De-Anonymization Attacks
We are seeing a rise in the number of Anonymous Social Networks (ASN) that claim to provide a sense of user anonymity. However, what many users of ASNs do not know that a person can be identified by their writing style.
In this paper, we provide an overview of a number of author concealment techniques, their impact on the semantic meaning of an author\u27s original text, and introduce AuthorCAAT, an application for mitigating de-anonymization attacks. Our results show that iterative paraphrasing performs the best in terms of author concealment and performs well with respect to Latent Semantic Analysis
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing
In Machine Learning, White Box Adversarial Attacks rely on knowing underlying
knowledge about the model attributes. This works focuses on discovering to
distrinct pieces of model information: the underlying architecture and primary
training dataset. With the process in this paper, a structured set of input
probes and the output of the model become the training data for a deep
classifier. Two subdomains in Machine Learning are explored: image based
classifiers and text transformers with GPT-2. With image classification, the
focus is on exploring commonly deployed architectures and datasets available in
popular public libraries. Using a single transformer architecture with multiple
levels of parameters, text generation is explored by fine tuning off different
datasets. Each dataset explored in image and text are distinguishable from one
another. Diversity in text transformer outputs implies further research is
needed to successfully classify architecture attribution in text domain.Comment: 4 Pages, 3 Figure, IEEE Format, Ai4i 202
Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation
Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed