Cyber Creative Generative Adversarial Network for Novel Malicious Packets

Machine learning (ML) requires both quantity and variety of examples in order to learn generalizable patterns. In cybersecurity, labeling network packets is a tedious and difficult task. This leads to insufficient labeled datasets of network packets for training ML-based Network Intrusion Detection Systems (NIDS) to detect malicious intrusions. Furthermore, benign network traffic and malicious cyber attacks are always evolving and changing, meaning that the existing datasets quickly become obsolete. We investigate generative ML modeling for network packet synthetic data generation/augmentation to improve NIDS detection of novel, but similar, cyber attacks by generating well-labeled synthetic network traffic. We develop a Cyber Creative Generative Adversarial Network (CCGAN), inspired by previous generative modeling to create new art styles from existing art images, trained on existing NIDS datasets in order to generate new synthetic network packets. The goal is to create network packet payloads that appear malicious but from different distributions than the original cyber attack classes. We use these new synthetic malicious payloads to augment the training of a ML-based NIDS to evaluate whether it is better at correctly identifying whole classes of real malicious packet payloads that were held-out during classifier training. Results show that data augmentation from CCGAN can increase a NIDS baseline accuracy on a novel malicious class from 79% to 97% with a minimal degradation in accuracy on benign classes (98.9% to 98.7%)

Socialist facades parametrized

Abstract. In my explorative diploma thesis “Socialist Facades Parametrized” I study and try to understand the facades of buildings from 27 countries of the Eastern Bloc built between the years 1954 and 1991.Through analyzing, understanding and parameterizing these facades my aim is to present a logical continuation of the development of architectural language which ceased to exist by the start of the 1990s. This thesis is not meant to propagate any kind of post-communist nostalgia or support any political movement, its goal is to recognize interesting approaches to façade ornamentality and possible uses in the contemporary context. The thesis consists of two equally important parts: the analytical part and the creative part. The first, analytical part of the thesis is based on the collection, selection, and further sorting of those facades into categories based on geometric similarity. This geometric similarity is then used for exploring parametric possibilities of such facades. The first goal of this thesis is to both learn more about Eastern Bloc’s so-called Socialist Modernism facades (1954–1991) and to change the perception of socialist architecture as just a group of grey boxes by presenting interesting examples. Also, there is my wish to learn more about the visual and general identity and cultural space of the Eastern Bloc. The second, creative part of the thesis is about the exploration of parametric modeling to create facades inspired by Socialist Modernism facades using parametric tools and their flexibility. An important task in this part is to learn and understand parametric modeling tools and the creation of a parametric generator of facades inspired by Socialist Modernism. Another goal is to explore the facade generator in the everyday practice of building design to experiment quicker. This step goes together with a general understanding of this emerging phenomenon and its use in architecture. In addition to enriching and developing my current architectural language with historical elements, I hope that my diploma thesis will be a source of inspiration to colleagues too

6 Seconds of Sound and Vision: Creativity in Micro-Videos

The notion of creativity, as opposed to related concepts such as beauty or interestingness, has not been studied from the perspective of automatic analysis of multimedia content. Meanwhile, short online videos shared on social media platforms, or micro-videos, have arisen as a new medium for creative expression. In this paper we study creative micro-videos in an effort to understand the features that make a video creative, and to address the problem of automatic detection of creative content. Defining creative videos as those that are novel and have aesthetic value, we conduct a crowdsourcing experiment to create a dataset of over 3,800 micro-videos labelled as creative and non-creative. We propose a set of computational features that we map to the components of our definition of creativity, and conduct an analysis to determine which of these features correlate most with creative video. Finally, we evaluate a supervised approach to automatically detect creative video, with promising results, showing that it is necessary to model both aesthetic value and novelty to achieve optimal classification accuracy.Comment: 8 pages, 1 figures, conference IEEE CVPR 201

A Case Study of Applied Co-Design in 3D Virtual Space for Facilitating Bicycle Use on Light Rail Systems

Cycling is highly recommended by experts concerned with environmental and public health. Cycling does not produce CO2 emissions, can be economical, and can improve physical fitness. However, the barriers to cycling remain significant to many. Combined with a light rail system the bicycle offers a compelling alternative to automobiles; yet, bicycles are denied access on certain rail systems because they can take too much space away from pedestrians who share the light rail interior. To help solve this problem, Co-Design in 3D virtual space is proposed as an effective means of creating an innovative design solution. The digital questionnaires and virtual 3D modeling research/design method used in this study gives the participant the ability to offer insights and express ideas through digital means and in 3D virtual space. This method, Co-Design in Virtual Space (CoDeViS), was developed by the author. CoDeViS methods are an outgrowth of physical co-design methods such as 2D collages and 3D Velcro modeling, developed by those featured in The International Journal of CoCreation in Design and the Arts. Physical 3D methods have been widely accepted in the new product development industry as effective ways to involve people outside a design team in the research and design process. CoDeViS methods offer promise to those seeking to make the principles of co-design available to larger groups of people in discrete locations around the world at lower cost. Historical developments, current technology, and the abilities of everyday people make CoDeViS possible.</p

Overcoming the Newtonian Paradigm: The Unfinished Project of Theoretical Biology from a Schellingian Perspective

Defending Robert Rosen’s claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling’s demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive tradition of anti-reductionist biomathematics. It is shown that the mathematicoephysico echemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this antireductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics

Preference Models for Creative Artifacts and Systems

Abstract Although there is vigorous debate around definitions of creativity, there is general consensus that creativity i) has multiple facets, and ii) inherently involves a subjective value judgment by an evaluator. In this paper, we present evaluation of creative artifacts and computational creativity systems through a multiattribute preference modeling lens. Specifically, we introduce the use of multiattribute value functions for creativity evaluation and argue that there are significant benefits to explicitly representing creativity judgments as subjective preferences using formal mathematical models. Various implications are illustrated with the help of examples from and inspired by the creativity literature

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Computational Capacity and Energy Consumption of Complex Resistive Switch Networks

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Assembled into random networks, such resistive switches produce emerging behaviors far more complex than that of individual devices. This was previously demonstrated in simulations that exploit information processing within these random networks to solve tasks that require nonlinear computation as well as memory. Physical assemblies of such networks manifest complex spatial structures and basic processing capabilities often related to biologically-inspired computing. We model and simulate random resistive switch networks and analyze their computational capacities. We provide a detailed discussion of the relevant design parameters and establish the link to the physical assemblies by relating the modeling parameters to physical parameters. More globally connected networks and an increased network switching activity are means to increase the computational capacity linearly at the expense of exponentially growing energy consumption. We discuss a new modular approach that exhibits higher computational capacities and energy consumption growing linearly with the number of networks used. The results show how to optimize the trade-off between computational capacity and energy efficiency and are relevant for the design and fabrication of novel computing architectures that harness random assemblies of emerging nanodevices