Mizuki Oka

Anomaly Detection Using Layered Networks Based on Eigen Co-occurrence Matrix

Anomaly detection is a promising approach to detecting intruders masquerading as valid users (called masqueraders). It creates a user profile and labels any behavior that deviates from the profile as anomalous. In anomaly detection, a challenging task is modeling a user’s dynamic behavior based on sequential data collected from computer systems. In this paper, we propose a novel method, called Eigen co-occurrence matrix (ECM), that models sequences such as UNIX commands and extracts their principal features. We applied the ECM method to a masquerade detection experiment with data from Schonlau et al. We report the results and compare them with results obtained from several conventional methods.

Scribble-a-Secret: Similarity-based password authentication using sketches

This paper presents a sketch-based password authentication system called Scribble-a-Secret as a graphical password scheme in which free-form drawings are used as a means to authenticate users. Unlike existing schemes, this approach requires no input of graphical passwords in particular sequences of strokes. Moreover, the system allows for a modicum of variation when users recreate their passwords. Our technique uses edge orientations extracted from sketch images to discern one user from another. Our experiments show that our recognition technique is robust for recognizing sketches while differentiating from others with both a false acceptance rate and false rejection rate of less than 1%.

Exploring default mode and information flow on the web.

Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called “Web”) dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called “tweets”) and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Webs dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period. Study of the information flow on Google and Twitter revealed that information is generally transferred from Twitter to Google, indicating that Twitter time series have some preceding information about Google time series. We also studied the information flow among different Twitter keywords time series by taking keywords as nodes and flow directions as edges of a network. An analysis of this network revealed that frequent keywords tend to become an information source and infrequent keywords tend to become sink for other keywords. Based on these findings, we hypothesize that frequent keywords form the Webs default mode, which becomes an information source for infrequent keywords that generally form the Webs reactive mode. We also found that the Web consists of different time resolutions with respect to TE among Twitter keywords, which will be another focal point of this paper.

Self-Organization on Social Media: Endo-Exo Bursts and Baseline Fluctuations

A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media.

Life as an emergent phenomenon: studies from a large-scale boid simulation and web data

A large group with a special structure can become the mother of emergence. We discuss this hypothesis in relation to large-scale boid simulations and web data. In the boid swarm simulations, the nucleation, organization and collapse dynamics were found to be more diverse in larger flocks than in smaller flocks. In the second analysis, large web data, consisting of shared photos with descriptive tags, tended to group together users with similar tendencies, allowing the network to develop a core–periphery structure. We show that the generation rate of novel tags and their usage frequencies are high in the higher-order cliques. In this case, novelty is not considered to arise randomly; rather, it is generated as a result of a large and structured network. We contextualize these results in terms of adjacent possible theory and as a new way to understand collective intelligence. We argue that excessive information and material flow can become a source of innovation. This article is part of the themed issue ‘Reconceptualizing the origins of life’.

Webal comes of age: A review of the first 21 years of artificial life on the web

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994—when the first WebAL work appeared—up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010–2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area.

Dynamic homeostasis in packet switching networks

In this study, we investigate the adaptation and robustness of a packet switching network (PSN), the fundamental architecture of the Internet. We claim that the adaptation introduced by a transmission control protocol congestion control mechanism is interpretable as the self-organization of complex itinerant behavior among many quasi-attracting states. To discuss this argument quantitatively, we study the adaptation of the Internet by simulating a PSN using ns-2. Our hypothesis is that the robustness and fragility of the Internet can be attributed to the inherent dynamics of the PSN feedback mechanism called the congestion window size, or cwnd. By varying the data input into the PSN system, we demonstrate the possible self-organization of attractors in cwnd temporal dynamics and discuss the adaptability and robustness of PSNs. The present study provides an example of Ashby’s Law of Requisite Variety in action.

Multiple Time Scales Observed in Spontaneously Evolved Neurons on High-density CMOS Electrode Array

Spontaneous evolution of neural cells was recorded around 4-34 days in vitro (DIV) with high-density CMOS microelectrode array, which enables detailed study of the spatiotemporal activity of cultured neurons. We used the CMOS array to characterize 1) the evolution of activation patterns of each putative neurons, 2) the developmental change in cell-cell interactions, and finally, 3) emergence of multiple timescales for neurons to exchange information with each other. The results revealed not only the topology of the physical connectivity of the neurons but also the functional connectivity of the neurons within different time scales. We finally argued the relationship of the results with “functional networks”, which interact with each other to support multiple cognitive functions in the mature human brain.

Characterizing Autonomy in the Web via Transfer Entropy Network

Using the idea of transfer entropy (TE), we study autonomy and information flow on the Web and the newly defined TE network. The Web shows rich and complex autonomous network dynamics. Social network services (e.g., Twitter or Facebook) are now becoming a major source of Web dynamics in addition to the Web search services (e.g., Google). It is widely accepted that Twitter messages (called ”tweets”) and Google search queries react strongly to significant social movements and accidents, which are often characterized by bursting patterns in the time sequences. We call this the reactive mode of the Web. On the other hand, the Web dynamics, without the significant social events, seem to have an intrinsic rich dynamics, which we call the default mode of the Web. In this paper, we study the default mode of the Web system, which we characterize via a TE network. The amount of information flow transferred between different sequences of Google queries as well as Twitter keyword frequencies is investigated and we compute a TE network among Twitter

A Sensorimotor Signature of the Transition to Conscious Social Perception: Co-regulation of Active and Passive Touch

It is not yet well understood how we become conscious of the presence of other people as being other subjects in their own right. Developmental and phenomenological approaches are converging on a relational hypothesis: my perception of a “you” is primarily constituted by another subject’s attention being directed toward “me.” This is particularly the case when my body is being physically explored in an intentional manner. We set out to characterize the sensorimotor signature of the transition to being aware of the other by re-analyzing time series of embodied interactions between pairs of adults (recorded during a “perceptual crossing” experiment). Measures of turn-taking and movement synchrony were used to quantify social coordination, and transfer entropy was used to quantify direction of influence. We found that the transition leading to one’s conscious perception of the other’s presence was indeed characterized by a significant increase in one’s passive reception of the other’s tactile stimulations. Unexpectedly, one’s clear experience of such passive touch was consistently followed by a switch to active touching of the other, while the other correspondingly became more passive, which suggests that this intersubjective experience was reciprocally co-regulated by both participants.