93 research outputs found
Information processing in complex networks
No full textEerste resultaten van onderzoek van Rick Quax suggereren dat een combinatie van informatietheorie, netwerktheorie en statistische mechanica kan leiden tot een veelbelovende theorie om het gedrag van complexe netwerken te voorspellen. Er bestaat nog weinig theorie over het gedrag van dynamische eenheden die verbonden zijn in een netwerk, zoals neuronen in een breinnetwerk of genen in een gen-regulatienetwerk. Quax combineert informatietheorie, netwerktheorie, en statistische onderzoeken en mechanica om te bekijken of dit een bruikbare theorie oplevert voor het gedrag van zogeheten ‘complexe netwerken’. Complexe netwerken zijn overal, van genregulatie in een cel tot infectieverspreiding, van hersenen tot sociale media. Zelfs als het gedrag van ieder afzonderlijk gen, neuron of persoon volledig bekend is, blijft het onduidelijk hoe het netwerk zich als geheel gedraagt. Quax zet de eerste stappen om een theorie te ontwikkelen voor het gedrag van complexe netwerken
IPCS14: Information Processing in Complex Systems 24th September Lucca
No full textAll systems in nature have one thing in common: they process information. Information is registered in the state of a system and its elements, implicitly and invisibly. As elements interact, information is transferred. Indeed, bits of information about the state of one element will travel – imperfectly – to the state of the other element, forming its new state. This storage and transfer of information, possibly between levels of a multi level system, is imperfect due to randomness or noise. From this viewpoint, a system can be formalized as a collection of bits that is organized according to its rules of dynamics and its topology of interactions. Mapping out exactly how these bits of information percolate through the system could reveal new fundamental insights in how the parts orchestrate to produce the properties of the system. A theory of information processing would be capable of defining a set of universal properties of dynamical multi level complex systems, which describe and compare the dynamics of diverse complex systems ranging from social interaction to brain networks, from financial markets to biomedicine. Each possible combination of rules of dynamics and topology of interactions, with disparate semantics, would reduce to a single language of information processing
IPCS13: Information Processing and Complex Systems, 18th September, Barcelona
No full textAll systems in nature have one thing in common: they process information. Information is registered in the state of a system and its elements, implicitly and invisibly. As elements interact, information is transferred. Indeed, bits of information about the state of one element will travel – imperfectly – to the state of the other element, forming its new state. This storage and transfer of information, possibly between levels of a multi level system, is imperfect due to randomness or noise. From this viewpoint, a system can be formalized as a collection of bits that is organized according to its rules of dynamics and its topology of interactions. Mapping out exactly how these bits of information percolate through the system could reveal new fundamental insights in how the parts orchestrate to produce the properties of the system. A theory of information processing would be capable of defining a set of universal properties of dynamical multi level complex systems, which describe and compare the dynamics of diverse complex systems ranging from social interaction to brain networks, from financial markets to biomedicine. Each possible combination of rules of dynamics and topology of interactions, with disparate semantics, would reduce to a single language of information processing
Adaptive Web-Based VR Streaming of Multi-LoD 3D Scenes via Author-Provided Relevance Scores
No full textThe growing storage requirements of 3D virtual scenes, combined with the increased heterogeneity of consumption devices, trigger the need for novel, on-demand streaming techniques of textured meshes. This paper proposes a way to perform relevance-aware Adaptive Bit-Rate (ABR) scheduling using MPEG-DASH, tailored to VR consumption in the web browser. Scene authors can annotate the relative importance of scene assets to optimize scheduling decisions. Our approach outperforms the state-of-the-art (measured using the MS-SSIM metric) across different scene complexities and network configurations, and is found to be most beneficial when scene complexity is high and network conditions are relatively poor.IEEE; IEEE Comp Soc; Virbela; Tecnico Lisboa; Immers Learning Res Network; Qualcomm; Vicon; HitLabNZ AIGI; Microsoft; Appen; Facebook Real Labs Res; XR Bootcamp; NSF; Fakespace Lab
Dynamical importance of nodes is poorly predicted by static topological features
No full textOne of the most central questions in network science is: which nodes are most important? Often this question is
answered using topological properties such as high connectedness or centrality in the network. However it is unclear
whether topological connectedness translates directly to dynamical impact. To this end, we simulate the kinetic
Ising spin model on generated and a real-world network with weighted edges. The extent of the dynamic impact
is assessed by causally intervening on a node state and effect on the systemic dynamics. The results show that
topological features such as network centrality or connectedness are actually poor predictors of the dynamical impact
of a node on the rest of the network. A solution is offered in the form of an information theoretical measure named
information impact. The metric is able to accurately reflect dynamic importance of nodes in networks under natural
dynamics using observations only, and validated using causal interventions. We conclude that the most dynamically
impactful nodes are usually not the most well-connected or central nodes. This implies that the common assumption
of topologically central or well-connected nodes being also dynamically important is actually false, and we cannot
abstract away the dynamics from a network before analyzing it
Modeling and simulating the propagation of infectious diseases using complex networks
No full textFor explanation and prediction of the evolution of infectious diseases in populations, researchers often use simplified mathematical models for simulation. We believe that the results from these models are often questionable when the epidemic dynamics becomes more complex, and that developing more realistic models is intractable.
In this dissertation we propose to simulate infectious disease propagation using dynamic and complex networks. We present the Simulator of Epidemic Evolution using Complex Networks (SEECN), an expressive and high-performance framework that combines algorithms for graph generation and various operators for modeling temporal dynamics. For graph generation we use the Kronecker algorithm, derive its underlying statistical structure and exploit it for a variety of purposes. Then the epidemic is evolved over the network by simulating the dynamics of the population and the epidemic simultaneously, where each type of dynamics is performed by a separate operator. All dynamics operators can be fully and independently parameterized, facilitating incremental model development and enabling different influences to be toggled for differential analysis.
As a prototype, we simulate two relatively complex models for the HIV epidemic and find a remarkable fit to reported data for AIDS incidence and prevalence. Our most important conclusion is that the mere dynamics of the HIV epidemic is sufficient to produce rather complex trends in the incidence and prevalence statistics, e.g. without the introduction of particularly effective treatments at specific times. We show that this invalidates assumptions and conclusions made previously in the literature, and argue that simulations used for explanation and prediction of trends should incorporate more realistic models for both the population and the epidemic than is currently done. In addition, we substantiate a previously predicted paradox that the availability of Highly Active Anti-Retroviral Treatment likely causes an increased HIV incidence.M.S
Detecting critical transitions in the human innate immune system post-cardiac surgery
No full textCoronary artery bypass grafting with cardiopulmonary bypass activates the human innate immune system (HIIS) and invokes a vigorous inflammatory response that is systemic. This massive inflammatory reaction can contribute to the development of postoperative complications that could topple the state of the system from health to disease, or even to some extent, death. The body, after all, is in a state where majority of its immune cell populations have been depleted, and sometimes needs days or even longer to recuperate. To obtain a deeper understanding on how HIIS responds to complications after cardiac surgery, we perturb the immune system model that we have developed in an earlier work in-silico by adding another source of inflammation triggering moieties (ITMs) hours after surgery in various regimes. A critical transition occurs upon the addition of a critical concentration of ITMs when the insult is sustained for approximately 3 h – a total concentration that corresponds to the fatal concentration of ITMs documented in literature. By perturbing HIIS in-silico with additional sources of ITMs to mimic persistent and recurring episodes of post-surgery complications, we are able to specify under which conditions critical transitions occur in HIIS, as well as pinpoint important blood parameters that exhibit critical transitions in our model. More importantly, by applying early warning signals on the clinical trial data used to calibrate and validate HIIS model, we are able to detect blood parameters that exhibit critical transitions in patients who died post-surgery, where pro-inflammatory cytokines are deemed potential markers for critical transitions
Physical-Layer Fingerprinting of LoRa devices using Supervised and Zero-Shot Learning
No full text© 2017 Copyright held by the owner/author(s). Publication rights licensed to ACM. Physical-layer fingerprinting investigates how features extracted from radio signals can be used to uniquely identify devices. This paper proposes and analyses a novel methodology to ingerprint LoRa devices, which is inspired by recent advances in supervised machine learning and zero-shot image classification. Contrary to previous works, our methodology does not rely on localized and low-dimensional features, such as those extracted from the signal transient or preamble, but uses the entire signal. We have performed our experiments using 22 LoRa devices with 3 different chipsets. Our results show that identical chipsets can be distinguished with 59% to 99% accuracy per symbol, whereas chipsets from different vendors can be fingerprinted with 99% to 100% accuracy per symbol. The ingerprinting can be performed using only inexpensive commercial off-the-shelf software defined radios, and a low sample rate of 1 Msps. Finally, we release all datasets and code pertaining to these experiments to the public domain.sponsorship: The authors would like to thank the anonymous reviewers for their helpful comments, and Enrique Argones, Bram Bonne, Rafael Galvez and Balazs Nemeth for their support. This work was supported in part by a Ph.D. grant of the Research Foundation Flanders (FWO), the Research Council KU Leuven C16/15/058, the Flemish Government through the imec Distributed Trust program, in particular the Netsec project, and through ICON project Diskman. (Research Foundation Flanders (FWO), Research Council KU Leuven|C16/15/058, Flemish Government through the imec Distributed Trust program, Flemish Government through ICON project Diskman, Flemish Government through Netsec project)status: Publishe
Power Analysis on AES and LoRaWAN
No full textSide-channel attacks introduce an alternate method of attacking cryptographic algorithms by targeting the implementation of the computer system rather than the algorithm itself. One of these side-channel attacks is the power analysis attack and has shown to be successful in attacking various device implementations using cryptographic algorithms which are considered to be secure. One of these victims is the popular and well used AES algorithm. Power analysis attacks could thus provide a method to break the security of these communication channels.
However, the practicality and effectiveness of these attacks in practice are often undocumented. In this thesis, the author will try to answer to question: "Is the AES algorithm in modern IoT appliances vulnerable for power analysis attacks?" and "Are power analysis attacks usable in practice?". To answer these questions, a detailed description about the AES algorithm and power analysis attacks is provided in this thesis. Next, several case studies are performed to address the practicality and effectiveness of the power analysis attacks. During these case studies the author was able to conclude that the quality of the measurements directly affects the effectiveness of the power analysis attacks. The quality of the measurements relies on several conditions such as electrical noise and measurement set-ups
Power Analysis on AES and LoRaWAN
No full textSide-channel attacks introduce an alternate method of attacking cryptographic algorithms by targeting the implementation of the computer system rather than the algorithm itself. One of these side-channel attacks is the power analysis attack and has shown to be successful in attacking various device implementations using cryptographic algorithms which are considered to be secure. One of these victims is the popular and well used AES algorithm. Power analysis attacks could thus provide a method to break the security of these communication channels.
However, the practicality and effectiveness of these attacks in practice are often undocumented. In this thesis, the author will try to answer to question: "Is the AES algorithm in modern IoT appliances vulnerable for power analysis attacks?" and "Are power analysis attacks usable in practice?". To answer these questions, a detailed description about the AES algorithm and power analysis attacks is provided in this thesis. Next, several case studies are performed to address the practicality and effectiveness of the power analysis attacks. During these case studies the author was able to conclude that the quality of the measurements directly affects the effectiveness of the power analysis attacks. The quality of the measurements relies on several conditions such as electrical noise and measurement set-ups
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