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Sökning: hsv:(NATURVETENSKAP) hsv:(Data och informationsvetenskap) > Popov Oliver

  • Resultat 1-10 av 132
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1.
  • Gamukama, Elly Amani, et al. (författare)
  • A framework for evaluating efficiency - Fairness tradeoff in IP networks in context of development
  • 2009
  • Ingår i: 2009 9th International Symposium on Communications and Information Technology, ISCIT 2009. - : IEEE Computer Society. - 9781424445219 - 9781424445226 ; , s. 507-512
  • Konferensbidrag (refereegranskat)abstract
    • Efficiency and fairness are main objectives in any system design and many choices in life are made based on their tradeoffs. In this paper we introduce a framework for the evaluation of efficiency-fairness tradeoffs that would provide a sound basis for network providers and social planners to provide or plan for an equitable access to the Internet to a diversity of users with different needs and financial possibilities representing mainly developing regions and emerging economies. Control approaches are introduced to address the upraising distortion of fairness concept in IP based networks by using the (α, β) - fairness concept to establish the upper and lower fairness bounds within which the social welfare and the network efficiency are maximized. Although the use of the (α, β) - fairness concept compromises to a certain extent the degree for fairness in resource capacity allocation, it does not jeopardize the utilities for end users or the network provider. Fairness in this context mainly parameterizes tradeoff between services equality and throughput maximization.
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3.
  • Milenkovski, Aleksandar, et al. (författare)
  • Statistical framework for ns-3 : terminating simulation and regression analysis
  • 2014
  • Ingår i: World Journal on Modeling and Simulation. - 1746-7233. ; 10:2, s. 116-125
  • Tidskriftsartikel (refereegranskat)abstract
    • The ns-3 simulator is constantly gaining popularity. It plays a central role in many recent research experiments. The accuracy of the reported simulation results of these experiments is an important concern. Thus, the support in ns-3 for simulation methodologies which guarantee the accuracy of these results is a necessity. Also, the simulation results are affected by numerous scenario parameters. The correlation between the results and the simulation parameters is a significant point of interest in many experiments. In this paper, we present a ns-3 statistical framework. It enables calculation of statistically accurate simulation results by applying the terminating simulation methodology. It features simultaneous execution of simulation scenarios in multi-processor and distributed environments. Also, we integrate support for regression analysis procedures. The proposed framework supports linear and polynomial regression analysis models.We consider simulation results as dependent variables and simulation parameters as independent variables. Regression analysis enables identification of simulation scenario parameters which are significantly correlated to given simulation results. Once a valid regression model is found, it is possible to estimatively predict metric values based on simulation parameter values. This may result in substantially reduced time and effort spent on simulation experimentation.
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4.
  • Bergman, Jesper, et al. (författare)
  • The Digital Detective's Discourse - A toolset for forensically sound collaborative dark web content annotation and collection
  • 2022
  • Ingår i: The Journal of Digital Forensics, Security and Law. - : ERAU Hunt Library - DIGITAL COMMONS JOURNALS. - 1558-7215 .- 1558-7223. ; 17:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In the last decade, the proliferation of machine learning (ML) algorithms and their application on big data sets have benefited many researchers and practitioners in different scientific areas. Consequently, the research in cybercrime and digital forensics has relied on ML techniques and methods for analyzing large quantities of data such as text, graphics, images, videos, and network traffic scans to support criminal investigations. Complete and accurate training data sets are indispensable for efficient and effective machine learning models. An essential part of creating complete and accurate data sets is annotating or labelling data. We present a method for law enforcement agency investigators to annotate and store specific dark web content. Using a design science strategy, we design and develop tools to enable and extend web content annotation. The annotation tool was implemented as a plugin for the Tor browser. It can store web content, thus automatically creating a dataset of dark web data pertinent to criminal investigations. Combined with a central storage management server, enabling annotation sharing and collaboration, and a web scraping program, the dataset becomes multifold, dynamic, and extensive while maintaining the forensic soundness of the data saved and transmitted. To manifest our toolset's fitness of purpose, we used our dataset as training data for ML based classification models. A five cross-fold validation technique was used to evaluate the classifiers, which reported an accuracy score of 85 - 96%. In the concluding sections, we discuss the possible use-cases of the proposed method in real-life cybercrime investigations, along with ethical concerns and future extensions.
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5.
  • Mondlane, Avelino I., et al. (författare)
  • Insurance as Strategy for Flood Risk Management at Limpopo River Basin – A decision making Process under Uncertainty
  • 2013
  • Ingår i: International Journal of Computers & Technology. - : CIRWOLRD. - 2277-3061. ; 10:8, s. 1862-1877
  • Tidskriftsartikel (refereegranskat)abstract
    • The Limpopo River Basin, one of the nine international rivers crossing Mozambique, historically has shown to be cyclically flooded, undermining the economic and social development of its four riparian countries. Local and external added efforts are always in place when floods occur. Nowadays there are recommended ex-ante instruments to prevent floods and one of the most applicable instruments worldwide is insurance. Most of the inhabitants, even governments, affected by Limpopo River Basin are poor, therefore our concern regards the viability to apply insurance as a strategy for flood risk management. Moreover our research investigates to what extent the application of insurance, within two identified communities as case study, might create an added value in the process of decision making on flood risk management for Limpopo River Basin.
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6.
  • Mondlhane, Avelino Isaias, 1964- (författare)
  • Scenarios for Flood Risk Management Strategies Integration in Mozambique : A backcasting approach for the case of the Limpopo River Basin
  • 2018
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Flood risk management strategic planning with long-term perspectives is a complex problem, for which the solution requires a multidisciplinary and multi-paradigm approach. A significant dimension of this complexity arises from the need to include or add a participatory mode to the solution process, which amounts to a requirement that all stakeholders, ranging from decision makers to experts and beneficiaries, be involved in the decision making. However, these stakeholders may have different objectives, and this may lead to different or even conflicting courses of action, particularly when a selection must be made of the most appropriate coping strategy that may lead to sustainability. Multiple-criteria decision analysis is one paradigm that has the capability to handle these conflicting courses of action. There is a volume of research that has presented various strategies for flood risk management over the last couple of decades. Recent approaches have included computer-based modelling and infrastructure measurement. One finding providing a strong basis for the relevance of the problem we are trying to solve is that most of these strategies fail in the long run; this is particularly true in developing countries, considering their economic, infrastructure and social limitations. Hence, a novel approach is very much warranted, and this is the central object of our study. An important aspect of its novelty lies in realising that instead of applying numerous strategies in isolation, one needs to combine and integrate them. Our research focuses on developing scenarios for integrating flood risk management strategies, based on multiple-criteria decision analysis to combine conflicting arguments in order to generate a viable strategy. Additional aspects of this holistic approach were imported from the area of business management, such as strategic planning and balanced scorecards for decision making within scenario planning. Finally, a long-term vision for a sustainable environment that minimises the impact of floods was designed using backcasting scenario planning. The decision-making alternatives were risk, hazard, exposure and vulnerability, and these were used against a set of 24 criteria for control. These criteria were extracted from various coping and adaptive capabilities, and from environmental, economic, and social domains. The scenarios for the integration of flood risk management strategies are based on a real-life case study of the Limpopo River Basin, and specifically of the Chókwe district in Gaza province, Mozambique. The result of this research was a framework called SPIFRiMS, based on a sliding weight elicitation method. The framework and the data from the case study were implemented in Excel. The research outputs were five different scenarios illustrating different options from the perspectives of the stakeholders and beneficiaries in the light of their long-term views when compared to the actual state of the art. 
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7.
  • Abbas, Haider, et al. (författare)
  • Security, Safety and Trust Management
  • 2017
  • Ingår i: 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises. - : IEEE Computer Society. - 9781538617595 ; , s. 242-243
  • Konferensbidrag (refereegranskat)abstract
    • The continuously evolving nature of today's internet outdates the existing security and safety mechanisms and therefore there is an emerging need to propose robust, powerful and reliable solutions. These advancements have a great impact on the software and system architectures, resulting in a highly dynamic smart networked environment. The systems used within these complex environments have at least two things in common, namely, the need to restrict or grant access for the required resources based on security policy to face security threats, and the need to sustain resilience of the environment in face of safety hazards. Both aspects should consider trust.
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8.
  • Aranda, Laura, et al. (författare)
  • A Conceptual Model of an Intelligent Platform for Security Risk Assessment in SMEs
  • 2019
  • Ingår i: 2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT). - : IEEE. - 9781728139036 - 9781728139029 ; , s. 181-188
  • Konferensbidrag (refereegranskat)abstract
    • SMEs are increasingly targeted by cyberattacks and usually less in control of their Information Security Management System than larger organizations due to a lack of resources. Risk assessment can help them to determine which changes are needed bearing in mind their constraints. However, common frameworks for risk assessments are more suitable for large organizations. Some of them have been designed specifically for SMEs but still target an audience of information security experts and are considered as time-consuming by SMEs. This article aims at tackling those issues by introducing a conceptual model of an Intelligent Platform for supporting SMEs in security risk assessment process. The design research method was used to develop a model taking into account the inputs from relevant stakeholders collected via interviews. The model was validated and improved with case studies where quick security risk assessments in three different SMEs have been performed following the activities that the proposed model is supposed to perform.
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9.
  • Bergman, Jesper, 1990-, et al. (författare)
  • Exploring Dark Web Crawlers : A Systematic Literature Review of Dark Web Crawlers and Their Implementation
  • 2023
  • Ingår i: IEEE Access. - 2169-3536. ; 11, s. 35914-35933
  • Forskningsöversikt (refereegranskat)abstract
    • Strong encryption algorithms and reliable anonymity routing have made cybercrime investigation more challenging. Hence, one option for law enforcement agencies (LEAs) is to search through unencrypted content on the Internet or anonymous communication networks (ACNs). The capability of automatically harvesting web content from web servers enables LEAs to collect and preserve data prone to serve as potential leads, clues, or evidence in an investigation. Although scientific studies have explored the field of web crawling soon after the inception of the web, few research studies have thoroughly scrutinised web crawling on the “dark web”, or ACNs, such as I2P, IPFS, Freenet, and Tor. The current paper presents a systematic literature review (SLR) that examines the prevalence and characteristics of dark web crawlers. From a selection of 58 peer-reviewed articles mentioning crawling and the dark web, 34 remained after excluding irrelevant articles. The literature review showed that most dark web crawlers were programmed in Python, using either Selenium or Scrapy as the web scraping library. The knowledge gathered from the systematic literature review was used to develop a Tor-based web crawling model into an already existing software toolset customised for ACN-based investigations. Finally, the performance of the model was examined through a set of experiments. The results indicate that the developed crawler was successful in scraping web content from both clear and dark web pages, and scraping dark marketplaces on the Tor network. The scientific contribution of this paper entails novel knowledge concerning ACN-based web crawlers. Furthermore, it presents a model for crawling and scraping clear and dark websites for the purpose of digital investigations. The conclusions include practical implications of dark web content retrieval and archival, such as investigation clues and evidence, and related future research topics.
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10.
  • Bergman, Jesper, 1990-, et al. (författare)
  • Recognition of tor malware and onion services
  • 2023
  • Ingår i: Journal of Computer Virology and Hacking Techniques. - 2263-8733.
  • Tidskriftsartikel (refereegranskat)abstract
    • The transformation of the contemporary societies through digital technologies has had a profound effect on all human activities including those that are in the realm of illegal, unlawful, and criminal deeds. Moreover, the affordances provided by the anonymity creating techniques such as the Tor protocol which are beneficial for preserving civil liberties, appear to be highly profitable for various types of miscreants whose crimes range from human trafficking, arms trading, and child pornography to selling controlled substances and racketeering. The Tor similar technologies are the foundation of a vast, often mysterious, sometimes anecdotal, and occasionally dangerous space termed as the Dark Web. Using the features that make the Internet a uniquely generative knowledge agglomeration, with no borders, and permeating different jurisdictions, the Dark Web is a source of perpetual challenges for both national and international law enforcement agencies. The anonymity granted to the wrong people increases the complexity and the cost of identifying both the crimes and the criminals, which is often exacerbated with lack of proper human resources. Technologies such as machine learning and artificial intelligence come to the rescue through automation, intensive data harvesting, and analysis built into various types of web crawlers to explore and identify dark markets and the people behind them. It is essential for an effective and efficient crawling to have a pool of dark sites or onion URLs. The research study presents a way to build a crawling mechanism by extracting onion URLs from malicious executables by running them in a sandbox environment and then analysing the log file using machine learning algorithms. By discerning between the malware that uses the Tor network and the one that does not, we were able to classify the Tor using malware with an accuracy rate of 91% with a logistic regression algorithm. The initial results suggest that it is possible to use this machine learning approach to diagnose new malicious servers on the Tor network. Embedding this kind of mechanism into the crawler may also induce predictability, and thus efficiency in recognising dark market activities, and consequently, their closure. 
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