Information Era. Conscience Society. Creativity

ttendees will learn about the research and development which will be effected by scientists in the branch of Conscience Society creation in next decades of XXI century. Conscience is usually seen as linked to a morality inherent in all humans, to a beneficent universe and/or to divinity. It is increasingly conceived of as applying to the world as a whole and as a main feature of conscience society. It has motivated its numerous models, characteristics and functions of Conscience for creation the societal intelligent adaptable information systems in Conscience Society. The moral life is a vital part for the world to maintain a Conscience (civilized) Society, so always keep in mind to: accept differences in others; respond promptly to others; leave some "free" time; care about others as if they were you; treat everyone similarly; never engage in violent acts; have an inner sense of thankfulness; have a sense of commitment. Creativity is a result of brain activity which differentiates individuals and could ensure an important competitive advantage for persons, for companies, for Society in general, and for Conscience Society in special. Very innovative branches – like software industry, computer industry, car industry – consider creativity as the key of business success. Natural Intelligence’ Creativity can develop basic creative activities, but Artificial Intelligence’ Creativity, and, especially, Conscience Intelligence’ Creativity should be developed and they could be enhanced over the level of Natural Intelligence. The basic idea for present communication represent the research results communicated at the last two annual AESM conferences [1] [2].Conscience, Adaptability, Creativity, Intelligence, Conscience Society

The Proceedings of 15th Australian Information Security Management Conference, 5-6 December, 2017, Edith Cowan University, Perth, Australia

Conference Foreword The annual Security Congress, run by the Security Research Institute at Edith Cowan University, includes the Australian Information Security and Management Conference. Now in its fifteenth year, the conference remains popular for its diverse content and mixture of technical research and discussion papers. The area of information security and management continues to be varied, as is reflected by the wide variety of subject matter covered by the papers this year. The papers cover topics from vulnerabilities in “Internet of Things” protocols through to improvements in biometric identification algorithms and surveillance camera weaknesses. The conference has drawn interest and papers from within Australia and internationally. All submitted papers were subject to a double blind peer review process. Twenty two papers were submitted from Australia and overseas, of which eighteen were accepted for final presentation and publication. We wish to thank the reviewers for kindly volunteering their time and expertise in support of this event. We would also like to thank the conference committee who have organised yet another successful congress. Events such as this are impossible without the tireless efforts of such people in reviewing and editing the conference papers, and assisting with the planning, organisation and execution of the conference. To our sponsors, also a vote of thanks for both the financial and moral support provided to the conference. Finally, thank you to the administrative and technical staff, and students of the ECU Security Research Institute for their contributions to the running of the conference

Survey of the State and Future Trends of Intelligent Systems

This paper presents an attempt to formalize objective macro model of the field of artificial intelligence (AI). We show that creation of this model is justified, and with the aid of information from World Wide Web it is possible now. With this aim in view, we propose a research method. To obtain a macro model of the artificial intelligence field, we made a survey of research groups in the world, including companies, applications, organizations as well as a general assessment of the state of Al technology. The survey is intended to show some benefits. Intelligent systems are becoming very useful and are starting to achieve many of the projected past promises. Important documents on future trends and roles of intelligent systems have been recently published, as well as interesting surveys in the field. We have assessed several methodologies of research of the state of the art in this field and identified their promises and limitations. Considering the present state of Al technology, research projects, important documents and trends in traditional information technologies, we have made a preliminary model of intelligent systems and their future surveys. In the era of second generation knowledge-based systems and growing complexity of the Al field, we believe that it is necessary to include macro model of Al in all scientific researches and application projects

A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications

Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of technology with the potential of far-reaching impact in domains ranging from medical over industrial to artistic, gaming, and military. Today, these emerging BCI applications are typically still at early technology readiness levels, but because BCIs create novel, technical communication channels for the human brain, they have raised privacy and security concerns. To mitigate such risks, a large body of countermeasures has been proposed in the literature, but a general framework is lacking which would describe how privacy and security of BCI applications can be protected by design, i.e., already as an integral part of the early BCI design process, in a systematic manner, and allowing suitable depth of analysis for different contexts such as commercial BCI product development vs. academic research and lab prototypes. Here we propose the adoption of recent systems-engineering methodologies for privacy threat modeling, risk assessment, and privacy engineering to the BCI field. These methodologies address privacy and security concerns in a more systematic and holistic way than previous approaches, and provide reusable patterns on how to move from principles to actions. We apply these methodologies to BCI and data flows and derive a generic, extensible, and actionable framework for brain-privacy-preserving cybersecurity in BCI applications. This framework is designed for flexible application to the wide range of current and future BCI applications. We also propose a range of novel privacy-by-design features for BCIs, with an emphasis on features promoting BCI transparency as a prerequisite for informational self-determination of BCI users, as well as design features for ensuring BCI user autonomy. We anticipate that our framework will contribute to the development of privacy-respecting, trustworthy BCI technologies

Big data: The end of the scientific method?

"For it is not the abundance of knowledge, but the interior feeling and taste of things, which is accustomed to satisfy the desire of the soul." (Saint Ignatius of Loyola). We argue that the boldest claims of big data (BD) are in need of revision and toning-down, in view of a few basic lessons learned from the science of complex systems. We point out that, once the most extravagant claims of BD are properly discarded, a synergistic merging of BD with big theory offers considerable potential to spawn a new scientific paradigm capable of overcoming some of the major barriers confronted by the modern scientific method originating with Galileo. These obstacles are due to the presence of nonlinearity, non-locality and hyperdimensions which one encounters frequently in multi-scale modelling of complex systems

Recent Applications in Graph Theory

Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further. This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks

Development and evaluation of cognitive risk and regulatory compliance management strategies for financial institutions.

This dissertation investigates how the risk and regulatory compliance management activities and business processes of financial institutions can be improved by utilizing cognitive computing technologies. At first, a systemic literature review, expert interviews as well as a survey were carried out with the aim to identify the main fields of action for the enhancement of the risk and compliance management procedures. The systemic review of 2,279 journal articles that deal with cognitive computing technologies in the banking and finance sector showed that risk and compliance management are main topics of interest. In further detail, the evaluation of six interviews and 62 survey forms displayed that the increasing number and complexity of legal requirements is regarded as a burden for the participating executive risk and compliance managers. Consequently, a majority of the participating experts were of the opinion that banks and other financial institutions are required to deal with the implementation of new technological solutions that feature artificial intelligence capabilities in order to deal with this increasing burden more efficiently in the future. These insights were taken as a foundation for the development of two implementation strategies. The first strategy aimed to show that a cognitive computing featured application can facilitate the management of new or extended regulations that are published by banking supervision authorities. The artificial intelligence and machine learning capabilities of the software analyse the content of financial regulations and create a probability-weighted initial list of obligations that result from a legal framework. In addition, based on the information that are stored in the system, the application identifies departments, business lines and controls that could be affected by an obligation. In a consecutive step, the compliance manager analyses the initial technical results and makes adjustments. This use case showed that the processing of legal requirements can be facilitated by the usage of cognitive computing technologies. The expert receives an initial list of obligations that result from a regulation without having to read a legal text line by line first. Therefore, time and cost associated with the management of regulatory requirements can be significantly reduced. The second implementation strategy focused on the optimization of risk management business processes. For the strategy development, a selected process mining application was used to analyse a specific risk management process at a credit institution in Germany. The evaluation of this use case showed that the usage of a process mining application offers compliance managers the opportunity to discover potential non-compliant process executions in detail and in real time. As a result, the compliance manger can react immediately when conspicuous activities are detected. Moreover, inefficiencies and bottlenecks in the real-life execution of risk management business processes can be identified. These insights offer financial institutions the opportunity to enhance their risk management business processes and the associated workload of the individual process participants. To draw a conclusion, the last major step for financial institutions to improve their risk and compliance management activities and business processes was to digitalize them and the next major step is to implement intelligence by using cognitive computing technologies.Administración y Dirección de Empresa