795 research outputs found

    Exploratory study to explore the role of ICT in the process of knowledge management in an Indian business environment

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    In the 21st century and the emergence of a digital economy, knowledge and the knowledge base economy are rapidly growing. To effectively be able to understand the processes involved in the creating, managing and sharing of knowledge management in the business environment is critical to the success of an organization. This study builds on the previous research of the authors on the enablers of knowledge management by identifying the relationship between the enablers of knowledge management and the role played by information communication technologies (ICT) and ICT infrastructure in a business setting. This paper provides the findings of a survey collected from the four major Indian cities (Chennai, Coimbatore, Madurai and Villupuram) regarding their views and opinions about the enablers of knowledge management in business setting. A total of 80 organizations participated in the study with 100 participants in each city. The results show that ICT and ICT infrastructure can play a critical role in the creating, managing and sharing of knowledge in an Indian business environment

    The enablers and implementation model for mobile KMS in Australian healthcare

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    In this research project, the enablers in implementing mobile KMS in Australian regional healthcare will be investigated, and a validated framework and guidelines to assist healthcare in implementing mobile KMS will also be proposed with both qualitative and quantitative approaches. The outcomes for this study are expected to improve the understanding the enabling factors in implementing mobile KMS in Australian healthcare, as well as provide better guidelines for this process

    Cyber Security

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    This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

    Threats from Botnets

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    At present, various cyberattacks based on Botnet are the most serious security threats to the Internet. As Botnet continue to evolve and behavioral research on Botnet is inadequate, the question of how to apply some behavioral problems to Botnet research and combine the psychology of the operator to analyze the future trend of Botnet is still a continuous and challenging issue. Botnet is a common computing platform that can be controlled remotely by attackers by invading several noncooperative user terminals in the network space. It is an attacking platform consisting of multiple Bots controlled by a hacker. The classification of Botnet and the working mechanism of Botnet are introduced in this chapter. The threats and the threat evaluation of Botnet are summarized

    A Deep Learning Based Approach To Detect Covert Channels Attacks and Anomaly In New Generation Internet Protocol IPv6

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    The increased dependence of internet-based technologies in all facets of life challenges the government and policymakers with the need for effective shield mechanism against passive and active violations. Following up with the Qatar national vision 2030 activities and its goals for “Achieving Security, stability and maintaining public safety” objectives, the present paper aims to propose a model for safeguarding the information and monitor internet communications effectively. The current study utilizes a deep learning based approach for detecting malicious communications in the network traffic. Considering the efficiency of deep learning in data analysis and classification, a convolutional neural network model was proposed. The suggested model is equipped for detecting attacks in IPv6. The performance of the proposed detection algorithm was validated using a number of datasets, including a newly created dataset. The performance of the model was evaluated for covert channel, DDoS attacks detection in IPv6 and for anomaly detection. The performance assessment produced an accuracy of 100%, 85% and 98% for covert channel detection, DDoS detection and anomaly detection respectively. The project put forward a novel approach for detecting suspicious communications in the network traffic

    Cyber Security

    Get PDF
    This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security

    Analysis on NSAW Reminder Based on Big Data Technology

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    NSAWS is an intelligent and real-time large database management system. By analyzing the user identity data and access rights contained in the collected information, the NSAWS finds out the potential risks and issues an alarm notice in a timely manner. This paper mainly studies how to strengthen the prevention of network attacks in BD environment from the following aspects. This paper first introduces the common technology on the Internet in our country and its application status; secondly, it expounds the architecture, deployment mode and operation mode of the large database system based on the basic security facilities such as cloud computing platform and firewall. Then the traditional NSAWS is analyzed and the simulation platform is tested. The results show that the platform has high accuracy and stability in alerting network security hazards and can effectively protect network security

    Survey of Attack Projection, Prediction, and Forecasting in Cyber Security

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    This paper provides a survey of prediction, and forecasting methods used in cyber security. Four main tasks are discussed first, attack projection and intention recognition, in which there is a need to predict the next move or the intentions of the attacker, intrusion prediction, in which there is a need to predict upcoming cyber attacks, and network security situation forecasting, in which we project cybersecurity situation in the whole network. Methods and approaches for addressing these tasks often share the theoretical background and are often complementary. In this survey, both methods based on discrete models, such as attack graphs, Bayesian networks, and Markov models, and continuous models, such as time series and grey models, are surveyed, compared, and contrasted. We further discuss machine learning and data mining approaches, that have gained a lot of attention recently and appears promising for such a constantly changing environment, which is cyber security. The survey also focuses on the practical usability of the methods and problems related to their evaluation

    No Security Through Obscurity: Changing Circumvention Law to Protect our Democracy Against Cyberattacks

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    Cybersecurity is increasingly vital in a climate of unprecedented digital assaults against liberal democracy. Russian hackers have launched destabilizing cyberattacks targeting the United States’ energy grid, voting machines, and political campaigns. America\u27s existing inadequate cyber defenses operate according to a simple assumption: hide the computer code that powers critical infrastructure so that America\u27s enemies cannot exploit undiscovered weaknesses. Indeed, the intellectual property regime relies entirely on this belief, protecting those who own the rights in computer code by punishing those who might access and copy that code. This “security through obscurity” approach has failed. Rightsholders, on their own, cannot develop effective countermeasures to hacking because there are simply too many possibilities to preempt. The most promising solution, therefore, is to open the project of cybersecurity to as many talented and ethical minds as possible. Openness, not civil remedies and secrecy, is a greater means of ensuring safety. This Article proposes that we adopt a “defense in depth” approach to security that will increase transparency by modifying anticircumvention laws and by facilitating communication between the security community and product vendors
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