Aditya Khamparia, Sagar Pande, Deepak Gupta, Ashish Khanna and Arun Kumar Sangaiah
The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).
Abstract
Purpose
The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).
Design/methodology/approach
Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.
Findings
By using the proposed technique, FScore obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.
Research limitations/implications
Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.
Originality/value
This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.
Details
Keywords
Sagar Pande, Aditya Khamparia and Deepak Gupta
One of the important key components of health care–based system is a reliable intrusion detection system. Traditional techniques are not adequate to handle complex data. Also, the…
Abstract
Purpose
One of the important key components of health care–based system is a reliable intrusion detection system. Traditional techniques are not adequate to handle complex data. Also, the diversified intrusion techniques cannot meet current network requirements. Not only the data is getting increased but also the attacks are increasing very rapidly. Deep learning and machine learning techniques are very trending in the area of research in the area of network security. A lot of work has been done in this area by still evolutionary algorithms along with machine learning is very rarely explored. The purpose of this study is to provide novel deep learning framework for the detection of attacks.
Design/methodology/approach
In this paper, novel deep learning is the framework is proposed for the detection of attacks. Also, a comparison of machine learning and deep learning algorithms is provided.
Findings
The obtained results are more than 99% for both the data sets.
Research limitations/implications
The diversified intrusion techniques cannot meet current network requirements.
Practical implications
The data is getting increased but also the attacks are increasing very rapidly.
Social implications
Deep learning and machine learning techniques are very trending in the area of research in the area of network security.
Originality/value
Novel deep learning is the framework is proposed for the detection of attacks.
Details
Keywords
Fariz Huseynov and Jeanene Mitchell
The purpose of this paper is to spur further exploration of blockchain technologies for environmental peacebuilding, specifically through water management. Although the…
Abstract
Purpose
The purpose of this paper is to spur further exploration of blockchain technologies for environmental peacebuilding, specifically through water management. Although the environmental peacebuilding field acknowledges the potentially transformative nature of frontier technologies, most existing studies do not address how such technologies can contribute to peacebuilding through improved natural resource governance. Using a theory synthesis research design, this conceptual paper connects these studies to discuss how blockchain technologies in water management may contribute to environmental peacebuilding through the efficient and transparent management of natural resources.
Design/methodology/approach
The authors use a conceptual approach and a theory synthesis research design to present potential mechanisms through which blockchain technology can potentially contribute to environmental peacebuilding.
Findings
The authors discuss the limitations in the literature on environmental peacebuilding, blockchain and water management, concluding that the third generation of studies should focus on the role of frontier technologies. This approach should especially address the negative consequences of technology for peacebuilding objectives. The authors argue that blockchain applications in water management can potentially contribute to environmental peacebuilding objectives in three ways: (i) creating a mechanism for confidence-building in low-trust contexts through automated and transparent water transactions, (ii) facilitating postconflict economic development through attracting capital and increasing the efficiency of water management and (iii) improving governance through greater transparency and local participation in natural resource management.
Originality/value
To the best of the authors’ knowledge, this study is among the first to conceptually explore the use of blockchain technology for water management in the context of environmental peacebuilding. The insights from this study can guide policymakers of conflict sides that focus on resolving issues such as lack of governance and low state agency.