Assessing and improving the quality of security methodologies for distributed systems

Uzunov, Anton V.; Fernández, Eduardo B.; Falkner, Katrina

doi:10.1002/smr.1980

Cited by 6 publications

(7 citation statements)

References 78 publications

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“…Currently developed IDSs do not show clear, structured software development processes. Consequently, resulting inadequate requirement management, processing, validation, and verification of requirements quality [19]. To elaborate more on the evidence provided in the literature, the detection process is not deployed at each layer of the hierarchy.…”

Section: Shortcomings Of Existing Idss From Se Perspectivesmentioning

confidence: 99%

“…Hence, recharging or replacing those sensor nodes will cost more because of the far distance.As for the security of WSNs, owing to the network limitations, it is difficult to achieve security in applications deployed over WSNs [8]. These sorts of networks are usually deployed in remote and hostile environments to perform its tasks [4,12,19]. However, hostile environments are usually unattended.…”

mentioning

confidence: 99%

“…However, hostile environments are usually unattended. Due to that, WSNs lack physical protection (e.g., no switches or gateways to monitor the flow of information) resulting a potential of node compromising as well as low network security and protection [10,15,19]. Therefore, it is important to secure such networks from intrusions and attacks, especially in applications where security services are important.…”

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confidence: 99%

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Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks

Almomani

AlRomi²

2020

Sensors

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Applying Software Engineering (SE) processes is vital to critical and complex systems including security and networking systems. Nowadays, Wireless Sensor Networks (WSNs) and their applications are found in many military and civilian systems which make them attractive to security attackers. The increasing risks and system vulnerabilities of WSNs have encouraged researchers and developers to propose many security solutions including software-based Intrusion Detection Systems (IDSs). The main drawbacks of current IDSs are due to the lack of clear, structured software development processes. Unfortunately, a substantial gap has been observed between WSN and SE research communities. Integrating SE and WSNs is an emerging topic that will be expanded as technology evolves and spreads in all life aspects. Consequently, this paper highlighted the importance of Requirement Engineering, Software Design, and Testing when developing IDSs for WSNs. Three software IDS designs were proposed in this study: Scheduling, Broadcast, and Watchdog designs. The three designs were compared in terms of consumed energy and network lifetime. Although the same IDS approach was used, but, by highlighting the design phase and implementing different designs, the network lifetime was increased by 73.6% and the consumed energy was reduced by 20% in some of the designs. This is a clear indication of how following a proper SE process could affect the performance of the IDS in WSN. Moreover, conclusions were drawn in regard to applying software engineering processes to IDSs to deliver the required functionalities, with respect to operational constraints, with an improved performance, accuracy and reliability.

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Section: Shortcomings Of Existing Idss From Se Perspectivesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks

Almomani

AlRomi²

2020

Sensors

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“…In our case, we needed a metamodel that covers the main components of a big data ecosystem and which at the same time incorporates security aspects into those components: the security reference architecture (SRA) for big data, defined in the previous section. The process follows the recommendations from the security-by-design approach [43,44] by taking security into consideration from the early stages of the process and by including security aspects during the whole process.…”

Section: Process For the Development Of A Secure Big Data Ecosystemmentioning

confidence: 99%

Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies

et al. 2020

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Big data ecosystems are increasingly important for the daily activities of any type of company. They are decisive elements in the organization, so any malfunction of this environment can have a great impact on the normal functioning of the company; security is therefore a crucial aspect of this type of ecosystem. When approaching security in big data as an issue, it must be considered not only during the creation and implementation of the big data ecosystem, but also throughout its entire lifecycle, including operation, and especially when managing and responding to incidents that occur. To this end, this paper proposes an incident response process supported by a private blockchain network that allows the recording of the different events and incidents that occur in the big data ecosystem. The use of blockchain enables the security of the stored data to be improved, increasing its immutability and traceability. In addition, the stored records can help manage incidents and anticipate them, thereby minimizing the costs of investigating their causes; that facilitates forensic readiness. This proposal integrates with previous research work, seeking to improve the security of big data by creating a process of secure analysis, design, and implementation, supported by a security reference architecture that serves as a guide in defining the different elements of this type of ecosystem. Moreover, this paper presents a case study in which the proposal is being implemented by using big data and blockchain technologies, such as Apache Spark or Hyperledger Fabric.

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“…Our proposal is composed by twelve different phases covering the main stages of development, including analysis and design which, normally, are not sufficiently considered in this kind of scenarios. Moreover, it is important to highlight that a process of this kind should not be only a description of a set of activities; in fact, it should be supported by a conceptual framework that defines the main components of the system to develop [14]. In our case, we needed a metamodel that covers the main components of a Big Data ecosystem and, at the same time, incorporates security aspects into them; for this, we have defined a customized Security Reference Architecture (SRA) for Big Data [15].…”

Section: Introductionmentioning

confidence: 99%

Secure Development of Big Data Ecosystems

et al. 2019

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A Big Data environment is a powerful and complex ecosystem that helps companies extract important information from data to make the best business and strategic decisions. In this context, due to the quantity, variety, and sensitivity of the data managed by these systems, as well as the heterogeneity of the technologies involved, privacy and security especially become crucial issues. However, ensuring these concerns in Big Data environments is not a trivial issue, and it cannot be treated from a partial or isolated perspective. It must be carried out through a holistic approach, starting from the definition of requirements and policies, and being present in any relevant activity of its development and deployment. Therefore, in this paper, we propose a methodological approach for integrating security and privacy in Big Data development based on main standards and common practices. In this way, we have defined a development process for this kind of ecosystems that considers not only security in all the phases of the process but also the inherent characteristics of Big Data. We describe this process through a set of phases that covers all the relevant stages of the development of Big Data environments, which are supported by a customized security reference architecture (SRA) that defines the main components of this kind of systems along with the key concepts of security.

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Assessing and improving the quality of security methodologies for distributed systems

Cited by 6 publications

References 78 publications

Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks

Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks

Improving Incident Response in Big Data Ecosystems by Using Blockchain Technologies

Secure Development of Big Data Ecosystems

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