Intrusion Detection and Prevention Systems: An Updated Review

Azeez, Nureni Ayofe; Bada, Taiwo Mayowa; Misra, Sanjay; Adewumi, Adewole; Vyver, Charles Van der; Ahuja, Ravin

doi:10.1007/978-981-32-9949-8_48

Cited by 54 publications

(19 citation statements)

References 4 publications

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“…One of them is the Intrusion Detection and Prevention System (IDPS) which is a computer or software program designed for network or system monitoring. It recognizes weaknesses, reports malicious attacks, and imposes protective methods to keep up with the progress of computerrelated crimes via multiple response techniques [87].…”

Section: Integritymentioning

confidence: 99%

Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review

2021

Adv. sci. technol. eng. syst. j.

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Sustainable urban development and utilization of Internet of Things (IoT) technology is driving cities globally to evolve into Smart Cities (SC). The power of IoT services and applications will enable public agencies to provide personalized services to the citizens and inevitably improves their much-needed quality of life. However, although the use of IoT technology proves to be advantageous to citizens, it is not without challenges, particularly concerning with the management of information security. As agencies prepare towards SCs with the utilization of IoT, their Information Systems (IS) security management is even more critical. Current IS security management approaches must be reviewed and potentially revise appropriately in tandem with the increasing commercial use of the IoT technology. Therefore, this paper aims to discuss challenges in the IS management specifically in protecting and assuring information accuracy and completeness. Document analysis on relevant literature has been carried out to identify and analyse the challenges. The result discusses that the IS security management for IoT-enabled SC is challenged in five aspects: governance, integrity, interoperability, personalization, and self-organizing. Considerations of these challenges will support SC development concerning the IS security management in IoT-enabled SC.

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Section: Integritymentioning

confidence: 99%

Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review

2021

Adv. sci. technol. eng. syst. j.

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“…An IDS is a tool that scans network traffic for any harmful activity or policy breaches. It is a system for monitoring network traffic for malicious activities and alerting network administrators to such abnormal activities [13]. IDSs achieve this by gathering data from several systems and network sources and analyzing those data for possible threats.…”

Section: Intrusion Detection Systemsmentioning

confidence: 99%

Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset

et al. 2020

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Due to the extensive use of computer networks, new risks have arisen, and improving the speed and accuracy of security mechanisms has become a critical need. Although new security tools have been developed, the fast growth of malicious activities continues to be a pressing issue that creates severe threats to network security. Classical security tools such as firewalls are used as a first-line defense against security problems. However, firewalls do not entirely or perfectly eliminate intrusions. Thus, network administrators rely heavily on intrusion detection systems (IDSs) to detect such network intrusion activities. Machine learning (ML) is a practical approach to intrusion detection that, based on data, learns how to differentiate between abnormal and regular traffic. This paper provides a comprehensive analysis of some existing ML classifiers for identifying intrusions in network traffic. It also produces a new reliable dataset called GTCS (Game Theory and Cyber Security) that matches real-world criteria and can be used to assess the performance of the ML classifiers in a detailed experimental evaluation. Finally, the paper proposes an ensemble and adaptive classifier model composed of multiple classifiers with different learning paradigms to address the issue of the accuracy and false alarm rate in IDSs. Our classifiers show high precision and recall rates and use a comprehensive set of features compared to previous work.

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“…Powering the IDPS system with ML, SDN, and MUD proving to be useful. IDPS system becomes a lot more effective and worthy for network security as in paper [7] presented an updated review on the IDPS systems. It shows the classification of IDPS systems and their role in securing the conventional network.…”

Section: B Related Workmentioning

confidence: 99%

“…To mitigate these kinds of attacks, the researchers suggest the IDPS. This system is not visible to the attackers thus restricts the communication to the other components of the network [7]. The taxonomy of IDPS in IoT is given in Fig.…”

Section: B Overview Of Intrusion Detection and Prevention Systemmentioning

confidence: 99%

SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey

Mazhar¹,

Salleh²,

Hossain³

et al. 2020

IJACSA

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Intrusion Detection and Prevention Systems: An Updated Review

Cited by 54 publications

References 4 publications

Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review

Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review

Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset

SDN based Intrusion Detection and Prevention Systems using Manufacturer Usage Description: A Survey

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