Analysis and Performance Evaluation of Application Specific Processors for Network-Based Intrusion Detection Systems

Author(s):  
Majid Nezakatolhoseini ◽  
Sam Jabbehdari ◽  
Mohammad Ali Pourmina
Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 629 ◽  
Author(s):  
Junaid Arshad ◽  
Muhammad Ajmal Azad ◽  
Roohi Amad ◽  
Khaled Salah ◽  
Mamoun Alazab ◽  
...  

Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.


2011 ◽  
Vol 5 ◽  
pp. 173-180 ◽  
Author(s):  
Adeeb Alhomoud ◽  
Rashid Munir ◽  
Jules Pagna Disso ◽  
Irfan Awan ◽  
A. Al-Dhelaan

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Wathiq Laftah Al-Yaseen ◽  
Zulaiha Ali Othman ◽  
Mohd Zakree Ahmad Nazri

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modifiedK-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modifiedK-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.


2006 ◽  
Vol 65 (10) ◽  
pp. 929-936
Author(s):  
A. V. Agranovskiy ◽  
S. A. Repalov ◽  
R. A. Khadi ◽  
M. B. Yakubets

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