Raspberry Pi as an Intrusion Detection System, a Honeypot and a Packet Analyzer

Tripathi, Shyava; Kumar, Rishi

doi:10.1109/ctems.2018.8769135

Cited by 17 publications

(10 citation statements)

References 8 publications

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“…However, NetGaurd is nothing different to a traditional IDS and just provides privacy by hiding the IP of the monitoring source, as an extra feature. There are few other similar implementations like [23,24]. The mere purpose of these implementation is to install and test IDS software on Raspberry Pi for various purposes.…”

Section: Iot Based Ids Implementationsmentioning

confidence: 99%

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Tirumala

Nepal²,

Ray

2022

EAI Endorsed Trans Smart Cities

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Ongoing ransomware attacks have forced business to think about security of their resources. Recently, small- to-medium enterprises (SMEs) and Smart-homes have become easy targets for attackers since they don’t have cyber defense mechanism in place other than simple firewall systems which are quite vulnerable. Cyber defense systems are costly and often not within the budget of SMEs or families which inspired to think about low cost yet highly efficient cyber defense solutions. Regular individuals and families who use internet for day to day use often end-up becoming a possible resource for using them as Trojan or bitcoin nodes. This research explores the prospects of implementing a Raspberry Pi (Raspberry Pi)-based intelligent cyber- defense system (iCDS) for SME networks and Smart-homes to filter malicious contents from incoming traffic and detect malware using artificial intelligence. Primarily, the work presented in this paper tries to evaluate the hardware capability of network interfaces (both internal, and attached) of Raspberry Pi for handle high volumes of incoming traffic. For this, we measure the network performance of the Raspberry Pi using the speed test software and try to explore the possibility of a light weight machine learning (ML) based malware detection. The results show that the built in Ethernet interface outperforms the built in WiFi and external attached USB to Ethernet Adapter in terms of latency, download and upload throughput. Also, a new DNA based ML approach was successfully able to produce over 19.5% better accuracy rates of over classifier trained with hash-sequence. The experiment results further emphasise on the importance of generating complex malware signatures with variety to face existing threats which has taken a new form due to increase in malware based attacks, particularly for ransomware. The complexity of the generated malware is based on generic yet strong encryption principles which produced good results which is quite encouraging at this stage.

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Section: Iot Based Ids Implementationsmentioning

confidence: 99%

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Tirumala

Nepal²,

Ray

2022

EAI Endorsed Trans Smart Cities

View full text Add to dashboard Cite

show abstract

“…For example, Kutukian (2016) implements the network monitoring tools on Raspberry Pi 3 to enable network admin to get fully monitoring access against networking hardware such as router, firewall and core switch. Several studies focus in intrusion detection system using Raspberry Pi for network monitoring and security were established (Osman et al, 2016;Tripathi & Kumar, 2018;Sumanth & Bhanu, 2020).…”

Section: Related Workmentioning

confidence: 99%

Enhancing Security and Privacy in Local Area Network (LAN) with TORVPN Using Raspberry Pi as Access Point: A Design and Implementation

Osman

Sedek

Othman

et al. 2021

JCRINN

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Network security is designed to protect the integrity, confidentiality and accessibility of computer networks and data using both software and hardware technologies. Every person, including organization requires a degree of network security solutions in place to protect it from the ever-growing landscape of cyber threats in the wild today. This paper aims to design and implement TorVPN as an access point using Raspberry Pi in enhancing security and privacy in Local Area Network (LAN). This access point was implemented by using the combination of The Onion Router (Tor) and Virtual Private Network (VPN) services. Then, the graphical user interface application was developed to assist and facilitate the user to access the network securely without having the difficulties to configure and install any software. To determine the effectiveness of the proposed work, there were two experiments involved in this study. Firstly, the confidentiality test which to verify its privacy in keeping the information securely. Secondly, the performance test of the Internet connectivity in terms of ping, download and upload speed. The encourage results was expected as the confidentiality tested on the TorVPN access point network has shown the positive outcome by securing client’s Internet data packet. While, the Internet connectivity is not stable enough, when the client’s IP address changed in the network. Hence, the combination VPN and Tor service using Raspberry Pi as an access point inside the LAN is suitable and secure the information in the network, but do not suggest for user who wants a good Internet connectivity.

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“…The IDS studies [5,[19][20][21][22][23][24][25][26][27] also have proposed attack detection based on Raspberry Pi. In the work of [18], the anomaly-based detection method was proposed by capturing the previous traffic patterns asbenign data for attack detection system construction.…”

Section: Raspberry Pi-based Idsmentioning

confidence: 99%

Towards a Lightweight Detection System for Cyber Attacks in the IoT Environment Using Corresponding Features

et al. 2020

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The application of a large number of Internet of Things (IoT) devices makes our life more convenient and industries more efficient. However, it also makes cyber-attacks much easier to occur because so many IoT devices are deployed and most of them do not have enough resources (i.e., computation and storage capacity) to carry out ordinary intrusion detection systems (IDSs). In this study, a lightweight machine learning-based IDS using a new feature selection algorithm is designed and implemented on Raspberry Pi, and its performance is verified using a public dataset collected from an IoT environment. To make the system lightweight, we propose a new algorithm for feature selection, called the correlated-set thresholding on gain-ratio (CST-GR) algorithm, to select really necessary features. Because the feature selection is conducted on three specific kinds of cyber-attacks, the number of selected features can be significantly reduced, which makes the classifiers very small and fast. Thus, our detection system is lightweight enough to be implemented and carried out in a Raspberry Pi system. More importantly, as the really necessary features corresponding to each kind of attack are exploited, good detection performance can be expected. The performance of our proposal is examined in detail with different machine learning algorithms, in order to learn which of them is the best option for our system. The experiment results indicate that the new feature selection algorithm can select only very few features for each kind of attack. Thus, the detection system is lightweight enough to be implemented in the Raspberry Pi environment with almost no sacrifice on detection performance.

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Raspberry Pi as an Intrusion Detection System, a Honeypot and a Packet Analyzer

Cited by 17 publications

References 8 publications

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Enhancing Security and Privacy in Local Area Network (LAN) with TORVPN Using Raspberry Pi as Access Point: A Design and Implementation

Towards a Lightweight Detection System for Cyber Attacks in the IoT Environment Using Corresponding Features

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