Filters








468 Hits in 5.9 sec

Unsupervised Monitoring of Networkand Service Behaviour Using SelfOrganizing Maps

Duc C. Le, A. Nur Zincir-Heywood, Malcolm I. Heywood, Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada, Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada, Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
2018 Journal of Cyber Security and Mobility  
The results show that the approach has a high potential as a data analytics tool on unknown traffic/web service requests, and unseen attack behaviours.  ...  The approach is evaluated on publicly available network traffic (flows) and web server access (web requests) datasets.  ...  Acknowledgments This research is funded through the Canadian Safety and Security Program (CSSP), a federally-funded program led by Defence Research and Development Canada's Centre for Security Science  ... 
doi:10.13052/jcsm2245-1439.812 fatcat:jvutnccf75fb5ls6osvsmn7jb4

Peer Based Tracking using Multi-Tuple Indexing for Network Traffic Analysis and Malware Detection

Matthew Hagan, BooJoong Kang, Kieran McLaughlin, Sakir Sezer
2018 2018 16th Annual Conference on Privacy, Security and Trust (PST)  
Index Terms-5-tuple flow tables, Zeus botnet, Network Behavioural detection, Next generation firewall I.  ...  For example, rule matches on packets of a particular size, at regular intervals are relevant for detecting ZeuS traffic.  ... 
doi:10.1109/pst.2018.8514165 dblp:conf/pst/HaganKMS18 fatcat:735x53znp5cprna5auvu4ikhkq

An Advanced Method for Detection of Botnet Using Intrusion Detection System

Alan Saji
2021 International Journal for Research in Applied Science and Engineering Technology  
A botnet, especially with remote-controlled bots that offers a platform for many cyber threats.  ...  The IDS (PI-IDS) check for payload detects energetic tries to test the user's statistics gram protocol (UDP) and transmission manage protocol (TCP) comparisons with acknowledged attacks but the PI-IDS  ...  All botnet flow records are successfully extracted using specific 1connection process and setting object vectors that differ from the botnet network traffic and the performance of its process.  ... 
doi:10.22214/ijraset.2021.37945 fatcat:qaekwelnvjcczd4plowbv3qmwq

Review on Botnet Threat Detection in P2P

Mohini N.
2015 International Journal on Recent and Innovation Trends in Computing and Communication  
The automatic detection of botnet traffic is of high importance for service providers and large campus network monitoring.  ...  This paper gives the review on the various techniques used to detect such botnets.  ...  automatic flow correlation, behavioural procedure.  ... 
doi:10.17762/ijritcc2321-8169.150266 fatcat:xr5bsjrzr5aw7mald5llbcoqvu

Cyber Attack Detection thanks to Machine Learning Algorithms [article]

Antoine Delplace, Sheryl Hermoso, Kristofer Anandita
2020 arXiv   pre-print
This paper explores Machine Learning as a viable solution by examining its capabilities to classify malicious traffic in a network.  ...  The Random Forest Classifier succeeds in detecting more than 95% of the botnets in 8 out of 13 scenarios and more than 55% in the most difficult datasets.  ...  BClus creates a model of known botnet behaviours and uses them to detect similar traffic on the network.  ... 
arXiv:2001.06309v1 fatcat:3rla7q4nxzgcpokiwzvf6tiblu

Bot Net Detection for Network Traffic using Ensemble Machine Learning Method

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Denial of Service) attacks, virtual deceit and distributed resource usage for cryptocurrency mining.The main aim f botnet is to steal private data of clients,sendind spam and viruses and DOS attacks in  ...  the network.  ...  Hence a real time solution is required for the detection of botnet attacks. This work utilizes the machine learning approach for the detection of botnet in network traffic.  ... 
doi:10.35940/ijitee.a8122.1110120 fatcat:pxo6mwnlabhzxkspt4agv3p2ai

SDN Framework for Securing IoT Networks [chapter]

Prabhakar Krishnan, Jisha S. Najeem, Krishnashree Achuthan
2017 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
In this paper, we discuss major security challenges in IoT networks and present the notion of security architecture for IoT based on programmable and virtualization technologies SDN/NFV, explain the architectural  ...  choices and its applications for IoT.  ...  Essentially the botnet detection logic is implemented based on traffic flow analysis at the SDN switch itself. 2.  ... 
doi:10.1007/978-3-319-73423-1_11 fatcat:fdyjkwosu5aqxkq6qfvtjyyi6i

Classification of device behaviour in internet of things infrastructures

Roman Ferrando, Paul Stacey
2017 Proceedings of the 1st International Conference on Internet of Things and Machine Learning - IML '17  
A novel approach to security detection using streaming data analytics to classify and detect security threats in their early stages is proposed.  ...  Implementation methodologies and results of ongoing work to realise this new IoT cyber-security technique for threat detection are presented.  ...  IoT traffic is not the only traffic flowing on the network therefore, It is safe to assume that changes in the network circumstances (e.g.  ... 
doi:10.1145/3109761.3109791 dblp:conf/iml/FerrandoS17 fatcat:up3hco7jhbdpbnuaj2hmea75ue

Benchmark-Based Reference Model for Evaluating Botnet Detection Tools Driven by Traffic-Flow Analytics

Katherinne Shirley Huancayo Ramos, Marco Antonio Sotelo Monge, Jorge Maestre Vidal
2020 Sensors  
The proposal relies on observing, understanding and inferring the behavior of each botnet family based on network indicators measured at flow-level.  ...  The experimental validation was performed on two public datasets of real botnet traffic—CIC-AWS-2018 and ISOT HTTP Botnet.  ...  On the other hand, anomaly-based IDS profile the behaviour of network traffic in order to detect deviations when no traffic categorization can be performed [30] .  ... 
doi:10.3390/s20164501 pmid:32806550 fatcat:d4udmyk5uveqfhqud4g7jfzd6m

Systematic Literature Review on IoT-Based Botnet Attack

Ihsan Ali, Abdelmuttlib Ibrahim Abdalla Ahmed, Ahmad Almogren, Muhammad Ahsan Raza, Syed Attique Shah, Anwar Khan, Abdullah Gani
2020 IEEE Access  
The method retrieves behaviour snapshots of a given network and utilises autoencoders to detect suspicious network traffic from suspicious IoT devices.  ...  traffic Detection accuracy and detec- tion time Detection 5 A30 DNS traffic Precision, recall, and F-measure Detection 5 A31 Network traffic Botnet reduction time Avoidance 4 A32 Network  ... 
doi:10.1109/access.2020.3039985 fatcat:dm4wxdvsfjbgff6gftca4gtahu

Application of distributed computing and machine learning technologies to cybersecurity

Hamza Attak, Marc Combalia, Georgios Gardikis, Bernat Gastón, Ludovic Jacquin, Dimitris Katsianis, Antonis Litke, Nikolaos Papadakis, Dimitris Papadopoulos, Antonio Pastor, Marc Roig, Olga Segou
2018 Zenodo  
The Data Analysis and Remediation Engine executes security analytics modules on top of monitoring data modules in order to detect threats.  ...  The security analytics heavily leverage Machine Learning algorithms for detecting anomalies and classifying threats.  ...  This makes for a very promising anomaly detection technique in cybersecurity based on big network flows.  ... 
doi:10.5281/zenodo.3266038 fatcat:3hp3onsq2zemzckcegscpfipjq

A Survey of Intrusion Detection Using Deep Learning in Internet of Things

baraa I. Farhan, Ammar D.Jasim
2022 Iraqi Journal for Computer Science and Mathematics  
In this paper we present a survey about the detection of anomalies, thus intrusion detection by distinguishing between normal behavior and malicious behavior while analyzing network traffic to discover  ...  To evaluate the performance we show accuracy measurement for detect intrusion in different systems.  ...  of potential of using DL for anomaly detection system based on the flow [32] .  ... 
doi:10.52866/ijcsm.2022.01.01.009 fatcat:ttdhhdmqr5gzvo32j66ofiouua

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences [article]

Joseph Gardiner, Marco Cova, Shishir Nagaraja
2015 arXiv   pre-print
We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels.  ...  Of the techniques that do address P2P botnets, detection is again dependent on specifics regarding control traffic ports, network behaviour of certain types of botnets, reverse engineering botnet protocols  ...  • Storing network traffic and alerts in logs analytics systems for further analysis and inspection. • Deploying NIDS to monitor the network traffic looking for signs of infection.  ... 
arXiv:1408.1136v2 fatcat:dhhjzhq44rgqxojwfaw324ehh4

Towards Situational Awareness of Botnet Activity in the Internet of Things

Christopher D. McDermott, Andrei V. Petrovski, Farzan Majdani
2018 2018 International Conference On Cyber Situational Awareness, Data Analytics And Assessment (Cyber SA)  
and modelling the behaviour of network flows.  ...  Botnet Detection Methods As previously stated much of the existing literature on botnet detection generally focuses on traditional network botnets, rather than IoT botnets.  ... 
doi:10.1109/cybersa.2018.8551408 dblp:conf/cybersa/McDermottPM18 fatcat:ihsy2qmiwzfqxfleqguvctsofe

A Supervised Classification Approach for Detecting Packets Originated in a HTTP-based Botnet

Félix Brezo, José Gaviria de la Puerta, Xabier Ugarte-Pedrero, Igor Santos, Pablo G. Bringas, David Barroso
2013 CLEI Electronic Journal  
In this document, the authors propose a methodology thought to detect malicious botnet traffic, based on the analysis of the packets that flow within the network.  ...  This objective is achieved by means of the extraction of the static characteristics of packets, which are lately analysed using supervised machine learning techniques focused on traffic labelling so as  ...  the extraction of the experimental traffic samples needed for the achievement of this research.  ... 
doi:10.19153/cleiej.16.3.2 fatcat:5cgqafq3ubb2zdcomb5qhh7pqy
« Previous Showing results 1 — 15 out of 468 results