21,344 Hits in 11.7 sec

Cyber Security Based on Artificial Intelligence for Cyber-Physical Systems

Hichem Sedjelmaci, Fateh Guenab, Sidi-Mohammed Senouci, Hassnaa Moustafa, Jiajia Liu, Shuai Han
2020 IEEE Network  
In "Learning-Assisted Secure End-to-End Network Slicing for Cyber-Physical Systems," the authors highlight the security issues of network slicing, study the machine learning solution to secure the slices  ...  Based on a machine learning algorithm and edge computing system, the authors develop two buffer queues to reduce the coupling degree of the system in parallel.  ...  In "Machine Learning based Side-Channel Leakage Detection in Electronic System-Level Synthesis," the authors propose a machine learning algorithm based on a clustering approach to achieve faster and more  ... 
doi:10.1109/mnet.2020.9105926 fatcat:hpx7lcbezvfsxlkm336k2si7ae

A Machine Learning Security Framework for IoT Systems

Miloud Bagaa, Tarik Taleb, Jorge Bernal Bernabe, Antonio Skarmeta
2020 IEEE Access  
This paper presents a novel machine learning (ML) based security framework that automatically copes with the expanding security aspects related to IoT domain.  ...  Regarding our anomalybased intrusion detection system (IDS) for IoT, we have evaluated the experiment in a real Smart building scenario using one-class SVM.  ...  This component uses a trained machine learning models based on network patterns and IoT behaviors for detecting threats.  ... 
doi:10.1109/access.2020.2996214 fatcat:qu2fq5t7pjejhd7wkj4lrprvoe

Malware threat analysis techniques and approaches for IoT applications: a review

Chimeleze Collins Uchenna, Norziana Jamil, Roslan Ismail, Lam Kwok Yan, Mohamad Afendee Mohamed
2021 Bulletin of Electrical Engineering and Informatics  
In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications.  ...  This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.  ...  [29] Agent-based malware detection (AMD) architecture for securing high-risk virtual machine (VM) from malware at the initial stage of VM life cycle.  ... 
doi:10.11591/eei.v10i3.2423 fatcat:tmkgezmv5ngcblgcxr6bmbqd3q

A Survey of Malware Risk Detection Techniques in Cloud

Ahmad Faiz Ghazali
2021 Turkish Journal of Computer and Mathematics Education  
This article aims to contribute in securing information technology (IT) systems and processes for information security by utilizing malware risk detection for decision-making processes to mitigate cyber-attacks  ...  Therefore, this article presents a survey of malware risk detection techniques in cloud. The survey was conducted on publications from Scopus from the last 5 years.  ...  This method uses an agent called viz that is guided by a virtual machine (VM) and an anomaly detection component runs on the VM's hypervisor.  ... 
doi:10.17762/turcomat.v12i3.797 fatcat:b64pm4nrcvbddm7xkc2hdvbyeq

Mitigating IP Spoofing to Enhance Security in Multi-Agent based e-Learning Environment

K. Shyamala, Shantha Visalakshi
2015 Indian Journal of Science and Technology  
IP spoofing must be detected and blocked in order to provide e-learning as a service to authenticate users of the system which is analyzed in this paper.  ...  the e-learning systems.  ...  multi-agent based content retrieval system can be implemented to achieve a secure e-learning content retrieval and management system. packet is discarded.  ... 
doi:10.17485/ijst/2015/v8i17/63910 fatcat:m7cbig5htvf2dpaga6pxdiebpy

Detection of Malware Attacks on Virtual Machines for a Self-Heal Approach in Cloud Computing using VM Snapshots

Linda Joseph, Rajeswari Mukesh
2018 Journal of Communications Software and Systems  
A machine learning approach is projected here to classify the attacked and non attacked snapshots. The features of the snapshots are gathered from the API calls of VM instances.  ...  The self-healing approach with machine learning algorithms can determine new threats with some prior knowledge of its functionality.  ...  Threats can affect the virtual machine manager, the virtual machines itself, the operating systems in the VM instances, the applications running on these Oss and the network.  ... 
doi:10.24138/jcomss.v14i3.537 fatcat:llz2cuqttfgnrei5wuboq6fvaa

Virtual Memory Introspection Framework for Cyber Threat Detection in Virtual Environment

Himanshu Upadhyay, Hardik Gohel, Alexander Pons, Leo Lagos
2018 Advances in Science, Technology and Engineering Systems  
In this paper, we propose a novel framework design that uses virtualization to isolate and monitor Linux environments.  ...  Recent widely reported hacking attacks on reputable organizations have mostly been on Linux servers. Most new malwares are able to neutralize existing defenses on the Linux operating system.  ...  This system is hosted on a Xen hypervisor based virtualization platform.  ... 
doi:10.25046/aj030104 fatcat:igixghustzhhxn7e37ye5d5ble

A Smart Agent Design for Cyber Security Based on Honeypot and Machine Learning

Nadiya El Kamel, Mohamed Eddabbah, Youssef Lmoumen, Raja Touahni
2020 Security and Communication Networks  
In this paper, we present an introduction of machine learning and honeypot systems, and based on these technologies, we design a smart agent for cyber-attack prevention and prediction.  ...  With the development of network attack techniques, every host on the Internet has become the target of attacks. Therefore, the network information security cannot be ignored as a problem.  ...  Smart Agent for Cyber Security Attacks Prevention and a Prediction-Based Machine Learning and Honeypot System Companies have invested a great deal on time and money in manual networks reconfiguration,  ... 
doi:10.1155/2020/8865474 fatcat:daepvtw72zgmhifyxmd5f4px6q

Study of Machine Learning for Cloud Assisted IoT Security as a Service

Maram Alsharif, Danda B. Rawat
2021 Sensors  
Machine learning (ML) has been emerging as a viable solution for intrusion detection systems (IDS) to secure IoT devices against different types of attacks.  ...  ML based IDS (ML-IDS) normally detect network traffic anomalies caused by known attacks as well as newly introduced attacks.  ...  Susilo et al. examined machine learning Random Forests (RF), Support Vector Machine (SVM) and deep learning Multilayer Perception (MLP), Convolutional Neural Network (CNN) algorithms for network-based  ... 
doi:10.3390/s21041034 pmid:33546394 fatcat:6uxbwk6e3ncsjloe4vabcncgby

Evolution of network enumeration strategies in emulated computer networks

Sean Harris, Eric Michalak, Kevin Schoonover, Adam Gausmann, Hannah Reinbolt, Joshua Herman, Daniel Tauritz, Chris Rawlings, Aaron Scott Pope
2018 Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '18  
This paper presents an evolutionary framework for evolving attacker agents in a real, emulated network environment using genetic programming, as a foundation for coevolutionary systems which can automatically  ...  Regardless of the security elsewhere, a skilled attacker can exploit a single vulnerability in a defensive system and negate the benefits of those security measures.  ...  ACKNOWLEDGEMENTS This work was supported by Los Alamos National Laboratory via the Cyber Security Sciences Institute under subcontract 259565.  ... 
doi:10.1145/3205651.3208270 dblp:conf/gecco/HarrisMSGRHTRP18 fatcat:ywkpy6efhbdvtixnpntccfnete

A review on biologically inspired approaches to security for Internet of Things (IoT)

Reshma Banu, G. F. Ali Ahammed, Nasreen Fathima
2016 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)  
Biologically inspired models for security have been more flourishing to put up the wonderful defense in securing ad hoc networks.  ...  Because of the features of ad hoc network, they require a strong, decentralized security mechanism.  ...  Machine learning based biologically inspired system can be divided into three essential blocks: • Machine learning algorithm to classify data into fraudulent or legal nodes. • Generation of virtual antibodies  ... 
doi:10.1109/iceeot.2016.7754848 fatcat:afobuqmyhbc2zbyotkmtzmzwgm

A Taxonomy of Virtualization Security Issues in Cloud Computing Environments

Nadiah M. Almutairy, Khalil H. A. Al-Shqeerat, Husam Ahmed Al Hamad
2019 Indian Journal of Science and Technology  
Furthermore, fifteen main virtualization threats and attacks are defined according to exploited vulnerabilities in a cloud environment.  ...  In this study, the systematic literature review is performed to find out the vulnerabilities and risks of virtualization in cloud computing and to identify threats, and attacks result from those vulnerabilities  ...  In general, the virtualization is based on a hypervisor.  ... 
doi:10.17485/ijst/2019/v12i3/139557 fatcat:es5fn7pxcvaqtocri6qen7ccj4

Cybersecurity challenges in energy sector (virtual power plants) - can edge computing principles be applied to enhance security?

Sampath Kumar Venkatachary, Annamalai Alagappan, Leo John Baptist Andrews
2021 Energy Informatics  
This paper aims to present a comprehensive Edge-based security architecture to help reduce the risks and help secure the physical systems and ensure privacy and data protection.  ...  Recent technological advancements have aided cybercriminals to disrupt operations by carrying out deliberate attacks on the energy sector.  ...  The use of A.I. and machine learning algorithms in the security layer could significantly change the dynamics of security due to learning from multiple sources.  ... 
doi:10.1186/s42162-021-00139-7 fatcat:x6r4viitbfekndinlbbhkujhne

Cloud Computing Security Using IDS-AM-Clust, Honeyd, Honeywall and Honeycomb

Chaimae Saadi, Habiba Chaoui
2016 Procedia Computer Science  
This work proposes new cloud infrastructure architecture, which combines IDS based on mobile agent sand using three types of honeypots in order to detect attacks, to study the behavior of attackers, increase  ...  the added value of Honeypot and IDS based mobile agents, solve systems limitations intrusion detection, improve knowledge bases IDS thus increase the detection rate in our cloud environment.  ...  This may be done by using intrusion detection sensors installed in a virtual machine to sniff network traffic and analyze packets on the Internet using Snort.  ... 
doi:10.1016/j.procs.2016.05.189 fatcat:l4lc6tfghjc5nml636w5xk2tuu

Towards a Multi-Agent based Network Intrusion Detection System for a Fleet of Drones

Said OUIAZZANE, Fatimazahra BARRAMOU, Malika ADDOU
2020 International Journal of Advanced Computer Science and Applications  
Multi-agent systems can perfectly address the security problem of a drone fleet, given the mobility, autonomy, cooperation and distribution characteristics present in the network linking the different  ...  Keywords-Fleet of drones; drone; intrusion detection; multi agent system; security; intrusion detection system; autonomy; distribution; UAV; unmanned aerial vehicle; unknown attacks; known attacks have  ...  The AIS system is based on autonomous, mobile, collaborative, adaptive and learning agents.  ... 
doi:10.14569/ijacsa.2020.0111044 fatcat:i5gnv5a4bbgdnmsxkkzxpir6em
« Previous Showing results 1 — 15 out of 21,344 results