Tips for developing IDS and significance of machine learning technique in a cloud platform

Research Paper

DISSERTATION ALGORITHM DEVELOPMENT TIPS FOR DEVELOPING INTRUSION DETECTION SYSTEM AND SIGNIFICANCE OF MACHINE LEARNING TECHNIQUE IN A CLOUD PLATFORM Dissertation Algorithm Development Ideas from Existing Recent Research Gaps in Computer Science Engineering Domain

Trending Research Methodologies In Cloud Computing, Engineering & Technology

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TutorsIndia Lab @ TutorsIndia.Com Engineering & technology (E&T) Lab at TutorsIndia is involved in exploring novel research areas by conducting dynamic research. It promotes innovation in all fields of engineering by advancing the technology with structured and continuous research. The problems and challenges faced by the existing technologies and trends are explored by our researchers exists in scholarly literature, in theory, or in practices that needs deliberate investigation. These problems are identified and fixed by our researchers by suggesting better novel alternatives with appropriate tools, technologies and approaches, thereby proving their effectiveness in real time applications.

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SHORT NOTES You will find the best dissertation research areas / topics for future researchers enrolled in computer science engineering. These topics are researched in-depth at the University of Glasgow, UK, Sun Yat-sen University, University of St Andrews and many more.

In order to identify the future research topics, we have reviewed the computer science literature (recent peer-reviewed studies) on the security and privacy issues in the cloud environment for efficient cloud service provisioning.

Various researches have revealed that there is a possibility to minimize the security errors and develop a secure cloud model using machine learning.

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BACKGROUND The Machine Learning (ML) technique is used for analysing and extracting useful information from the database.

ML techniques in intrusion detection system (IDS) has been looked into broadly because of its capability to give promising answers for automating detection of abnormal traffic patterns or attacks in a real-time network.

It is essential to comprehend the importance and purposes for intrusion detection results that are delivered by ML models.

Numerous investigations concentrating on the utilization of ML in IDS have introduced improved outcomes when contrasting and different procedures, there isn't a lot of importance on understanding the purposes behind the lower misclassification rates or improved outcomes.

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INTRUSION DETECTION SYSTEM (IDS)

IDS is a security tool which monitors and captures the scans the system / network, system logs and/or traffic for suspicious activities network.

01

03

To detect malicious activity like port scans, DoS attacks, even attempts toward crack into computers whereas NIDS monitors network traffic.

02 It alerts the system or cloud administrator about the network attacks.

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Hire Tutors India experts to develop your algorithm and coding implementation to efficiently reduce network traffic for your Computer Science dissertation Services.

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HOST-BASED INTRUSION DETECTION SYSTEMS (HIDS) Host-based IDS analyse and monitor the data which has been gathered from particular host machine.

Collecting data from network events, file system and system calls, the HIDS detect intrusion of specific machine.

It reports the presence of network attack upon detection of deviation from expected performance/behaviour.

To monitor the efficiency of HIDS, it depends on the selected system features.

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DISTRIBUTED INTRUSION DETECTION SYSTEM (DIDS)

DIDS comprises the different IDS, for instance, NIDS and HIDS where it enables network monitoring or communicates with each other over a large network.

Intrusion detection mechanism gathers the details about system data then convert into a consistent form to be conceded to central analyser (CA).

Analysis process, the hybrid combination of signature and anomaly-based detection approach were used.

Distributed IDS are used to detect both unknown and known attacks.

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HYPERVISOR BASED IDS (HY-IDS)

2

is running at the hypervisor layer.

monitor the communications amongst VMs, within the hypervisor-based virtual network and hypervisor and VM based network.

3

In addition, data availability is one of the benefits of HY-IDS.

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Tutors India develop ML algorithms using Python, Hadoop framework and many more to booth secure access control in cloud computing platforms.

1

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SUMMARY

This section has discussed the importance of machine learning technique and detection of network traffic over the cloud environment.

Also, we have recommended a solution for an effective model for both detection of known and unknown network traffic and prevention model of cloud resource over the network.

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RECOMMENDATIONS To explore IDS based on Deep Neural Network will give better with respect to search space, intrusion detection and prevention of network traffic information.

Simulated annealing based optimization method will be applicable to select the best set of values of parameters that involves in the building of IDS. It may avoid the error as well as manual tuning of parameters.

To detect intrusions within encrypted packets by incorporating machine learning technique with meta-heuristic algorithms like artificial bee colony (ABC), particle swarm optimization, crow search algorithm, ant colony optimization (ACO).

Needs to improve the prediction performance with respect to expected intensity, type of attack or target parameters by using deep learning methods.

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