Tips for developing intrusion detection system and significance of machine learning technique in a cloud platform

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DISSERTATION ALGORITHM DEVELOPMENT TIPS FOR
DEVELOPING INTRUSION DETECTION SYSTEM AND
SIGNIFICANCE OF MACHINE LEARNING TECHNIQUE IN A
CLOUD PLATFORM
Research Paper
Dissertation Algorithm Development Ideas from
Existing Recent Research Gaps in Computer
Science Engineering Domain Trending Research
Methodologies In Cloud Computing, Engineering
Technology
TagsTutors India Computer Science Dissertation
Topics Topics in Computer Science Computer
Science dissertation help
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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)
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IDS is a security tool which monitors and
captures the scans the system / network, system
logs and/or traffic for suspicious activities
network.
To detect malicious activity like port scans,
DoS attacks, even attempts toward crack into
computers whereas NIDS monitors network traffic.
03
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It alerts the system or cloud administrator
about the network attacks.
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LIFECYCLE OF GREEN PRODUCTS
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algorithm and coding implementation to
efficiently reduce network traffic for your
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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. T
o monitor the efficiency of HIDS, it depends on
the selected system features.
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dissertation and assignment in computer science
research with assured 21 distinction.
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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)
Tutors India develop ML algorithms using
Python, Hadoop framework and many more to booth
secure access control in cloud computing
platforms.
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Hy
is running at the hypervisor layer.
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monitor the communications amongst VMs,
within the hypervisor-based virtual network
and hypervisor and VM based network.
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In addition, data availability is one of the
benefits of HY-IDS.
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SUMMARY
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.
This section has discussed the importance of
machine learning technique and detection of
network traffic over the cloud environment.
Tutors India has vast experience in developing
dissertation research topics for students
pursuing the UK dissertation in computer science.
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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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