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V2212790 V1
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V2212790 V1
Data Ethics and Research Methods
Module Code: MMI226823
Student Name and ID:
Referencing: Harvard
Title/Topic: Proactive Hunting of Cyber Threats with Secure AI-powered
advance endpoint detection and response
Chapter 1: Introduction
(i) Background
Arti*cial intelligence is the simulation of human behaviour in a machine
(Bresniker et al., 2019). They are programmed in a way that makes machines
think like humans and also mimic human behaviours. There are many
applications of AI. One such application area is in analyzing the cyber risk and
theta area. In today’s world, the most system runs digitally and over the

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internet. As a result these sites, are highly susceptible to cyber-attacks and
threats. With Secure AI’s advanced endpoint detection and response
technique, these threats can be hunted down for making the systems secure
and effective for the users (Tmobile, 2022).
(ii) Research Questions
The following research questions will be addressed through the study.
RQ 1: Why is secure AI the best method for hunting cyber threats?
RQ2: How applicable is secure AI’s endpoint detection and response technique
when it comes to hunting cyber threats?
(iii) Description of the research problem and research-issue
In companies and organizations, even with tight lockdowns and security means
it is inevitable that a threat gets past the *rst line of defence. Whenever this
incident occurs. The organization would be needing speci*c tools which can
proactively patrol their environment while identifying and eliminating any
threat associated with the system. This particular type of security can be
appropriated using Arti*cial Intelligence or Secure AI. The secure AI can
proactively hunt and also respond to several threats and malicious behaviour
across a systems endpoint like in PC. laptop, servers. This is done by examining
data behaviour and certain abnormalities.
(iv) Goal of the study
The goal of the literature review section would be to have a critical and
comprehensive analysis of the state of the art of the selected research topic by
examining the work and perception of other writers. The goal of the spiral
evaluation would be to identify some common or basic approach and solution

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to the given topic on a testbed setup with the help of some relevant software
toolkit and framework.
Chapter 2: Literature Review
2.1 Taxonomy
The taxonomy of the study is presented in the table shown below.
Research outcome: Determine how Secure AI can hunt cyber theta through
endpoint detection and response measures.
Research methods: Systematic literature review method
Theories related to a cyber security threat and secure AI are to be assessed.
The application of secure AI endpoint detection for cyber threat mitigation to be
To address the proposed research question.
Identifying the research central issue
Neutral -representation
Espousal for a position.

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Organizations who want to prevent cyber threats with secure AI.
Students who wish to participate in AI focussed cyber security detection.
Scholars and researchers.
Table 1: Taxonomy of Research
(Source: Adopted from Glock, 2022)
2.2 Overview of an existing approach, elaboration of major approaches and
According to the industry report named “4 robust-solution-to-*ght cyber
criminals”, in the year 2019, cybercrime cost businesses around 2 trillion USD
IN revenue loss (Tmobile (c), 2022). The report also states that by the end of
2022, worldwide spending on cybersecurity will reach around 133.7 billion USD.
This indicated or re+ected upon the fact that organizations need to be serious
and concentrate more on addressing the cyber threat to the earliest stage as
otherwise the organization is bound to expense loss of assets and money from
the cyber attacks.
Truong et al., (2020), highlighted that there has been an everlasting demand for
robust security upon the evolving technology. Since the need for security
measures is increasing, conventional solutions would not be capable enough to
provide security to advanced threats like various DoS attacks, malicious
attacks, bugs, and malware. For addressing these issues, ef*cient and +exible

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“security methods” are very important. In this context, it is important to note
that the *rst line of security defence like the *rewall, user authentication, and
data encryption are not quite appropriate or enough for covering the whole
system’s “security need” and covering certain challenges while considering the
everlasting-intrusion methods. Tmobile (2022), reported that even if
organizations possess lockdown and security measures, it is quite inevitable
that the theta can get past the *rst line of cyber security defence. This report
also highlights that in this circumstance secure AI is the ideal solution for
eliminating these advanced threats.
Tmobile (2022) highlighted that secure AI follows a data collection approach for
their operation and addressing of cyber risks. By appropriately collecting data
and analyzing the data behaviour using AI cybersecurity, organizations or users
can easily identify the malicious operation and can take immediate measures.
Secure AI offers a smarter net for emerging threats. This secure AI is a
comprehensive and intelligent solution against hacking in devices such as PC,
mobile, and laptops, They deliver certain prevention measures and endpoint
detection and response which include managed “threat hunting” and threat
When it comes to the working approach of secure AI, they integrate the three
core elements of security inside a single agent. Soni (2019) mentioned that this
approach allows them to protect their organization from advanced threats at
various stages of the cyber attacks like the detection, prevention and different

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remediation capability. The organization needs to adopt a “zero trust”
mentality approach for protecting itself from potentially catastrophic cyberattacks. This approach would help the organization in guarding against
potential threats and issues (Chehri et al., 2021). It re+ects upon taking a
proactive approach to how an organization can monitor their people, system or
their services while using its network. In organizations, there are several ways
through which hackers can have access to the network.
The avenue in the organization’s system needed speci*c cyber security
solutions for ensuring that their data is protected. Once a user or organization
reviews the cyber security needs of the organization, they need to evaluate
certain options that provide this kind of protection. For instance (Tmobile (b),
2022) re+ected that perimeter protection protects the company system,
network and data from external threats. If organizations use private network
access, then they will get secure access to some speci*c company apps and
the data that is needed without having to open the whole network. Sometimes
the organization also seeks mobile device protection. As per Cheatham et al.,
(2019), mobile device protection allows the organization,s workers and
employees in protecting their devices regardless of the network access to the
internet. The organization also need to consider certain monitoring and
remediation measures for proactively searching for PC, tablets, servers and
thread that can quickly detect the issues and also provide remediation.
The question arises as to why one should select secure AI for cyber threat
detection over other measures. In this context, some of the characteristics,
functions and approaches of secure AI need to be examined to understand why
a user should select secure AI for their cyber security masters. Grachev et al.,

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(2021) highlighted that the secure AI by itself does not just match the endpoint
data against the known indicator of the compromise or IOC. They have the
capability in spotting threat activities in the system that otherwise gets
overlooked while using traditional models or approaches of cyber security
measures, With secure AI, one can see “never-before-seen” that, *le-less
malware and even lateral movements which are hard to spot in systems. The
secure AI generally prevents alert fatigue in the system by making use of AI for
ful*lling related items of an attack so that they can visualize the whole attack
story by incorporating the “end-to-end” context for a malicious threat.
2.3 Critical Discussion
The secure AI can proactively hunt for the response to threats and also
highlights malicious behaviour across system endpoints. The Secure AI is
designed in a way for countering alert fatigue when the user system gets
desensitized to theta alerts which don’t amount to anything. According to
Wirkuttis and Klein (2017), the secure AI solution would generally determine if
the theta posed on the system is real or false before alerting the main user. The
secure AI also recommends responses based on the threat level. As per Tmobile
(2022), Secure AI works on the principle of analyzing historical data behaviour.
They have the capability in learning and also date towards the detection and
response to newer and unfamiliar threats. As seen in the earlier section,
organizations wishing to incorporate secure AI need to have a zero-trust
mentality. This is because in organizations, the threat can occur and exit from
anywhere (Samtani et al., 2020). It can even occur from an organization’s
internal employee accessing a vulnerable app via a cloud. It can even come
from a mobile user or employee logging in from some sort of unsecured Wi*
connection. The secure network can lead to phishing and it can crash the whole

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system of the organization. Every device along with the connection may pose a
risk for the user and organization (Tao et al., 2021). Hence it is vital to check
and analyze the true threat and take appropriate measures. In this context, the
secure AI if deployed successfully can analyze and identify these true theta and
can recommend appropriate measures that seem suitable for the
As per Brundage et al., (2018); Tmobile (2022), secure AI can act as the initial
line of defence for the organization’s data. As newer security threats and
various network vulnerabilities have emerged, it became hard for the
organization and used to keep up. With the help of secure AI, the organization
can introduce certain security measures and technologies and also expertise to
their network. This results in protecting the system from newer kinds of cyber
threats. Secure AI offers more visibility and transparency across the device and
system data. Though secure AI, de*ned “cyber protection capabilities” over a
single endpoint sensor can be discovered and managed. The secure AI also
offers a contextual threat analysis for reducing the false positives and only
addresses the true threat thereby eliminating time and resource wastages. The
secure AI also considers the whole picture when it comes to theta detention in
the system when compared to traditional methods (Samtani et al., 2020). In the
traditional or another method, in many cases, the true theta is not android form
the false theta and as a result that leads to a wastage of time and resources.
The secure AI approach does more to identify the true theta and recommend
actions on these true threats. They mostly focus on identifying the theta from
the systems end points which are a key source of hacking attempts by hackers.

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Chapter 5: Conclusion and Outlook
In companies and organizations, indeed with tight lockdowns and security
implies it is truly inescapable that risk gets past the primary line of defence. At
whatever point this occurrence happens. The organization would be requiring
particular instruments or tools which can proactively watch their environment
while recognizing and killing any danger related to the framework. This speci*c
sort of security can be appropriated while utilizing Secure AI.
From this research, it is determined that secure AI end-point decision
measures are highly applicable when it comes to identifying cyber threats and
issues. The reason the secure AI approach is more popular than the traditional
approach is that this approach looks at the whole picture and identi*es the
true theta instead of the false threat. Doing so saves the organization and user
a lot of time and resources. Much research was undertaken to identify the
importance of secure AI. The reason why organizations need to focus on
cybersecurity is beau’s it will otherwise lead to a huge revenue loss for the
organization The hackers and phishers apply various updated and enhanced
measures for hacking into the organization’s system. With the traditional
approach, it may have been very dif*cult to identify and analyse all these
threats. From the research, it was discovered that secure AI can proactively
hunt and respond to these newer threats across the endpoints of the system.
The endpoints are the area where hackers generally inject a virus or phishing
link to enter the system. Secure AI tries to repair these areas effectively to
prevent hacking attempts.

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