IT 3: Analyzing OSINT in Threat Detection: A Comprehensive Report

This report examines the application of Open Source Intelligence (OSINT) in threat detection. It explores key aspects of OSINT, including its role in identifying and mitigating cyber threats by analyzing publicly available information. The report delves into various techniques such as risk assessment, which involves identifying potential vulnerabilities and threats, and the importance of online presence analysis to understand the digital footprint of individuals and organizations. Sentiment analysis is discussed as a method to gauge opinions and sentiments related to threats, while influencer analysis is presented as a tool to identify sources driving negative discussions. The report emphasizes the significance of OSINT in providing early warnings and protection against internet-based security attacks, highlighting the need for automation and reliable sources. Overall, the report provides a comprehensive overview of OSINT's role in enhancing cybersecurity and preventing potential threats.

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IT Write Up
OSINT in Threat Detection
(Student Details: )
3/26/2020

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Contents
Threat Detection using Open Source Intelligence.....................................................................2
Introduction................................................................................................................................2
OSINT in Threat Detection........................................................................................................2
Threat detection......................................................................................................................2
Risk Assessment.....................................................................................................................3
Online Presence......................................................................................................................3
Sentiment Analysis.................................................................................................................4
Influencer Analysis................................................................................................................4
Conclusion..................................................................................................................................5
References..................................................................................................................................6

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Threat Detection using Open Source Intelligence
Introduction
The discussion is mainly focused on threat detection in Open Source Intelligence
(hereinafter referred to as OSINT) so that Open Source Intelligence can be understood in a
good manner. Presently, threat information like cyber-attack techniques as well as
responsibility claims is distributed with the help of the deep web and social media. On the
other hand, an explosion of information, as well as an insufficiency of security analysts, is
making it difficult to detect this type of information at the early stages. In this way, in the
absence of early detection, it causes another problem of delayed preparation in relation to
attack damage (Bazzell, 2016). Thus, this discussion is introducing threat detection methods
in order to identify signs of a threat trend in this era. Thus, in the context of OSINT threat
detection, the key topics include threat detection, risks assessment, online presence, sentiment
analysis, and influencer analysis will be covered while providing a concise summary in the
end.
OSINT in Threat Detection
Threat detection
The OSINT provides threat intelligence by offering a clear, comprehensive and
simple way to consume intelligence which has a high degree of relevance to the service
provider and security vendors. In the context of threat detection, Open source information
contains many cyber-attacks making plans alerts from ill-intentioned actors (Continuum,
2019). The use of computerized series, governmental entities and companies can divert
cyber-attacks like people who have been directed at the White House and JP Morgan this past
October. Moreover, manual methods are insufficient because of the number of records to be
analysed and the speedy speed with which threats stand up. For example, OSINT threat
detection is essential to minimize the potential of such an event at any school or within any
community with school administrators, security professionals, parents and community
leaders' ideas (Cornell, 2018). Thus, threat detection can be better performed by the use of
OSINT automation platforms. It is because these OSINT threat detection platforms can easily

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offer early cautionary of and protection against Internet-based security attacks (Financier
Worldwide Magazine, 2019).
Risk Assessment
In this context, the threat, as well as risk assessment, is crucial for further preventing
cyber-attacks like school shooting. As mentioned by, in the event of the school shooting in
Parkland, Florida, there were so many groups from students to lawmakers (Glassman &
Kang, 2012); who have been searching for different ways to make U.S. schools as well as
communities safer and prevent further shootings. With OSINT threat detection, the best way
to make schools safer is to utilise threat assessments with OSINT. It is a tool developed by
law enforcement for effectively protecting public figures (Ribeiro, 2018).
In the context of the school shooting, crime rates across the field are increasing day by
day. In this way, a primary thing for risk assessment is to recognize that violence in schools is
just a small part of the larger issue of gun violence within American society (Geekflare,
2019). Thus, risk assessment is safe as well as an effective way of helping students who have
threatened violence themselves. Risk assessment with OSINT is a systematic process of
intervention and evaluation for the individuals who have made behavioural or verbal threats
of violence against other people around them (Grey Campus, 2020).
Online Presence
In this context, there is some kind of personal information which is available online
and can be assessed by the cyber-attackers. Such kind of information can be compromised on
the Dark Web. It has been found that effective OSINT comes through various sources. In
addition to that, online presence suggests that online articles and magazines from trusted
outlets are good places to find this online personal information of the institutions, individuals
and school databases, as are videos through respected security conferences. Thus, in order to
enhance security measures must not overshadow ways that already have been established to
avoid violence in the school shooting (Cornell, 2018).
Sentiment Analysis
In the context of sentiment analysis of OSINT, it is worth knowing that there are two
most frequently utilized OSINT methodologies include sentiment analysis and lexical
analysis. In general, sentiment analysis is an attempt to infer an individual's opinions or
sentiments on the basis of his or her online behaviour (Geekflare, 2019). It has been observed

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that in OSINT when a person utilizes some specific terms on the web; then they are
categorized as neutral, negative or positive. Based on the above, the person is usually given a
score which is known as sentiment analysis on OSINT based on online activities (Grey
Campus, 2020).
Apart from this, sentiment analysis is also used on social media networks to conduct
better sentiment analysis (Gravrock, 2019). It has been found that companies often utilise
social media monitoring or sentiment analysis in order to effectively oversee what exactly
individuals think about their brands and thereby manage perceptions (Bazzell, 2016). Thus,
with the help of OSINT tools, modern brands are identifying negative comments all across
social media platforms as well as mitigating them. From the safety and security perspective,
there are security and defence agencies that employ their social media OSINT for further
conducting the sentiment analysis for further access unfiltered info on what people are
thinking and expressing about a given topic. Therefore, sentiment analysis is used to manage
threats into the process (Ribeiro, 2018).
Influencer Analysis
As discussed above, online presence and sentiment analysis; both are used to conduct
influencer analysis. This analysis is used to see who is driving negative discussion with the
help of influencer analysis. In the threat detection from OSINT, the influencer analysis is of
high importance because OSINT has been defined in terms of leveraging publicly accessible
data from television, radio, newspapers, commercial databases, internet, media, and others
(Grey Campus, 2020).
On the other hand, influencer analysis gives the authority to see the origin of negative
influencers. With the rise of the net and social media use, online sources can these days be
labelled as an essential OSINT subset (Grey Campus, 2020). Moreover, records amassed on
the internet using OSINT are normally free. Subsequently, it is vital to pick out dependable
resources you can trust. OSINT can be used for lots of purposes along with agency due
diligence, recruitment, policing, and danger intelligence in addition to advertising.
Furthermore, with the help of amazing knowledge of OSINT gear and market developments
you can completely make use of the intelligence value of OSINT (Geekflare, 2019).

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Conclusion
In whole, with this research on OSINT, it has been found that Open Source
Intelligence refers to the intelligence discipline which typically pertains to intelligence
created from openly available data and information. This public information is usually
collected, disseminated and thereby exploited regularly to a suitable audience in order to
address a particular intelligence as well as requirements. In this context, threat detection in
OSINT requires aggregating and analysing social media data whenever it is text-based.
However, for OSINT it is challenging with audio, video, graphics as well as images due to
the fact that content into such formats may require to be transformed within usable
intelligence. On the other hand, some other challenges have been found in threat detection as
authentication, because it includes being capable to exactly find the user’s identity.

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References
Bazzell, M. (2016). Open source intelligence techniques: resources for searching and
analyzing online information. UK: CreateSpace Independent Publishing platform.
Continuum. (2019). Cybercrime & Security Overview: Terms, Trends, Statistics, and
Takeaways. Retrieved 2019, from
https://www.continuum.net/resources/mspedia/cybercrime-and-security-overview
Cornell, D. (2018). Threat assessments crucial to prevent school shootings. Retrieved 2020,
from http://theconversation.com/threat-assessments-crucial-to-prevent-school-
shootings-93636
Financier Worldwide Magazine. (2019). Emerging trends in cyber security. Retrieved 2019,
from https://www.financierworldwide.com/emerging-trends-in-cyber-
security#.Xg3TKkczbIV
Geekflare. (2019). 7 Popular Open Source Intelligence Tools for Penetration Testing.
Retrieved from Geekflare: https://geekflare.com/osint-tools/
Glassman, M., & Kang, M. (2012). Intelligence in the internet age: The emergence and
evolution of Open Source Intelligence (OSINT). Computers in Human Behaviour,
28(2), 673-682.
Gravrock, E. (2019). Here are the biggest cybercrime trends of 2019. Retrieved 2019, from
https://www.weforum.org/agenda/2019/03/here-are-the-biggest-cybercrime-trends-of-
2019/
Grey Campus. (2020). Top 10 Popular Open Source Intelligence (OSINT) Tools. Retrieved
from Grey Campus: https://www.greycampus.com/blog/information-security/top-
open-source-intelligence-tools
Ribeiro, M. (2018). How Open Source Intelligence Could Save Your Network. Retrieved from
Security Intelliegence: https://securityintelligence.com/how-open-source-intelligence-
could-save-your-network/

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