Open Source Intelligence is the most widely used of all the threat intelligence subtypes. It is defined by both the U.S. Director of National Intelligence and the U.S. Department of Defense (DoD). It’s “produced from publicly available information that is collected, exploited, and disseminated in a timely manner to an appropriate audience for the purpose of addressing a specific intelligence requirement”.
From this definition, it can be inferred that open source refers specifically to information that is available for public consumption. There have been significant advances in the field of Open Source Intelligence. The most notable of them being tied to Artificial Intelligence (AI) and machine learning.
There are two primary ways through which Open Source Intelligence can be used for cybersecurity. The first case pertains to ethical hacking and penetration testing. Security experts identify the potential weakness in friendly networks in order to avert a future cyber-attack of increasing magnitude. The second case pertains to identification of new vulnerabilities and threats.
Deep Web and Dark Web
Open Source Intelligence is often used with intelligence data from closed sources such as the Deep Web and the Dark Web. The Deep Web is typically considered to include parts of the internet not accessible through traditional web browsers. Dark Web is typically considered to include parts of the Deep Web that are hidden for illicit purposes. It allows users to remain anonymous.
In the domain of security, an analysis of online resources can enable military and other users to learn about planned actions, before they occur from malware aimed at networks to terrorist attacks.
A number of militaries worldwide have invested a great deal in research and technology pertaining to this. There is growing recognition that the ability to analyse large quantities of data has significant potential, he said, with a major focus on identifying patterns of behaviour, including when to defend a network from potential insider threats.
Advances have been in facial recognition technologies. Can be seen in biometrics use in airports, as well as potential applications for military intelligence and other users. If such technology is linked to other databases, it can be relatively easy to track people’s movements. Also to build profiles of them both online and offline.
Challenge of Personal Privacy
While this has obvious advantages, there are also challenges that need to be resolved. Particularly when it comes to personal privacy. Many of the advances in the area stem from developments in AI, which is capable of analysing datasets in real time.
Further, there are several other areas for potential technological development that could transform the domain, particularly with the collection and analysis of open source intelligence. For example, quantum computing could have a major effect and ease the task burden.
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Open Source Intelligence helps in trend and pattern analysis and visualisation of topics, messages, people, organisations, and locations of interest for a number of users. Including defence clients, the positive and negative sentiments surrounding these, and the propagation of information among web communities. It also provides a quantitative scale for ranking the most authoritative and influential authors and sources.
It may be mentioned here that in the domain of security, machine learning has existed for decades. However, two major differences are perceptible currently: the volume of data available and the computing power available to process it.
For example, over the past 10 years the number of people using smartphones worldwide – which generate huge amounts of data – has grown massively. While computing power has led to more efficient and a deeper analysis of the data.
This does not mean though the human analyst will be removed from the picture any time soon. Algorithms can be used to significantly speed up the time it takes to find the required information and can help the filtering process.
Open Source Intelligence now comes into picture as it helps to analyse minute data. And such kind of analysis cannot be replicated by a human mind on its own.