Intelligence

Definition of Intelligence and Its Essential Terminology

Intelligence is a process t hat utilizes information to analyze and respond to emerging requirements of an organization. It is an ability to obtain, adapt, alter, extend, and use t he information to solve various organizational problems. Intelligence provides solutions to resolve issues arising during unpredictable circumstances in an organization. It is t he output obtained from analysis of information. In this process, intelligence converts “what” and “how” of t he information into “why” and “when” of t he problem-solving process.

Essential Terminology

Cyber Threat

A cyber threat is a possibility of performing malicious act ions to damage the critical IT resources of a target organization.

Vulnerability

Vulnerability is t he existence of weakness, design, or an implementation error that, when exploited, leads to an unexpected and undesirable event compromising the security of the system. Simply put, vulnerability is a security loophole t hat allows a malicious outsider to enter the system by bypassing various user authentications or implemented security controls.

Zero-Day Attack

In a zero-day attack, t he attacker exploits vulnerabilities in a computer application before the software developer can release a patch for them.

Exploit

An exploit is a breach of IT system security through vulnerabilities in the context of an attack on a system or network. It also refers to malicious software or commands that can ca use unanticipated behavior of legitimate software or hardware through attackers who take advantage of the vulnerabilities.

Advanced Persistent Threats

Advanced persistent threat (APT) is an attack that focuses on stealing information from the victim machine without its user being aware of it. These attacks are generally targeted at large companies and government networks and are slow in nature, so the effects on computer performance and Internet connections are negligible. APTs exploit vulnerabilities in the applications running on a computer, operating system, and embedded systems.

Also Read : What is Threat Intelligence, Information & Data ?

Risk

Risk refers to a degree of uncertainty or expectation of potential damage that an adverse event may cause to the system or resources of an organization under specified conditions.

Information Security

Information security is defined as “a state of well-being of information and infrastructure in which t he possibility of theft, tampering, and disruption of information and services is kept low or tolerable.” It relies on five major elements: confidentiality, integrity, availability, authenticity, and non- repudiation.

Algorithm

The most vital a part of AI is that the algorithm. These are math formulas and/or programming commands that inform a regular non-intelligent computer on how to solve problems with artificial intelligence. Algorithms are rules that teach computers the way to figure things out on their own. it should be a nerdy construct of numbers and commands, however what algorithms lack in desirability they more than make up for in usefulness.

Black box

When the rules are applied an AI will a lot of complicated math. This math, often, can’t even be understood by humans (and typically it simply wouldn’t be well worth the time it would take for us to figure it all out) yet the system outputs helpful data. when this happens it’s called black box learning. the real work happens in such a way that we don’t really care however the computer arrived at the choices it’s created, because we all know what rules it accustomed get there. Black box learning is however we will ethically skip “showing our work” like we had to in high school algebra.

Machine learning

The meat and potatoes of AI is machine learning — actually it’s typically acceptable to substitute the terms computing and machine learning for each other. They aren’t quite a similar, however, however connected.
Machine learning is the method by that an AI uses algorithms to perform artificial intelligence functions. It’s the results of applying rules to create outcomes through an AI.

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Neural network

When we want an AI to get higher at something we create a neural network. These networks are designed to be very similar to the human nervous system and brain. It uses stages of learning to grant AI the ability to solve complicated issues by breaking them down into levels of knowledge. the primary level of the network may only worry a few few pixels in a picture file and check for similarities in different files. Once the initial stage is finished, the neural network can pass its findings to consecutive level which can attempt to perceive some a lot of pixels, and perhaps some data. This method continues at each level of a neural network.

Natural language process

It takes an advanced neural network to parse human language. once an AI is trained to interpret human communication it’s called natural language process. this is helpful for chat bots and translation services, however it’s also represented at the cutting edge by AI assistants like Alexa and Siri.

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