Endpoint Security-Using Artificial Intelligence and Machine Learning

AI (Artificial Intelligence) is a powerful new technology to detect threats in fast-moving businesses.
In fact, by applying machine learning to the complete inspection of end points, you can detect threats in real-time.

What is Endpoint Security?
Simply put, it is a process of defending critical data on the end devices like laptops, smartphones, tablets, etc., which are in turn connected to a network. But from whom are we seeking the protection? It does not take long to understand that this safeguarding is being made against today’s raging cyber threats.

Why does one need Endpoint Security today?
Data is the foundation of an organization that drives decisions and upheaval of ideas. It aids in a strategic contemplation of organizational relationships, drives informed decision making and weaves together the organization’s credibility.

A secure endpoint strategy becomes dynamically important given the complex cyber-threat landscape unfolding in current times. A data theft disaster would cost you more than a fortune, besides massive data loss.

Modern and upgraded data defense solutions that use Artificial Intelligence and Machine Learning are the only answer to help intercept such huge pecuniary losses and ultimately guard your organizational repute and credibility.

Some common types of cyber threats:

  1. Phishing:
    Phishing is one kind of social engineering threat usually aimed to steal critical user data, such as username details, passwords, credit card numbers, etc. An intruder, disguised as a trusted entity, deceives a victim to open an email, message, or through other electronic communication.
  2. Watering Hole:
    This one is aimed at infecting websites that a particular group of users regularly use with malware. The ultimate objective is to cause an incursion into the device of a targeted user within the group.
  3. Malware Attack:
    One of the supposedly famous cyber-attacks, a malware attack involves stealing of personal information through the creation of malicious software installed on a target’s device, without their knowledge. This is usually done for financial gains and some infamous examples of it are Ransomware, Trojan horses, etc.
  4. Denial of Service Attack:
    It is a kind of attack on a specific service that interrupts its regular function and blocks other users from reaching and using it. The usual target for this attack may be an online service such as a website; nonetheless, somebody can also launch it by confronting networks, machines, or just a single program.
  5. Man-in-the-Middle Attack:
    Here, a spiteful player places himself within a conversation between two parties, mimics both of them, and obtains access to data that the two parties meant to grant each other.

How are Artificial Intelligence and Machine Learning Spearheading a Resilient Endpoint Security?
Though it has turned obvious that a complete 100% efficiency is hard to achieve, advanced technologies like Artificial Intelligence and Machine Learning facilitate more powerful testing criteria. This attains immense significance to maintain stalwart organizational endpoint security.

Risk Identification:
Identifying potential risks becomes the first step in the direction of thwarting an attack. AI and ML have a proven history of leafing through the past data, which include details of location, login and logout timings, patterns of behavior, etc., using algorithms and predictive analysis.

This data proffers the right scope to discern anomalies and intrusive traits leading to risk recognition at the very early stages of the attack. Subsequently, the entire network may then be secured.

Robust Application Security:
Most applications today come with inherent loopholes and vulnerabilities in terms of security. End-point security thus gains a prominent ground to build a strong wall of defense. What better then AI and ML based unified systems through which pre-defined algorithms can be built? Employing this can lead you to place such harmful applications into dynamic containers or “blocks” with the help of an initial warning.

Efficiency Automation:
Willing to duct-tape your entire end to end IT systems from malicious incursions? AI and ML will be your trusted companions to automate a routine that is efficient enough to make your organization an impregnable fortress.

You can now identify risks and conduct a comprehensive analysis within seconds! In simple words, your team does not have to sit up and gauge the happenings to understand where and what went wrong. Why you might ask! Because everything is automated.

Keeping Phishing at bay:
One of the biggest growing types of attacks is Phishing. How can AI and ML help get ready and robust for this? These technologies analyze all emails (both content and metadata), and other messages to check for their authenticity. Also, other details like the subject line, context are examined and compared with past patterns. The access to the user will be automatically denied if there is any maliciousness detected.

In Conclusion:
Artificial Intelligence and Machine Learning will help advance and make your organization’s endpoint security more powerful and the end devices and access practical and impassable. It thus becomes imperative to emerge and develop with technology, automate the classification of trickery, and update the art of cyber-threat detection.