Top Artificial Intelligence-Based Tools For Cyber Security

In today’s world, everyone is benefitting from internet connectivity. Just a click is enough to know about the whereabouts of a distant friend or the location of aliens(I know you cannot). But at the same time, We as a user are at risk to savvy cyber criminals who are constantly adapting their techniques to sneak into critical systems. As an internet user, there is always a limitation on what you want to tell people about yourself publicly. Imagine you wake up and find that everyone knows about your medical condition that you wanted to keep private. It is a breach of your data, right ??.

Similarly, every entity wants its systems strong enough to block illegal attempts of cyber-criminals. These systems include defense, power plants, hospitals, and financial service companies prone to cyber-attacks that provide essential services to society. In the news, you must have heard cyber attacks are launched more often against countries that have differences among themselves and use these tools as a weapon against each other. Hence, at least everyone should be familiar with the practices employed by the attackers to get into systems and cause jeopardy. A subfield of computer science called cybersecurity teaches us how to safeguard databases, computer systems, and networks against online assaults. 

Cybersecurity falls into five broad categories: Critical infrastructure security, Cloud security, Internet of Things security, Application Security, and Network Security. Let us know some common types of techniques used by the attackers.

Malware infection

Malware is malicious software developed to cause damage to a database or server and could force an illegal entry into your systems without your knowledge. It can be in the form of an erroneous attachment or specific links.

Ransomware attacks

Ransomware is a kind of malware where the user gets locked out of his files/systems. Then, the criminal demands money in exchange for access to the files. You must have heard about crypto-ransomware attacks.

Phishing Attacks

Emails or links are designed to inspire you to answer the credentials like passwords/ bank details. That’s it, and Hackers make payments or get access to the systems and vanish in thin air. Other types include smishing, vishing, etc., based on the nature of attacks.

Social Engineering

Often you have received calls from spam numbers impersonating themselves as an official. They obtain basic details from digital media. People outright manipulate others to reveal personal information.

I hope till now you have got some basic idea about cyber-security threats. Let’s see how AI can help us to protect against spoof and sophisticated attacks done by cyber-criminals and will know some of the AI tools used against such attacks. According to a global survey released by Pillsbury, an international law firm, 49% of its executives think AI is the best tool to counter nation-state cyber attacks. It also predicts that cybersecurity-related AI spending will increase at a CAGR of 24% through 2027 and reach a market value of $46 billion. Its applications include classification algorithms for early malware and spam detection, abnormality in malicious traffic or user behaviors, and correlation algorithms that connect signals from disparate systems.

Some use cases of AI in cybersecurity include spotting zero-day malware using AI and ML techniques that can analyze malware based on intrinsic characteristics rather than signatures. If the software is designed to encrypt many files at once rapidly, that’s suspicious behavior. Suppose it takes steps to hide from observation. That’s another sign that the software isn’t legitimate. It can help identify and prioritize threats and sometimes take automated actions to solve security issues quickly. From startups to government entities, All are spending their best on cybersecurity because once a professional criminal breaches your data, trust is lost, which could hamper enterprise brand value. Intelligent automation can care for these problems when appropriate, helping companies deal with a shortage of qualified cybersecurity professionals. 

Top Artificial Intelligence-Based Tools For Cyber Security

Cyber Security Tool Kit (CyberSecTK)

CyberSecTK is an accessible python library for developing the toolkit needed for processing and quality extraction of cyber-security-related data. It aims to bridge the gap between techniques and cybersecurity.

It is a suite of program modules, data sets, and tutorials supporting research and teaching in cyber security and defense required for cyber-security professionals to develop a method from scratch.

Sophos Intercept X tool

Intercept X utilizes a deep learning neural network to conduct deep analysis and determine if a file is safe or malicious in 20 milliseconds before it executes.

The model is trained on real-world database and bi-directional threat intelligence sharing via access to millions of samples provided by the data scientists resulting in highly accurate and zero-day malware and a lower false positive rate.

Vectra’s Cognito

Cognito by Vectra is an AI tool that detects and responds to attacks inside the cloud, data center, IoT, and enterprise networks. It uses behavioral detection algorithms by collecting network metadata and logs. It further diagnoses the events and stores them to expose hidden attackers in workloads and IoT devices.

Targeted attack analytics (TAA) by Symantec

The Targeted attack analytics (TAA) tool developed by Symantec comes with cloud-based analytics that automatically adapts to new attack tactics by delivering continuous attack detections, plus the ongoing addition of new attack analytics. The company used the tool to counter the Dragonfly 2.0 attack in 2017, which targeted multiple energy companies and tried to attain access to the company networks.


Bio-inspired Hybrid Artificial Intelligence Framework for Cyber Security (bioHAIFCS) is a framework that combines timely and bio-inspired ML approaches suited for the protection of critical network applications, i.e., military information systems. It comes with a Hybrid Evolving Spiking Anomaly Detection Model (HESADM), used to quickly and accurately prevent cyber-attacks that cannot be avoided otherwise by passive firewalls. Also, Evolving Computational Intelligence System for Malware Detection (ECISMD); and the Evolutionary Prevention System from SQL injection (ePSSQLI) attacks.


StringSifter is an ML tool that ranks strings automatically based on their relevance for the malware examination. It requires Python 3.6 or above to run. It gets strings as input and sorts the exact string as output based on their relevance for malware analysis.


DefPloreX is a ML toolkit for large-scale e-crime forensics. It is a flexible toolkit based on open-source libraries to analyze millions of defaced web pages. It uses machine learning and visualization techniques to turn unstructured data into meaningful high-level descriptions.

IBM QRadar Advisor

IBM’s QRadar Advisor uses IBM Watson technology to protect against cyber attacks. They are using AI to auto-investigate indicators of any compromise or exploitation. QRadar Advisor is the cognitive reasoning to give critical insights and further accelerates the response cycle. It can further help security analysts to assess threat incidents and reduce the risk of missing them. It reduces the time spent investigating incidents from days and weeks down to minutes or hours.  


With a single dashboard, Tessian’s ML-powered email filters can detect and eradicate suspicious activity both inbound and outbound. Real-time monitoring allows users to keep track of their organization’s integrity instantly with ease.

Vectra’s Cognito platform

With Vectra’s Cognito platform, analysts are able to focus their time on the most important tasks. They can use human intelligence and data science for faster threat detection in real-time and automate some of these tasks that previously took up precious hours with manual labor – reducing turnaround times significantly!


Please note this is not a ranking article

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