Internet of things Security

Main tools based on artificial intelligence for cybersecurity

In today’s world, everyone benefits from Internet connectivity. Just one click is enough to know about the whereabouts of a distant friend or the location of aliens (I know you can’t). But at the same time, we as users are at risk of falling victim to clever cybercriminals who are constantly adapting their techniques to break into critical systems. As an Internet user, there is always a limitation on what you want to tell people about yourself publicly. Imagine waking up to find that the whole world knows about your medical condition that you want to keep private. It’s a data breach, right?

Similarly, all entities want their systems to be strong enough to block illegal attempts by cybercriminals. These systems include cyber-attack-prone defense, power plants, hospitals, and financial services companies that provide essential services to society. In the news, you must have heard that cyber attacks are most often launched against countries that have differences between them and use these tools as a weapon against each other. Therefore, at least everyone should be familiar with the practices used by attackers to break into systems and cause harm. A subfield of computing called cybersecurity teaches us how to protect databases, computer systems, and networks from online attacks.

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 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 a bad attachment or specific links.

ransomware attacks

Ransomware is a type of malware where the user is locked out of their files/systems. The criminal then demands money in exchange for access to the files. He must have heard of crypto ransomware attacks.

phishing attacks

The emails or links are designed to inspire you to respond to credentials such as passwords/bank details. That’s it, and hackers make payments or gain access to systems and disappear into thin air. Other types include smishing, vishing, etc., depending on the nature of the attacks.

Social engineering

You have often received calls from spam numbers posing as officials. They obtain basic data from digital media. People openly manipulate others to reveal personal information.

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

Some use cases for AI in cybersecurity include zero-day malware detection using AI and ML techniques that can analyze malware based on intrinsic characteristics rather than signatures. If the software is designed to quickly encrypt many files at once, this is suspicious behavior. Suppose you take steps to hide from observation. That is another sign that the software is not legitimate. It can help identify and prioritize threats, and sometimes take automated action to quickly resolve security issues. From start-ups to government entities, they all invest as best they can in cyber security because once a professional criminal breaches your data, trust is lost, which could hamper the value of the business brand. Intelligent automation can fix these issues where appropriate, helping companies deal with a shortage of qualified cybersecurity professionals.

Main tools based on artificial intelligence for cybersecurity

Cyber ​​Security Toolkit (CyberSecTK)

CyberSecTK is an accessible python library for developing the necessary toolset for quality data processing and extraction related to cyber security. Its goal is to bridge the gap between techniques and cybersecurity.

It is a set of program modules, data sets, and tutorials that support the cybersecurity and defense research and teaching necessary for cybersecurity professionals to develop a method from scratch.

Sophos Intercept X Tool

Intercept X uses a deep learning neural network to perform deep analysis to determine whether a file is safe or malicious 20 milliseconds before it is executed.

The model is trained on real-world database and two-way threat intelligence sharing through access to millions of samples provided by data scientists, resulting in highly accurate, zero-day malware and a faster rate. of false positives lower.

Cognito of Vectra

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

Symantec Targeted Attack Analysis (TAA)

Symantec-powered Targeted Attack Analysis (TAA) tool comes with cloud-based analytics that automatically adapt to new attack tactics by providing continuous attack detections in addition to the continuous addition of new attack analytics. The company used the tool to counter Dragonfly 2.0 attack in 2017that targeted multiple energy companies and attempted to gain access to company networks.

BioHAIFCS

The Bioinspired Hybrid Artificial Intelligence Framework for Cyber ​​Security (bioHAIFCS) is a framework that combines timely and bioinspired ML approaches suitable for the protection of critical network applications, i.e. military information systems. It comes with a hybrid evolving spike anomaly detection model (HESADM), which is used to quickly and accurately prevent cyberattacks that passive firewalls cannot otherwise prevent. Additionally, the Evolving Computational Intelligence System for Malware Detection (ECISMD); and the Evolutionary Prevention System for SQL injection attacks (ePSSQLI).

rope sieve

StringSifter is an ML tool that automatically sorts strings based on their relevance to malware examination. It requires Python 3.6 or higher to work. Gets strings as input and sorts the exact string as output based on its relevance to malware analysis.

DefPloreX

DefPloreX is a suite of ML tools for large-scale electronic crime forensics. It is a flexible set of tools 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 QRadar Advisor uses IBM Watson technology to protect against cyber attacks. They are using AI to automatically investigate indicators of any compromise or exploitation. QRadar Advisor is the cognitive reasoning to deliver critical insights and further speed up the response cycle. Additionally, it can help security analysts assess threat incidents and reduce the risk of missing them. Reduce the time spent investigating incidents from days and weeks to minutes or hours.

Tessian

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

Vectra Cognito Platform

With Vectra’s Cognito platform, analysts can focus their time on the most important tasks. They can use human intelligence and data science for faster real-time threat detection and automate some of these tasks that previously required precious hours of manual work, significantly reducing response times!

References:

  • https://analyticsindiamag.com/top-8-machine-learning-tools-for-cybersecurity/
  • https://hub.packtpub.com/6-artificial-intelligence-cybersecurity-tools-you-need-to-know/
  • https://cybermagazine.com/top10/10-cybersecurity-companies-powered-ai
  • https://ai-techpark.com/top-cybersecurity-tools-for-2022/
  • https://www.datacenterknowledge.com/security/top-three-use-cases-ai-cybersecurity
Please note this is not a ranking article

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I’m a consulting intern at MarktechPost. I am majoring in Mechanical Engineering at IIT Kanpur. My interest lies in the field of machining and robotics. Also, I have a strong interest in AI, ML, DL and related areas. I am a technology enthusiast and passionate about new technologies and their uses in real life.


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