ARTIFICIAL INTELLIGENCE IN CYBER SECURITY

INTRODUCING INTELLI-SAFE

With the increasing popularity of Deep learning and the omnipresence of AI in all fields of the IT sector, many cybersecurity professionals and information security analysts have been pushed to believe that these approaches could also be the key to eliminate all the cybersecurity challenges.

As cyberattacks grow in volume and complexity, artificial intelligence (AI) is what we need to help under-resourced security analysts stay ahead of threats. Intelli-Safe with its revolutionary approach comes with a promising solution for defending today's systems and consoles.

THE IDEOLOGY

AI-powered systems will be an integral part of cybersecurity solutions. It will be accessible to cybercriminals as much as it would be cybersecurity organizations.

This will leave AI using automated programs susceptible to advanced threats. Like any other cybersecurity solution, AI is not 100% foolproof.

To stand apart Intelli-Safe introduces its revolutionary tech which has been set up by designing two AI models that simultaneously work to corrupt and secure the system respectively.

Intelli-Safe offers tech which no cybercriminal or malicious organization can even think of combatting.

These AI modals are left in a dynamic interactive environment, with one model constructed to penetrate into the system and the other to defend and secure the system making them rebel with each other for the ultimate possession over the system.

This helps in securing the system from risks and vulnerabilities that otherwise wouldn’t have been figured out till generations to come.

Why AI and Machine Learning is the solution to today's Cyber Security Challenges?

AI systems are iterative and dynamic. They get smarter with the more data they analyze, they “learn” from experience, and they become increasingly capable and autonomous as they go.

Data analytics (DA), on the other hand, is a static process that examines large data sets in order to draw conclusions about the information they contain with the aid of specialized systems and software. DA is neither iterative nor self-learning.

How AI helps?

Learn — AI is trained by consuming billions of data artifacts from both structured and unstructured sources, such as blogs and news stories. Through machine learning and deep learning techniques, the AI improves its knowledge to “understand” cybersecurity threats and cyber risk.

Reason — AI gathers insights and uses reasoning to identify the relationships between threats, such as malicious files, suspicious IP addresses or insiders. This analysis takes seconds or minutes, allowing security analysts to respond to threats up to 60 times faster.

Augment — AI eliminaIntellegencetes time-consuming research tasks and provides a curated analysis of risks, reducing the amount of time security analysts take to make the critical decisions and launch an orchestrated response to remediate the threat.

Challenges Of Cyber Security

Before proceeding further, some time should be given o take into consideration what challenges we are trying to overcome using the tech Intelli-Safe has to offer.

• Geographically-distant IT systems
• Manual threat hunting
• Reactive nature of cybersecurity
• Hackers often hide and change their IP addresses
• A vast attack surface
• 10s or 100s of thousands of devices per organization
• Hundreds of attack vectors
• Big shortfalls in the number of skilled security professionals
• Masses of data that have moved beyond a human-scale problem

Where does today's Cyber Security Stand?

Today’s organizations use multiple lines of defense. This multi-layered security system usually starts with the best firewall capable of filtering out network traffic. After this layer, the second line of defense consists of antivirus (AV) software. These AV tools scan through the system to find and eliminate malicious codes and files.

Last but not least organizations periodically run backups as a part of a disaster recovery plan. This is how they pay close attention to their network security and encounter the massive impact of every small- to large-scale cyber-attack and secure their infrastructure.

Intelli-Safe brings Future to the present

Organizations these days use a very conventional path to combat cyber threats. By using AI Intelli soft changes in this traditional approach.

• It will help organizations monitor and respond to security incidents by using advanced tools.
• It will facilitate next-generation firewalls having in-built machine learning technology that could find a pattern in network packets and block them automatically if flagged as a threat.
• Intelli-Soft is also working on this promising technique where the natural language capabilities of AI will be used to understand the origination of cyber-attacks. This theory will be put into practice by scanning all data across the internet.

What Intelli-Soft promises to deliver, no one else does.

• IT Asset Inventory — gaining a complete, accurate inventory of all devices, users, and applications with any access to information systems. Categorization and measurement of business criticality also play big roles in inventory.
• Threat Exposure Reduction — hackers follow trends just like everyone else, so what’s fashionable with hackers changes regularly. AI-based cybersecurity systems can provide up to date knowledge of global and industry-specific threats to help make critical prioritization decisions based not only on what could be used to attack your enterprise but based on what is likely to be used to attack your enterprise.
• Controls Effectiveness — it is important to understand the impact of the various security tools and security processes that you have employed to maintain a strong security posture. AI can help understand where your infosec program has strengths, and where it has gaps.
• Breach Risk Prediction — Accounting for IT asset inventory, threat exposure, and controls effectiveness, AI-based systems can predict how and where you are most likely to be breached so that you can plan for resource and tool allocation towards areas of weakness. Prescriptive insights derived from AI analysis can help you configure and enhance controls and processes to most effectively improve your organization’s cyber resilience.
• Incident response — AI-powered systems can provide improved context for prioritization and response to security alerts, for fast response to incidents, and surface root causes to mitigate vulnerabilities and avoid future issues.
• Explainability — The key to harnessing AI to augment human infosec teams is the explainability of recommendations and analysis. This is important in getting buy-in from stakeholders across the organization, for understanding the impact of various infosec programs, and for reporting relevant information to all involved stakeholders, including end-users, security operations, CISO, auditors, CIO, CEO, and board of directors.

Others working in the same direction

AI has already been adopted to strengthen the security infrastructure of organizations. There are numerous real-life examples where AI-powered solutions are significantly improving cybersecurity.

• Gmail uses machine learning to block 100 million spams in a day. It has developed a system to filter out emails and offer a spam-free environment efficiently.
• IBM’s Watson cognitive training uses machine learning to detect cyber threats and other cybersecurity solutions.
• Google is using Deep Learning AI on its Cloud Video Intelligence platform. On this platform, the videos stored on the server are analyzed based on its content and context. The AI algorithms send security alerts whenever something suspicious is found.
• Balbix platform uses AI-powered risk predictions to protect the IT infrastructure against data and security breaches.

How we stand apart?

While other companies work on integrating AI-based solutions only for the defense of the system. In order to do so, We have an AI dedicated to attacking the system which helps in listing out vulnerabilities that

On the way to constructing this intriguing tech, we have kept in mind the adversaries of using Artificial Intelligence and Machine Learning in Cybersecurity.

As AI matures and moves increasingly into the cybersecurity space, the team at Intelli-Safe also guards against the potential downsides of this exciting new technology.

Since the tech behind Intelli-Safe keeps evolving every minute because of its dynamic training environment consisting of two interactive AI models, the potential hackers become incompetent to foil security algorithms by targeting the data.

It is feared that without massive volumes of data and events, AI systems will deliver inaccurate results and false positives but the approach adopted by our tech takes care of this too.

We also ensure data manipulation does not go undetected, so the organizations don't have to struggle to recover the correct data that feeds their AI systems.

Which Market will benefit the best from this Tech?

AI’s crucial role right now is to offload work from human cybersecurity engineers, to handle the depth and detail that humans cannot tackle fast enough or accurately enough. Advances in machine learning technology mean that AI applications can also automatically adapt to changes in threats and spot problems as they arise.

There is a shortage of working professionals providing Cyber Security solutions. Our tech eliminates this shortage and fulfills this demand.

It shares a big database of systems and helps overcome vulnerabilities both at individual and enterprise level consoles.

Usually, organizations and individuals opt for subscriptions of antivirus softwares and cloud storage for their promises of high security. Intelli soft promises to solve this problem from the core and architecture of the system by counting the risks and listing their methods of prevention.

This will help the developers and manufacturers in designing better and safer operating systems and machines respectively.