With advancing technologies, one can realize the best of the imagined smart society which includes: autonomous vehicles, smart e-devices, virtual assistants, medical robots, AR and VR applications, automated machines recognizing human behavior, and many more countless use-cases.

And all of that is simply driven by Data.

The CONCEPT

In order for all of the above to continue growing at the rate of demand, cloud environments have become popular. 

Today, applications are no longer local and DevOps (operations development) joins the deployment of the Internet of Things(IoT) or in its version for the industry to the proliferation of connected devices, from toys to household appliances with all kinds of industrial sensors, telecommunication technologies such as 5G and more.

“Cloud environments, IoT, and the proliferation of connected devices increase organizations’ exposure to cyberattacks.”

This increases exposure to cyber risks, on the one hand, and exposes organizations to third-party risks on the other. In other words, it is no longer enough that we are protected, but that we have to demand the protection of our strategic partners.

The first step in establishing the best defense against a potential cyberattack is to incorporate a solution that includes preventive monitoring, user education, proper patch management, and incident handling.

However, currently, options have been developed that can transcend this basic configuration, one of the best is the implementation of Artificial Intelligence (AI) in cybersecurity.

It is not surprising that cyber incidents have risen in the Allianz Risk Barometer from 15th position in 2013 to 1st position as the most important business risk in 2020, in countries as varied as Austria, Belgium, France, India, Malaysia, South Africa, South Korea, Sweden, Switzerland, the United Kingdom, the USA or Spain and by aviation, financial services, government, and public services, professional services, technology, and telecommunications. 

Source: agcs.allianz.com

Also, the 15 Global Risk Report (2020) of the World Economic Forum advances in the line of placing cyber attacks in one of the most worrying scenarios. 

Artificial Intelligence and Cybersecurity

Investment in artificial intelligence as a service, that is, applications that use AI to improve and facilitate their own activity will increase from $ 1.52 billion in 2018 to $ 10.88 billion in 2023, (a year-on-year growth rate of 48.2% during this period) according to MarketsandMarkets. 

This gives us an idea of ​​how appetizing that market will be for cybercriminals. 

However, we cannot ignore that 95% of cybersecurity incidents are due to human error, according to the IBM X-Force Threat Intelligence Index 2018 report, which indicates that we are a potential danger to our companies, as a simple USB charging cable that can cause a disaster in our company.

Thus, in training and awareness, it is the first link with which we must work in our company to improve cybersecurity. The second is the updating of our protection technologies.

Significant Use Cases

To preserve the sensitive data from hackers, businesses and brands seek aid from AI and its subsets (Machine Learning, Deep Learning, NLP) for protection of their business assets and security enhancement.

With all the top AI companies investing in the tech market, the global information security expenses will account for $170 billion by the end of 2022. 

Let’s check out the real-time business use cases of Artificial Intelligence and its descendants, making remarkable contributions in the sphere of cybersecurity.

#1 Network Threat Analysis

With more digitization, companies have upgraded their network systems to the next level which complicates the vast network topologies.

Artificial Intelligence in cybersecurity monitors the in and out network traffic and thus manages the internal communications, transactions, connections, and applications, mining the most vulnerable risks of suspicious activities and threat types.  

#2 Malware Detection

Malware is the ever-existing category of code intended to inject harmful data to a computer machine for hacking or leaking data. With machine learning’s inference techniques, AI is enabled to act like a pro in detecting the presence of malware along with categorizing it as per its traits.

Well trained deep structured algorithms based on powerful technologies of AI and ML have rendered the most successful results in cybersecurity, making the best use of huge, accurately labeled sets of data. 

#3 Security Analyst Augmentation

With major possibilities of human error in handling crucial and sensitive data, machine learning is powered to augment human analysts which are, nevertheless, the essential arbiters of knowledge, control, assessment, and explainability.

Automation of repetitive tasks triages tedious and monotonous data enrichment tasks for strategic decision making. Augmented security tools useful for the security teams are surfaced using machine learning principles to determine, analyze, monitor, and curate the potential threats and configured specifically to make the fixes.

#4 AI-Based Threat Mitigation

Smart malware developed by hackers and threat actors that aim to attack victims as per specific contexts can be dealt with AI propositions of scalability, personalization, and behavioral analytics to spy on data breaches, outbreaks, or other security-related incidents. 

[Prefer a 10mins read on: “Top 10 Important Benefits of Artificial Intelligence.”]

Businesses Empowering AI in Cybersecurity and Information Security

In cybersecurity and information security, Artificial Intelligence, Machine Learning, Deep Learning have promoted extensive concepts of data protection against the new and consistent threat types, acting as a boon for businesses to stop cybercrime.

Although the endpoint security technologies (computers, mobiles, printers, sensors, etc.) where security problems normally accumulate or start converge, we can find two different categories. 

On the one hand, we have endpoint protection platforms (EPP) and on the other endpoint detection and response solutions (EDR). 

EPP provides us with comprehensive solutions that typically unify various preventive security functions, including antivirus, antimalware, personal firewall and data protection, in order to prevent devices from being affected by malicious code.

EDR solutions give visibility to what happens in the equipment and offer the ability to detect, investigate, and respond to malicious activities.

#The Magic Quadrant Gartner, one of the reports most respected industry consulting cybersecurity, selects the best tools for endpoint protection, among which is CrowdStrike, from which Sofistic, the division of Cuatroochenta for cybersecurity, is an implementer. 

Gartner has highlighted among the benefits of Crowdstrike that its Falcon Complete service, compatible with all environments (physical, virtual, and in the cloud) provides fully managed detection and response and commitment consulting for incident response, also offers a guarantee of prevention of breach of $ 1 million.

#With a similar context, a tool named as Darktrace is developed on the basis of unsupervised machine learning and artificial intelligence, which analyzes the data flows in and through SaaS applications (Software as a Service) and cloud workloads, learning the normal life pattern of each user, device, and container. 

#Google Play blocked 1.9 billion malware on Android phones in 2019. The overlord uses AI and ML to identify suspicious apps on the Android OS with a robust technique of peer grouping. This concept creates segments in alike apps and runs reconnaissance to look out for ones with threatening elements.

Google keeps a close eye on the apps that require irrelevant permission access from users (like turning on microphone or location service) to avoid the steep chances of discrepancy and possible risks.

Last Say

We are constantly witnessing truly amazing advancements in technology where AI and its sub branches have allied with humans to provide solutions for the security hiccups faced at any time. 

Artificial Intelligence in Cybersecurity is maturing with time, transforming the situation of progressing businesses in a similar and even superior way to momentous security changes in the cyber world.

The next level is to witness a world of AI-powered software and machines which will be envisioned to end negative data behaviors and false positives with self-healing and self-learning networks, manipulating complex data sets.

About Author:

“Gary B is a serial entrepreneur with 14 years in technology and commercial software solutions. A true passion for building something great from nothing and willing to push to the limits to achieve big goals. Have a high degree of entrepreneurial spirit. His main differentiator is his focus on achieving excellence.”