In an ideal set up, if one is running a B2B business, chances are that he must have multiple levels of security system in place irrespective of the size of the organization – whether it is a small-scale, medium-scale or large scale enterprise. The most impactful of all the cybersecurity systems have the following basic features:
- They complement the human elements of cybersecurity instead of completely replacing them
- They aid to the overall digital security of the organizations
- They supplement the other protection systems viz. perimeter, network, endpoint, application & data security processes
Doug Theis, Director of Market Strategy at Expedient stated the imperativeness of cybersecurity as follows:
“A security system with several layers is difficult to hack. So, even if your data is targeted, getting through the many tiers of security will be a hassle. The simplest of programs, such as free online email accounts, have multi-layered security, too. Even if accessing your accounts takes a few extra steps, it is still worth the effort, certainly better than losing your data. Using a firewall, making sure your antivirus software is updated, running antivirus checks frequently and updating your programs regularly are all part of maintaining your data security.”
Imagine a hypothetical scenario where an enterprise has a system based on hardware or software firewalls, along with network security solutions that track & determine the authenticity of the allowed networks & block the alien ones. If hackers manage to get past these defenses, they will be facing the enterprises’ antivirus & anti-malware defense mechanisms. Perhaps then they may come across the intrusion detection &/prevention solutions (IDS/IPS). The problem arises when cyber hackers manage to get past all these halts.
Artificial intelligence aids cybersecurity by improving methods of analysis & understanding of cybercrimes by the security experts. It enhances the cybersecurity technologies used by the organizations to combat cybercriminals & help keep an organization’s critical data, including the customers’ data safe.
Artificial intelligence & machine learning demarcate the beginning of a new wave of technological development, revolutionizing the realm of information technology & data security & transcending it beyond the conventional signature-based pattern matching using antiviruses (AV).
The European Union recognized the importance of data protection and implemented the General Data Protection Regulation (GDPR) on 25/5/2018, to safeguard the customers’ data which legally regulated the process of their data acquisition, processing & transfer, to safeguard the privacy of customers.
Using artificial intelligence & machine learning the marketers can process the nature of past attacks & threats and can also identify potential attacks & get notified on time for restricting any threats well before they might even emerge.
Why Use AI & Machine Learning in the Cybersecurity framework
Capgemini Research Institute scrutinized the role of AI in cybersecurity in their report “Reinventing Cybersecurity with Artificial Intelligence”, which deduced that building up cybersecurity defenses is imperative for organizations. In the report, 850 executives from cybersecurity, IT information security & IT operations across 10 countries participated, & expressed unanimous views on inculcating AI-enabled response in the businesses’ arsenal of cybersecurity. They concluded that AI is indispensable for cybersecurity partially because hackers are already using technology to perform cyber-attacks & partially because the AI-enabled systems allow the organizations to better monitor the potential threats & be better prepared to respond to them on time (in case any potential threat arises).
Some of the key takeaways from the report are as under:
- 75% of the surveyed executives agreed that AI equips their organizations to respond faster to breaches
- 69% of the organizations believe that AI is essential to respond to cyberattacks
- 60% of the organizations believed that AI improves the accuracy & efficiency of cyber analytics
Following are some of the main reasons to use AI in cybersecurity:
1. Marketers need to be Amenable enough to quickly Detect, Identify & Respond to Cyberthreats:
Cybercriminals don’t follow a schedule & hence, the data security officers need to be alert 24/7/365 to tackle the cyber-attacks. AI-based cybersecurity solutions are designed to work around the clock to protect the data of the organizations.
Using the trend analysis of past attacks the AI-based platforms using machine learning can help B2B marketers analyze the potential risks. Furthermore, in the case of any cyberattacks, the AI-enabled security platforms can respond within milliseconds to the cyberattacks. If detecting such attacks is left just up to the humans, it may take them minutes, hours, days or even months to identify the associated risks & tackle them.
2. Helps the organizations monitor large & complex networks:
As the networks within the organizations have become larger & more complex than ever before, it has virtually impossible for human beings to handle them all, on their own. With the help of AI & machine learning, not only the organizations can monitor the humongous & complex networks, but they can also broaden the aspects of existing cybersecurity solutions, paving ways to create new ones.
Moreover, machine learning algorithms are capable of learning on their own. Thus, using ML algorithms the past patterns of similar attacks can be monitored & scrutinized to prevent any potential threats in the future.
Thus, AI is a huge boon to the cyber protection of any organization.
3. AI can be effectively integrated with existing Cybersecurity platforms to aid the Human Endeavors:
AI can be easily integrated with an organization’s existing cybersecurity platforms; however, it takes conscious effort & isn’t an overnight task. Systematic planning, training, grass-root level preparation, in terms of scrutiny of resources & intensiveness of an organization, cumulatively ensure that both the system, as well as the employees, can use AI to its full advantage.
AI systems supplement the existing cybersecurity functions in the following ways:
- They help in creating precise login technics based on biometric
- They help with the detection of suspicious & malicious activities leveraging predictive analytics
- They enhance learning & analysis through natural language processing
- They better secure the conditional authentication & access platforms
- With a little bit of organized training, the cybersecurity analysts can easily use the AI technics that have been amalgamated into their internal cybersecurity frameworks. Thus, AI doesn’t replace the critical human etiquette of cybersecurity but supplements them to keep abreast with the probable risks that have arisen with the expanding realm of technology & the Internet of Things (IoT).
4. Reduces Burden on the Cybersecurity Personnel:
Leveraging artificial intelligence & machine learning helps the organizations in saving copious amounts of time that might have otherwise been spent on identifying the probable cyber threats & in devising mechanisms to cope up with them. Moreover, a system entirely based on humans would be less competent and would cost more than incorporating AI-based platforms. In an ever-evolving landscape of cyber threat, machine learning-based algorithms ensure that B2B marketers can have an all-intrinsic & cost-effective platform for tacking the potential cyberattacks.
5. Helps Organizations avoid the Hefty Fines that GDPR Entails:
The General Data Protection Regulation of the European Union (EU) applies to all companies which process the personal data of the citizens belonging to the European Union, regardless of the geographies in which they may be located.
There are substantial fines & penalties for the non-compliance of GDPR norms. While fines range from 10 million pounds or 2% of the global annual revenues of companies to as much as 20 million pounds or 4% of their annual global turnover (whichever is greater); additional penalties can also be imposed if a company fails to report a breach about the data of its customers within 72 hours of breach realization.
Having an AI-based platform will ensure that not only the organizations can cope up with the potential risks about the data processing, storage & transfer of their clients, but are also able to report breaches on time, in case they happen. Thus, AI helps the organizations in carving out a trustworthy platform for cybersecurity with minimum risks for cyberattacks, wherein, even if some hackers manage to get through, the penalties as a result of the aftermath will be much less because of the early detection & mitigation measures opted for by the organizations.
Wrapping It Up
Using artificial intelligence (AI) & machine learning algorithms have numerous advantages. However, just like any new technological renaissance, they also come with some inherent risks associated with the use of AI & machine learning algorithms that the B2B organizations should know about. Some of them are as under:
- Much in the same way the AI has reinvented cybersecurity, it has also revolutionized cybercrime; the cyber attacks use technology to sharpen & improve their technics
- AI may not be practical in all applications as it is very resource-intensive
- AI isn’t cheap
Despite all the above challenges with AI, it still has enough advantages to outnumber the downsides. Small & medium-sized enterprises can invest in affordable security-as-a-service (SaaS) solutions that use AI & are cost-effective too. Cyber attacks can be avoided by inducing cyber ethics in the employees & internal teams alike & by providing some crucial pieces of training on GDPR compliance. Furthermore, training is also required to make the complacent employees, particularly those in the cybersecurity department, understand that the technology isn’t there to replace them but to aid their daily chores for simplification of their tasks.
Cybersecurity researchers & analytics from across the globe are researching continuously to build models for avoiding invasive, adversarial AI attacks. Companies like IBM already have adversarial AI library called the IBM Adversarial Robustness Toolbox (ARI). Major industry players like Check Point, CrowdStrike, FireEye, Fortinet, LogRhytm, Sophos, Symantec & Palo Alto Networks have already integrated artificial intelligence cybersecurity tools & are continuously working on their security intelligence frameworks.
Demitrios ‘Laz’ Lazarikos, Founder, Blue Lava, Inc. quoted the dire need for cyber risk programs as follows:
“A modern cybersecurity program must have Board and Executive level visibility, funding, and support. The modern cybersecurity program also includes reporting on multiple topics: understanding how threats impact revenues and the company brand, sales enablement, brand protection, IP protection, and understanding cyber risk.”
According to a report by Statistica, the global cybersecurity market size is projected to be worth $248.26 billion by 2023. AI has emerged as an indispensable tool for crafting & redefining modern B2B cybersecurity.
We, at Valasys Media, abide by robust GDPR policies to avoid any probable risks with the data breaches. Our services such as Lead Generation, Lead Nurturing & Account-Based Marketing have all been specifically designed to help B2B organizations achieve a high return on their investment, without risking their critical internal & customer data to any potential cyberattacks.
Moreover, we also have Business Intelligence Services at disposal, to help our customers derive meaningful insights from their business data to translate them into actions for customer profiling, retention & acquisition. Data-driven decision making ensures that our B2B clients can optimize their sales conversion rates.
For more insights on our services & to avail them, feel free to contact us.