The world today is heading to become more digital at an astonishingly fast rate, and in the future, this is going to be much faster than what we are witnessing today. The term digitalization depicts everything that is moving at a lightning speed and the end-consumer is able to get what he wants almost instantly as the service provider now has the means of delivering it. With several advantages and benefits that this digital era brings in, there are also many setbacks associated with it.
One of the most destructive threats that it holds is the risk of our private information being leaked to any untrusted third-party. The last few decades have witnessed an increased number of cases pertaining to identity theft, money loss, and data breaches. Cyberattacks in nature are present everywhere and time and again have been affecting individuals, businesses as well as government organizations in a similar manner.
We are heading towards an era that will give the cybercriminals an easy approach to reach their targets present anywhere in the world, and thus, the need for cybersecurity has become more critical now.
AI and Machine Learning for Enhancing Cybersecurity
Both- AI and machine learning can be used for identifying and safeguarding the systems from one or other forms of the latest cybersecurity threats. It is clear that emerging threats operate so fast and thus make it extremely challenging for traditional security tools to highlight the tackle cyberattacks.
AI and Machine Learning could be applied in the following ways to enhance cybersecurity-
Detecting and Predicting New & Complex Threats
The malware attacks tend to grow with time, thus, organizations are always in the need for more dynamic approaches such as AI and Machine learning, when they look to work against the malware attacks. AI systems that empowered by Machine learning often leverage the information gathered from previous attacks.
The nature of previous attacks is processed along with threats and even identify other possible potential attacks that might take place in the same way. AI and ML systems could be utilized for looking out and providing notifications regarding the emerging attacks and this could be beneficial for controlling the threats at a very early stage.
Reducing the Burden of Cybersecurity Personnel
Machine learning along with artificial intelligence can be used for improving cybersecurity and also helps in saving a considerable amount of time and money for an organization. Machine learning is the most effective tool when it comes to accessing large volumes of data and this data could help the systems to learn and analyze and reducing attacks by the means of predictive analysis. The number of security alerts appearing regularly can be quite overwhelming for the security team in an organization. In the absence of AI and ML systems, security experts are forced to spend huge time behind manual identification of the threats. In the worst case, they might even have to wait for an attack to occur for carrying out diagnosis investigation of such attacks.
Database Updation and Identification of Mass Movements
AI holds great potential when it comes to updating the databases. It analyzes logs from diversified sources and detects the new and imminent threats. AI can be used for “connecting the dots” for identifying new threats and vulnerabilities spread by hackers. It can also be used for identifying malware and spyware trends by analyzing data present across several channels. AI can be used for detecting new malware before-hand and minimize the damage on a larger scale.
Identifying Unusual Activities
Along with detecting large scale malware movements, AI could also be used at an individual level for scanning a system for any abnormal or unusual activity. By constant scanning, large data can be collected for determining the instance at which a given activity is unusual. The users can regularly be monitored for detecting unauthorized access and in case of abnormal activity, certain parameters could be placed for determining whether it is a threat or a fake warning. Machine learning could be used with AI for determining what a “normal” activity means and what all should be considered as “abnormal” activity. With advancements in machine learning, AI could become better for determining the finest of abnormalities indicating something has gone wrong.
AI and Machine Learning for Cybersecurity: Boon or Bane?
The Positive or Boon Side
With a tremendous future potential, there have been advancements in technology having relevant impacts on the cybersecurity domain. One significant game-changer in the domain of cybersecurity includes the tools and techniques that are developed and supported by AI.
Following are some of the major advantages of using AI for cybersecurity-
AI can easily automate the process of detecting advanced threats. It can analyze the large volume of activity that takes place through a company’s network along with the massive volumes of communication channels like email, files, and websites that are accessed by the employees. AI may not be fully accurate in detecting threats, but still, it can identify a majority of activities and samples that may be hostile, thereby allowing the humans to focus on more suspicious and potentially malicious threats.
AI has the potential to identify the malicious attacks that are based on the application behavior of the network. With time, AI cybersecurity solutions can learn about a network’s regular traffic and behaviors and thus, differentiating the deviations from the normal.
The Negative or Bane Side
With observable potentials of AI, the probability of attackers weaponizing it and using it for boosting and expanding their attacks remains a huge threat. A major concern that remains present at all times is- hackers have could use AI for automating cyberattacks on a large scale. The domains of cybercrime and cybersecurity are going to change for the worst and if these domains learn how to use AI and machine learning for destructive purposes. New progress in AI could give rise to new kinds of cyber threats and AI might even hack into the vulnerability of a system at a speed that can be faster than that of humans.
Following are some major setbacks that AI could offer in cybersecurity space-
The cybercriminals can now acquire AI-driven cybersecurity solutions and even perform bugging of their malicious programs against them. This results in the theoretical creation of AI-proof malware. The cybercriminals can also possibly use machine learning for understanding what the AI-based systems are looking for and thus can pollute the sample to prove that their attack is genuine.
AI systems are not advanced enough for reporting 100% accuracy in distinguishing between a malicious and a kind activity. For protecting a network and its application along with data, most of the cybersecurity solutions (inclusive of AI-based solutions) often make a mistake on the caution side. Thus, the user can do the marking as anomalous and threatening whenever he’s in doubt and thus, these alerts need to investigated by domain-experts.
What Future Holds for AI in Cybersecurity
AI in cybersecurity has a very promising and potential future. Such promises are always accompanied by one or other forms of risk. The opportunities have been widely explored, and thus there needs to exploration for the potential challenges and vulnerabilities that might hinder its usage in this domain. Firstly, all the systems powered by AI are also being used by cybercriminals and hackers and this can be a high-security threat for machines and their associated data. The future of AI in cybersecurity depends majorly on the effective use of the technology for safeguarding the data and the key processes.
Thus, AI along with ML is going to be the key part of the next-gen security, allowing elevated degrees of cybersecurity. AI and ML could be together used for achieving online-hygiene and tackling the attacks of cyberattacks are going to be the breakthrough idea that is going to help the organizations in securing a modern IT environment against the changing threat landscapes.
