Original article was published on Artificial Intelligence on Medium
Can AI Transform Cybersecurity?
Being the next big thing in the technology sector, Artificial Intelligence or AI is already a very popular buzzword. With the likes of the Internet of Things, big data, single-page applications, cloud, 5G or virtual reality, AI has also become increasingly popular among the technology geeks as well as the general population. Above all, the majority of the earlier listed technologies finds the implementation of AI in their domain for achieving the expectations. Similar to this, now experts are also finding AI useful for cybersecurity which is one of the major threat to the current generation.
Every time a single user uses any device to connect with the internet, the risk of cyberattack grows. Today, from the big names like Google or Facebook to the kid using personal computer at his or her home is vulnerable to cyberattack, piracy, data theft and hacking.
The data breach has become the major concern for companies or organizations regardless of their size. Because of this, all the big names are continuously pouring money for cyber defenses to avert all the hacking, data theft and other possibilities.
Today, several experts are finding AI and machine learning a boon for data security. So, the question comes, how Artificial Intelligence and Machine Learning can change all? And how future looks with AI for cyberattacks?
Artificial Intelligence and Cybersecurity
Kids from every generation are told about the stories of the world having flying cars or served by robots, however, science hasn’t quite come that far. Yet, we have progressed by many folds in the last few decades. Maybe robots are not preparing our dinners or acting as a valet but most people have their own Siri or Cortana, one of the most developed and advanced voice assistants till now.
All of this happened because of Artificial Intelligence, it can really do a lot of things for humans. Apart from this and others, AI has also made significant strides in Cybersecurity. Numerous cybersecurity providers are now offering products that use AI and machine learning for detecting and responding to cyberattacks. Here AI is being used for network analysis, email analysis, in antivirus, biometric login, detecting threats and so much more.
But why there is a need for Artificial Intelligence for Security?
A large part of cybersecurity is the boring and hectic task requiring trawling of large chunks of data, looking for anomalies or looking for the indicators of a potential attack. Once the threat is detected, further data analysis is required for identifying the details which takes a lot of time and honestly, humans are really bad for doing this task.
Contrary to this, computers don’t get bored and can easily do the data analysis at large scale for detecting the anomalies. Here, artificial intelligence comes in the picture which can provide scalability for ensuring the cybersecurity or the organization. It can help humans by filtering out unwanted data and bringing the most relevant data for analysis.
Use of Artificial Intelligence in Cybersecurity
Still, artificial intelligence is in the developing phase and lots of applications are yet to be developed or explored. Yet, there are several AI-based advanced systems which are helping organizations to defend against cyber threats.
Automated network analysis
Because of the huge amount of data requiring analysis, network analysis is perfect for machine learning algorithms. Majority of the cyber attacker work over the network, so monitoring the network communication itself is a good way for threat detection.
ML-based algorithms can prevent the misuse of common protocols for C2 i.e. command-and-control communications with which hackers can blend easily with the rest of the traffic over the network. They place data in HTTP header values or embed it in DNS) requests which can easily bypass the firewall and increases the probability of being overlooked. Here these ML algorithms can use keyword matching, anomaly detection, stats monitoring and other possibilities to determine whether the given packet is different from others or not. And if different then it’s brought to human attention for future analysis.
Phishing is considered one of the biggest threats to all the organizations and exploits humans by adding malicious links to the emails. Detecting these emails is one of the most focused areas of current researches in cybersecurity.
Artificial Intelligence and machine learning-based algorithms are affective in detecting phishing emails of all kinds. Some programs include simulating clicks on all links present in the email and examining the resulting pages for checking the signs of phishing. Natural language processing is used for determining the word choice, grammar and other signs of similar emails. Further, anomaly detection is used to check the feature of email’s sender, email body, attachments, recipient or other items which can be the cause for suspicion.
Even a human can perform this analysis, however, the vast number of email which people are currently receiving on a daily basis makes it difficult for human beings to do this task. Using these advanced algorithms of AI & ML help users to know the suspicious emails and can provide protection and lessen the vulnerability to phishing attacks.
Machine learning for antivirus
Current issues with antivirus programs are that they are signature-based which results in delays, the applicability of signatures and scalability. There is always a delay between an attack and signature’s availability, and even the use of a large list of signatures is also problematic which makes storage and scanning difficult as well as less efficient.
Antivirus incorporated with AI models can focus on detecting unusual behavior as per the programs instead of matching the signatures. This will help AI-based antivirus to catch zero-day exploits and other previously malware which are unknown.
User behavioral modeling
More than modeling the program’s behavior on any computer, AI-based models for cybersecurity help in modeling the behavior of a user on the system.
It can detect and remediate account takeover attacks which helps attackers to gain the system access by stealing the user’s credentials and using the account through legitimate means. By observing these changes, AI-based models help in detecting the takeovers of the accounts by the attackers and can initiate account lockout or further investigations.
Using AI for biometric logins
Recently, Amazon was targeted and which resulted in a security breach causing compromised email addresses and personal information of various users. This mainly happened as the majority of the passwords are predictable and some are even easily available on the dark web because of previous data breaches.
Many cyber experts believe that passwords are vulnerable to cyberattacks and can be easily compromised. To tackle this, biometric login can be introduced by deploying Artificial intelligence for secure logins. In these cases, AI models can scan retina, fingerprints and palm prints accurately and these logins can be used alongside passwords with devices like smartphones.
Securing conditional access
Various organizations use authentication models for securing data from intruders or unknown individuals. In this case, if any employee with the authority is accessing sensitive data remotely, then the system can be easily compromised using the network. These traditional authentication models are less agile and using AI for this type of security can help organizations to create a dynamic, global, real-time authentication framework that can change the access based on a network or location.
Here AI models can also use a multi-factor authentication wherein the system will collect the user’s information for analyzing user’s behavior, device, network, application, location and data. This will help artificial intelligence-based systems to change any access privileges which will ensure data security on any networks.
What could be the limitations of artificial intelligence for cybersecurity?
Though, we have discussed several benefits of artificial intelligence, yet, there are certain limitations which are obstructing the implementation of this technology for cybersecurity.
First and foremost, building any AI-based system and its maintenance requires a huge amount of resources including data, memory and computing power.
Secondly, all these advanced models or systems require training with data such as datasets regarding malicious and non-malicious codes so that they can learn. More importantly, these data required to train the models need to be very precise and accurate for a higher success rate. Thus, finding and collecting these precise data can be a very difficult, time-consuming and tedious task for many individuals.
As ethical hackers and other cybersecurity experts will use AI for their security, black hat hackers can also use artificial intelligence-based models to check their own malware. This might even result in the creation of more advanced malware or AI-proof malware. Considering all the damage done by normal malware in the last few years, we can easily predict the destruction level of AI-proof malware.
Lastly, similar to the principles used for AI system that protects data, hackers can also develop their own systems which can outsmart AI-powered cybersecurity systems causing more advanced cyberattacks.
Companies which are currently using AI for Cybersecurity?
Cybercrimes account for over trillion dollars of loss by every passing year and is no surprise that with this, the demand for cybersecurity is exploding. It promises to protect data theft and piracy by providing security to the network and systems on which all the organizations and companies are operating and storing their data.
As effective security requires effective and smarter detection, many companies are investing heavily for upping their game with the implementation of using artificial intelligence for achieving their goal. This has sparked a new wave of AI-based solutions, systems and products to keep hackers and other related individuals at bay.
Here are few companies who have effectively implemented artificial intelligence for cybersecurity to make the current digital world more safer.
It is a Seattle based company which is helping businesses and other organizations in identifying the crucial cyber threats. It helps the cyber team to save time which they usually wasted in observing alerts that don’t require immediate attention.
Its engine i.e. Versive Security Engine or VSE for short uses AI which helps in separating critical risks from regular network activity and identifying chains of activities which causes cyberattacks. This keeps the security team to get ahead of any possible attacks.
This company is based in Colorado, USA and provides end-to-end security to several companies or organizations by quickly detecting and responding to any cybersecurity threats.
Logrhythm is using machine learning algorithms for profiling and detecting compromised accounts, privilege abuse, online threats and other anomalies. With its user interface, the security team of any organization can easily and quickly respond to cyber threats.
It is based in California and is known for providing technologies which are helping various businesses and companies to identify any suspicious activities before it enters their network. With the solution provided by Anomali, organizations can not only identify the threats or adversaries but can also collaborate with other organizations for sharing their findings and data
It is another California based company which has successfully implemented artificial intelligence for providing cybersecurity. It provides cloud-native endpoint protection software by the name called Falcon.
It offers prevention, visibility across endpoints and proactive threat hunting to its users from various industries like healthcare, retail, finance and others. Falcon helps security team by automatically investigating online threats and takes the guessing game by analysts out.
This company is based in Boston and is a cybersecurity platform which provides threat hunting, analysis and monitoring. Organizations get greater visibility within their security systems and keep them ahead of any possible threats.
Its platform helps companies to easily determine whether their systems are under attack or not. Normally, threat hunting requires heavy resources but Cyber reasons help by automating the job so security teams of any sizes or skills can benefit from it.
This company is again based in California however it also has various offices in different parts of the world. It is continuously helping other companies for detecting and fighting cyber threats in real-time without any difficulties.
It thoroughly analyzes the network and the data for making the calculations and identifying the patterns of cyber threats. Here, machine learning algorithms use data for helping other companies for detecting all the deviations from regular behavior and ultimately, identifying the threats.
Jask is a San Francisco based company which is using artificial intelligence for cybersecurity by offering an autonomous platform for modernizing the security operation centers by automating the tasks which provide cybersecurity teams more time for investigating high priority alerts. It helps by giving full visibility to organizations such as contextual data for easily identifying cyber threats.
This is the last company on this list. It is providing solutions for cyber threats for almost every part of the IT infrastructure. Majority of a Fortune 5companies are using Fortnite products for a network, web application security, secured unified access and threat protection. Its product called FortiWeb is based on artificial intelligence and web application firewall that uses two layers of statistical probabilities and machine learning for detecting the threats with accuracy and precision.
How does the future look for Artificial Intelligence in cybersecurity?
As already said, artificial intelligence is one field where still a lot of development is left. With further developments and research, I am very sure that it will create new opportunities in the field of cybersecurity giving a big relief to all the companies and organizations. With the advancements of algorithms for cybersecurity, the requirement for humans to weed out false positives from the true data will also decrease which will save time and enable fully automated security systems.
However, the biggest challenge with the use of artificial intelligence for cybersecurity is its high effectiveness can only be used when models are trained with super-accurate datasets, which is still not very easy. Algorithms trained with poor quality datasets or corrupted data are highly likely to miss the detections or else can end up providing wrong false alarms.
Another major concern for using artificial intelligence and machine learning in cybersecurity is that it won’t be just useful for cybersecurity teams but can also empower hackers resulting in AI-powered cyber-attack. As per the Darktrace CEO N. Eagen, “the future of cybersecurity will be artificial intelligence vs artificial intelligence” which in itself raises several eyebrows of security experts.
As the anti-cyber-attack developments will take place in AI & ML field, they will also leverage various cyber attackers and malware authors for a variety of different applications such as AI-enabled botnets, network scanning and automated phishing attacks. Knowing all these probabilities and predictions, it is sure that all the artificial intelligence-based defense systems will have to learn to adapt or grow to meet and counteract all the advanced threat of these fast-evolving systems.