Businesses and organizations have to be at their best to avoid becoming victims of cyber-attacks. However, it is difficult to predict a cyber-attack and how it’s going to unravel. It is complicated to know what the next significant threat will be. Without a doubt, cyber threats are becoming more prominent, sophisticated, and involving big numbers.
The cybersecurity landscape has become increasingly complicated in 2020 with the widespread adoption of remote work. The COVID-19 pandemic has forced organizations and small businesses to organize work remotely. The shift to remote work has exposed organizations to attacks. During the pandemic, the focus of information security teams has been on securing their remote workforce.
Other unique cybersecurity challenges include widespread use of IoT devices that increase attack surfaces, brute force attacks, phishing attacks, ransomware, credential stuffing, and nation-states’ intellectual property threats. The protection and defense of networks and data have become extremely difficult.
Reactive cybersecurity has been shelved as a way of protecting networks and sensitive data. The fact that attacks have become automated has rendered reactive cybersecurity ineffective. Artificial intelligence (AI) in cybersecurity introduces a proactive way of fighting cyber threats.
Artificial intelligence and machine learning (ML) are now essential cybersecurity tools. AI is now traversing cybersecurity aspects, with organizations and security teams relying on technology to fight off threats. Analytics, a necessary AI technology capability, has helped to analyze data and risky behavior from millions of cyber incidents to identify potential cyber threats and strange events on employee accounts. In real-time, analytics helps so that security teams can act promptly to stop threats. Additionally, AI is assisting in ensuring business continuity if an attack occurs.
AI algorithms become as useful as the human beings behind the technology. Cybersecurity professionals must harness the potential of AI by understanding how it can be used in analyzing data to detect potential threats and inform the next course of action. Cybercriminals stop at nothing in creating and tweaking malware code to evade detection by security software and methods. It is a never-ending struggle between defenders and attackers.
The identification of every variation of malware is not easy when cybercriminals are becoming smarter and more sophisticated. The use of AI and ML makes defenders stay ahead by allowing them to stop unknown and newer types of malware and cyber threats.
ML is particularly useful in solving unknown or not so explicit threats. It may underpin the creation of anti-malware solutions since it can draw upon the machine learning database of previously detected threats. The new form of malware can be checked against the database by examining the code, identifying it, and blocking an attack. The same is true when malicious code has been bundled within delicate pieces of code to hide the delivered payload’s intent. Machine learning techniques have been successful in uncovering attacks and protecting users against new malware campaigns.
Besides uncovering new malware variants, AI and ML can be used to boost cybersecurity efforts. An AI-based network monitoring tool is one such method being used to track what network users are doing daily. By developing a clear picture of typical behavior, the information is then used by cybersecurity teams to detect risky practices and act accordingly to protect a network, users, and sensitive data. This means that if an employee clicks on a phishing link, the system will detect this as abnormal behavior and flag it for potential malicious activity.
AI is really about the ability to adapt and respond to the continually changing cybersecurity landscape. AI helps defenders understand the relevance of cybersecurity measures, the consequences of a breach, change in behavior, react intelligently, and develop a proportional response to attacks in real-time.
AI and ML have given businesses agility and flexibility to detect, prevent, respond, and recover from cyber-attacks. Through ML, companies can spot threats, block malicious intrusion, prevent deployment of malware, and prevent theft of data. All this can happen without affecting the daily running of the business. Additionally, a network must not be shut down if malicious activity is detected on a single machine. A timely and proportionate response can be initiated to prevent the disruption of day-to-day activities and decision-making processes.
Challenges to Be Overcome
AI and ML-based security tools may be programmed incorrectly, leading to algorithms missing critical indicators of a potential cyber threat. Serious problems may arise if a device has not been coded to take into account specific parameters. Therefore, any AI security tool is as useful as the people behind it. Keep in mind that cybercriminals may also use these technologies to escape detection and become more effective in launching attacks.
AI and ML cybersecurity technology doesn’t replace cybersecurity personnel within the organization. AI is not going to solve all cybersecurity problems. The use of technology should be anchored on the expertise and continuous adjustment by security personnel. AI will not entirely replace security personnel required to evaluate and adjust models to detect vulnerabilities better and prevent attacks.
AI is an emerging technology that is feared might make cyber-attacks more dangerous and more difficult to detect. Cybercriminals may have already started using AI to carry out their nefarious activities. AI-based deepfake technology has already rattled the cybersecurity industry since it has been used to spread disinformation or abuse individuals via fake videos. Cybercriminals used AI-generated audio to impersonate a CEO and hoodwink employees’ voice to transfer approximately $240,000. It has become an arms race between defenders and attackers in the use of AI technology.
Finally, the development and improvement of AI-based cybersecurity tools and their correct use along security teams will help secure businesses against smart and potent cyber threats.