Artificial Intelligence for Smarter Cybersecurity

Cybersecurity is becoming as essential as internet connection in the current situation due to high usage of cyber activity, the thread to our valuable data has also increased. As almost all kind of organizations keeps their huge volume of data on a cloud to manage and access it easily, the issue has raised to keep it private and protected. With continuous advancements in technologies, Artificial Intelligence has come forward to secure our extremely valuable data on the internet.  AI, in simple words, is artificial decision-making similar or equal to human decision-making, based on certain unique algorithms and related mathematical calculations. Whereas Cybersecurity is the security measures to be taken to prevent cyber-attacks in the virtual world. AI’s tool likes Machine Learning (ML), Data Analytics, Predictive maintenance has great potential to make cybersecurity strong than ever.

Currently, we have two types of cybersecurity systems, Analyst driven, and Machine is driven, respectively. Expert systems (Analyst driven) are created and handled by qualified staff, and the fundamental of their work relays upon the identification of threat signatures to prevent attacks. For an instance, malicious code or techniques that are used to identify and prevent cyberattacks — just like a fingerprint database is used to capture criminals. Although the downside of this approach is that threat signature can be recognized and entered the “base” after the attack has already been done. So, it becomes very difficult to prevent similar attacks in the future. Thus, analyst-driven systems are not capable enough to protect against earlier unfamiliar attacks called zero-day attacks. On the second hand, Automated systems (Machine driven) identifies potentially dangerous attacks in a system or network based on an analysis of existing data — that is, a typical classification problem solving — one of the basic problems of machine learning.  Automated systems act “ahead of the time”, this attitude can successfully deal with zero-day attacks. In this blog, we will discuss how AI is playing its role in cybersecurity.

Integrating powerful AI tools with the cybersecurity process strengthens the capacity of the human staff of cyber professionals. Just upgrading the existing cybersecurity system and adding a security level does not secure your data completely. The only way to prevent your data from cyber-attacks is to leverage the latest AI technology. AI, powered by machine language, can identify various types of a cybersecurity breach, and notifies the authorities or take apt measures to fix the thread quickly. Though we have embraced AI powered cybersecurity as an emerging necessity of the future, many have also perceived AI as a potential threat to cybersecurity. Many big companies have been the target of security breaches consisting of crucial information like email addresses, personal information, and passwords. Cybersecurity experts have put an emphasis on multiple occasions about the vulnerability of credit card information, passwords, and other highly private information to cyber-attacks. 

In this digital era, companies are highly concerned about their network security as they know that even a minor cyber-attack can cost very high in terms of losing their valuable data along with the trust of users. To ensure their cyber infrastructure, a multi-layer of defense system is developed. In general, these layers start with a strong firewall that can manage and filter the network traffic. The next layer is made up of anti-virus software to protect the structure against malicious codes and files.  and lastly, backups are being done on a regular basis as a part of the recovery plan.  For now, setting up firewall policies, managing backups, and many such tasks require a professional, but AI is slowly changing the conventional approach. With AI-based cybersecurity, an organization can monitor and respond to security alerts received from the AI-based tools. Moreover, smart firewalls have installed machine learning tools that inspect the prospect threat by matching the identified patterns and blocks automatically if found as a threat. ML just not identify patterns but automatically learns new patterns on its own, helping to prevent a new kind of malware. Other than machine learning, Biometrics is the most used tool to enhance cybersecurity. Biometrics uses fingerprints, eye-prints, and palm-prints in conjunction with a password, and common use of this is of the latest smartphone lock. Plus, AI can track users’ behavior on regular basis, preventing any otherwise suspicious activity.

Google’s machine learning tools blocks thousands of spam email is a well-known example of AI in cybersecurity. Other than that, it also uses deep learning tools on cloud video intelligence, on this platform, the videos are stored on the server and being analyzed based on their content and context. The AI algorithms send security alerts whenever something suspicious is found.

Although AI for cybersecurity has many benefits, an extra indulgence of AI could also pose a huge threat as it could be exploited by malicious hackers. AI could be susceptible to malicious cyber programs imitating legitimate AI-based algorithms. With increasing ML-based products, algorithms get overlooked creating a fake sense of security. Besides this, the algorithm labels data as per its nature, which could be malware, clean data, or some other tags. With this “supervised learning” nature of AI, cybercriminals can change the label as per their facility, to input a threat into a system in disguise. Also, scheduled tasks depending on AI can be deceived by advanced hacking campaigns with the use of machine learning. For example, with the new developments in neural networks and speech synthesis, an attacker can emulate a trusted voice or a video. With the advancement in Natural Language Processing, malicious chatbots can ask for sensitive information while acting as someone real behind the screen, leading to more sophisticated phishing and spear-phishing emails. The advancement of AI can create a huge number of fake impressions resulting in almost impossible to distinguish between fake and real. Moreover, to develop and manage an AI system, more resources like memory, data, and computing power is required, which could be difficult to meet sometimes. Along with this, companies sometimes cannot afford high-paying cyber experts with hands-on all AI tools for better security. As even hackers are using AI systems to harm the system, it is a tough task to protect your data with full assurance.

Solutions to AI limitations

To minimize the drawbacks of AI for cybersecurity, here are some tips to keep in mind.

• Hire a cybersecurity company with professionals who have experience and skills in various facets of cybersecurity.
• Keep checking for potential gaps in the system and network on a regular basis and fix them on the spot.
• Use filters for URLs to get prevention from malicious links which may have a virus or malware.
• Use inbuilt firewalls and other malware scanners to secure your systems and upgrade them frequently.
• Manage your outgoing traffic and have access to exit filters to block this type of traffic.
• Constantly review the latest cyber threats and security protocols to get updates about risk management.
• Perform regular audits of both hardware and software to make sure your systems are healthy and working.

Taking actions on mentioned steps minimizes the risk of cyber-attacks, though there is always a sword-swinging upon your data. It is best to also strategize a recovery plan, in case of data lost.