AI and Automation for Cybersecurity

As the attack surface on the web continues to evolve and scale rapidly, there are infinite signals that need to be analysed so as to detect potential risks. This is a daunting and complex task for humans. To overcome this unmatched challenge, Artificial Intelligence (AI) has emerged as a key tool in cybersecurity to help security professionals, IT teams and businesses strengthen security programs and make them effective and efficient.

Artificial Intelligence is a highly valuable technology capable of analyzing countless events and at the same time identifying a wide range of cyber threats. It includes malware, phishing, social engineering tactics and others. AI learns from past cyber threats or attacks and builds a mechanism to detect any sort of deviation from established systems and processes in place. It is interesting to note that AI with more experience becomes more efficient as well as autonomous. 

Automation is another tool that when combined with, or powered by AI, can make cybersecurity productive and highly capable. Since threat actors have increased the use of automation tools, there is no reason why businesses shouldn’t adopt the latest automation tools. It can help in making processes faster, reducing human errors and predicting behaviour. It can chiefly help in different segments such as application security, endpoint security, data security and IoT security. Many experts believe that hyper-automation techniques are the way to go in the coming years. 

AI and Cybersecurity

  • Basics of Artificial Intelligence 

Artificial Intelligence cannot be defined and understood completely today. With the limited knowledge of its capabilities, experts describe AI as technologies that learn and act from acquired data and derived information. Today, AI works as assisted intelligence, helping businesses and individuals to achieve their objectives. It also provides augmented intelligence which involves tasks or processes that cannot be done by individuals and organizations by themselves. Finally, autonomous intelligence is touted as the future of Artificial Intelligence comprising machines which can act on their own and do not need human assistance. 

AI is predicted to solve the most difficult and complex of human tasks in the future. So, how can it help cybersecurity? Find out below.

  • Artificial Intelligence in Cybersecurity 

With the growing sophistication of cyber-attacks and the use of advanced technology in carrying them out, a new approach is required urgently. Artificial Intelligence can be used to increase visibility, detect threats, respond fast and become more efficient. Some of the key areas where AI can lead cybersecurity programs in organizations include gigantic attack surfaces, organizations with an extensive number of devices, countless everyday attack vectors, and lack of security professionals and at a place where humongous amount of data generation happens.

AI in cybersecurity is fast gaining prominence and many have achieved a return on security investment as well. Other fields which can gain support from AI are discussed.

  • Inventory

Large organizations will have a vast number of users, computer systems, devices and software applications in use. IT asset inventory categorization and understanding how critical they are to business functions are important. AI can keep track of all these elements within an organization.

  • Threat Exposure

The cyber attack technology, methods and trends change with time and cyber threat actors time and again surprise business entities and security teams with new threat pathways. Artificial Intelligence can bridge the knowledge gap with the latest global, local and industry-specific threats and trends. It will help security leaders to take quick and timely actions and prioritize certain key actions. 

  • Security Assessment

Every organization employs security tools, software, controls, processes and policies to maintain a security posture and protect against cyber attacks. However, time-to-time assessment of those plans and programs is important. AI can help to better understand the gaps and strengths in the process and make it far more effective.

  • Prediction

AI can be one of the best tools to predict when, how and where your business can be breached at any given time. It can help to bring more resources and reinforcement in that area of concern and overcome any existing challenges too. It can boost cyber resilience capabilities. 

  • Incident Response

AI can further help in providing a clear context for giving a response to security alerts. This, in turn, can help in improving the response rate, analysing the root cause of security compromise and mitigating vulnerabilities and possible future issues from harming the organization.

Examples of AI Adoption 

Google used machine learning two decades back in their product Gmail. The deep learning capabilities have evolved and enable algorithms to self-regulate and adjust in certain events. IBM has utilized Watsons cognitive learning platform for threat detection which is powered by machine learning. 


AI and Cybersecurity Challenges

Artificial Intelligence opens up immense opportunities and possibilities in cybersecurity. However, as with any dual-use technology today, there are multiple challenges as well that face AI in cybersecurity.

One of the concerns raised by many experts is the potential for manipulation of AI, machine learning and deep learning by threat actors to conduct highly sophisticated, faster and destructive cyber attacks. It also poses ethical as well as security concerns. A lot needs to be done to study the autonomous nature of AI, its behaviour and the possible security risks associated with it. 

Automation and Cybersecurity

Automation in cybersecurity primarily means automating several processes such as configurations and alerts. Security managers can often get busy with security architectures and miss out on performing critical tasks. Thus, automation tools can save time by automating functions and assisting security teams to focus on other valuable tasks without worrying about repetitive functions. It can help in avoiding unwanted errors too. 

Some of the ways automation can help cybersecurity are discussed.

  • Data Sequencing

Myriads of security tools collect a huge amount of threat data. However, what they do not normally provide is how to process the data and take the necessary steps. To achieve this objective of data sequencing, business entities need to gather data from within their infrastructure as well as outside. Post this step, identifying similar threat behaviour from the extensive data is done. Thus, the analysis of this big size needs a high level of computing and it is impossible to do manually. This is where automation comes into the picture as it can help the process by making it faster, accurate and more effective.

  • Protections 

One of the goals of the security team is to develop protections and distribute them as soon as a threat is identified. It is essential to prevent the threat from damaging networks, clouds and endpoints within an organization. Now it can become a daunting task to create protections for technologies and endpoints manually. Automation acts as a blessing in developing protections keeping up with the threat and without wasting resources. 

In addition, automation helps in implementing the protections as fast as possible, thereby protecting against attacks for the current case and for the future. 

  • Detection

When a threat actor gains access to a network, the countdown begins until data is breached and it is recognized accordingly as well. To stop an attack, the only possible option is to work faster than the attack itself. One of the ways to perform detection is to analyze the complete environment and identify events or behaviours that look suspicious. This analysis or investigation is quite difficult to do manually. Automation can expedite the process.

AI and Automation in Cybersecurity

AI and automation can facilitate security analysts in many ways. It can provide meaningful insights that make protection and prevention as well as the detection and response process effective. Additionally, it helps in mitigating alert fatigue which in turn powers analysts for making better and more informed decisions. 

Furthermore, combining AI and automation with a zero-trust model will be the most advantageous. Experts believe that the discovery of sensitive data, better context of any given interactions, access management etc. through AI-Automation can help in meeting data privacy standards and regulatory compliance requirements. 

Plus, AI and automation can boost the productivity and experience of security resources working at any business organization. In fact, recent reports have shown that businesses across verticals are embracing AI and automation for this reason alone. The combination certainly has a positive impact on the way in which to deal with the sheer volume of security events and attacks.