Artificial Intelligence is revolutionizing the field of cybersecurity, playing an important role in protecting individuals, organizations, and critical infrastructures from cyber threats. However, AI empowers security professionals to stay one step ahead in the ongoing battle against cybercrime. Keep reading this article to learn about the role of AI in cybersecurity.
What is the Role of Artificial Intelligence in Cyber Security?
AI systems operate independently and autonomously. The future of artificial intelligence solutions can’t be predicted; however, they shouldn’t be relied upon entirely. The best way to approach it is to think of it as an intelligent and powerful soldier who can make calculations and act intuitively on the battlefield. Nevertheless, machine learning uplifts the potency of defensive force. With this article proceeding ahead, we will learn about the role artificial intelligence plays in the sphere of enabling cyber security with the future of AI in cyber security. Before that, let us overview what is cybersecurity.
What is Cyber Security?
To heed against cyberattacks, cybersecurity is a practice to ensure the protection of information stored on any electronic gadget that is connected to the internet. Additionally, the increasing use of IoT devices by consumers poses more potential risks to the confidential and sensitive information of any person or group. That renders cybersecurity a non-negotiable instrument.
There are different components to cybersecurity that are based on the type of security it provides, some of which are application security, network security, information or data security, cloud security, operational security, etc.
What is Artificial Intelligence?
Artificial intelligence is algorithms that are designed to mimic human intelligence to perform real-time tasks and improvise by using machine learning capabilities to adapt to new sets of information in the form of texts, audio, and video and process them on the integrated foundation of hardware and software. AI programs intake large amounts of data, analyze them for correlations and patterns, and create their own periodical inputs for multiple situations.
AI is a store of domain-specific knowledge that works in three ways:
- Assisted Intelligence
- Augmented Intelligence
- Autonomous Intelligence
What is Artificial Intelligence in Cybersecurity?
As an impromptu action, cybersecurity emphasizes the importance of constantly monitoring and addressing threats before they are able to cause any damage to the system. That being the case, the integration of the role of artificial intelligence in cyber security not only automates manual force processes but also increases the accuracy and speed of workflow. This allows you to maintain security in a streamlined manner.
When it comes to the benefits of AI Cyber Security, there are so many we can talk about. Furthermore, we will go through artificial intelligence and cybersecurity opportunities and challenges as well.
I. Data Asset Inventories
AI is a set of expert systems that use deep learning capabilities to access and gain accurate inventories of all devices, users, and applications running on them. That enables it to offer a data repository with all the information within an enterprise to better categorize and manage the data assets.
II. Securing Authentication
AI secures personal information on a device, such as usernames and passwords, money card numbers, IDs, etc. used by multiple commercial websites active across a business. To ensure this information’s safety, they implement an added layer of security that protects from exposure to infringements like different types of malware, viruses, worms, and trojans.
III. AI Identifies Unknown Threats
Sophistication with time is not limited to just security but also breaches. Hundreds of millions of pests activate annually. Ultimately, any obsolescence in the security system could render the device vulnerable to threats. Embedding the role of artificial intelligence in cyber security makes it possible to provide robust security, allowing it to accurately assess and respond to both existing and unknown threats. This AI-driven approach helps to protect against the ever-evolving landscape of cyber threats.
IV. Monitors Traffic and Detects Anomalies
Even in a medium-sized organization, there is an abundance of exchange of data on a server, and that too with multiple servers on the network between businesses and customers. Unauthorized access keeps privacy at bay and security at demand. The data that travels across the network in an organization might engage potential risks that need to be identified and prevented from causing any action. AI is the perfect solution for security specialists to independently evaluate traffic and ensure that data is kept secure.
V. Intelligent Intelligence Over Time
The integration of machine learning and deep learning capabilities enables Artificial Intelligence to improve over time. It continuously evolves and updates itself on the basis of ongoing information analysis. It analyzes the patterns in the network of an organization and clusters them according to its algorithm, allowing it to detect any further deviations or unrecognized patterns in the future dynamically.
VI. Endpoint Protection from Penetrations
The proliferation of devices within an organization enables a challenge in maintaining security. To protect systems from potential threats at both the hardware and software levels, antivirus programs and Virtual Private Networks (VPNs) create a multi-layered shield of defense.
VII. Risk Protection
IT assets, both tangible and ethereal, need the assistance of AI systems as they are constantly targeted by cybercriminals. Moreover, the intensity of hacking is now elevated to such a degree that any device is capable of being remotely accessed and used from any distance if hacked. With AI, it is possible to predict and track upcoming cyberattacks and prepare suspect sites accordingly.
VIII. Bot Blocking
The role of artificial intelligence in cyber security also extends to blocking bots. Bots do the talks for every organization in the sales and service sector. The comprehension of bots poses threats to company systems and creates traffic. AI discriminates between allowable and safe bots and eliminates malicious ones.
IX. Better Risk Management
Speed is the essence in the current scenarios and systems always appreciate quick evaluation and defense against infiltrations. To give an idea to our readers, as per reports the average of threats an organization receives per day is approximately 200,000 in number. An individual’s ability to recognize, understand, verify, and resolve an issue takes much longer than a previously generated algorithmic calculation does. This reduces the workload of the force and also assists in identifying weak points in a system that can be used to solve problems.
X. Better Overall Security
Business organizations are often threatened by malware, ransomware, hacking, and denial-of-service attacks. Artificial Intelligence prioritizes security measures against all such dangers and provides comprehensive protection. AI creates logical connections between risks and unauthorized IP addresses and drives logical and data-driven insights in real time. These assist security specialists to respond to attacks up to 60 times faster.
XI. Retrieve Systems and Analyze Root Cause
In the event of a system breach resulting in a loss of data, it can be refunded for the entire amount of its data. Additionally, with a deeper analysis, the root cause of the attack can be identified and investigated.
XII. Automated Security
Security automation is conducted where Artificial Intelligence uses machine learning to automate similar security tasks, such as patch management and responding to incidents. Thus, the overload of human resources to specify and supervise the task of security chambers can be reduced. Artificial Intelligence could bolster automation in independent security systems. It would entail organizations to defend against threats in real-time even in the unavailability of manual operators.
Is Artificial Intelligence Way to Future Cybersecurity?
An intelligent agent that swiftly solves side-lines and shoots away user abnormalities, scrutinizes hidden threats in millions of lines of code faster than estimated, or spots malware attacks – what more could an organization ask for? The concept of Artificial Intelligence in cybersecurity is to rapidly recognize malicious attacks and attempts. We learned about the role of artificial intelligence in cyber security. Ultimately, we are sane to say that the future of AI in cyber security is bright and clear.
Considering the development of IoTs, cloud computing, robots, etc. has highlighted the need to emphasize AI in cybersecurity solutions.
- According to Forbes, business organizations are already spending billions of dollars on AI and Industrial IoT (IIoT) to implement intelligent technologies. This forecasts the artificial intelligence market alone to be worth $500 billion by 2025.
- From 2022 to 2029, the Future of Artificial Intelligence in Cyber Security market could grow at a compound annual growth rate of 24.2% and reach $66.22 billion.
- Telecommunications, banking, and consumer products are among the top three industries using artificial intelligence. Global cybersecurity spending may reach $174.7 billion by 2024, according to International Data Corporation.
- It is imperative for businesses to invest in advanced AI-integrated systems in order to stay competitive in the market and face evolving threats. As per a report, over 30,000 incidents of cybercrime were reported in 2019, including 4000 breaches leading to data loss. In 2020, the average cost to an organization that suffered a security breach amounted to over $8 million.
- According to IBM, failure in early detection and combat causes severe losses and in 2022, the average cost of data breaches was $4.35 million globally. The companies that have AI fully deployed and automation programs saved $3.05 million.
- In the 2022 Gartner Board of Directors Survey, the percentage of boards that consider cybersecurity as a business risk has risen from 58% to 88%. Thus, the future of AI in cyber security could be coming with a long road ahead.
What are the Challenges Faced by Artificial Intelligence in Cybersecurity?
However, it also brings with it many hurdles that cybersecurity may have to encounter as the pulsating hike in intelligence does not throw a boundary limited to security. While considering the role of artificial intelligence in cyber security, opportunities do not succumb at the doors of cybercriminals to steal data.
On the other side of the page, some of the major challenges that AI cybersecurity solutions could face are:
I. Affordability of Resources
The adoption of machine learning models and artificial intelligence solutions necessitates the need for specialized equipment, infrastructure, and expertise to manage AI security systems. Considering the significant financial outlay involved in it, not every medium or small-sized company, regardless of the potential threats they face, would be able to fetch such costs. Moreover, the market of experts is comparatively smaller than global demand, which imbibes more hardship in acquiring resources.
II. Dynamics of Economy
Things do not curtail at the establishment of infrastructure, but cart to about administration of IT systems as well. Artificial intelligence incites a high level of maintenance and management. Unless service providers offer AI security as a Software-as-a-Service (SaaS) or Platform-as-a-Service (PaaS) model, not many businesses would be able to carry the costs and resources to keep the AI security systems functioning optimally.
III. Half-Baked Internal Processes
Security components of most businesses extend to only tools and platforms, while improvements in internal processes and the need for cultural changes are overlooked by virtue of continually preventing capital investments. This proves a failure of security systems with artificial intelligence.
IV. Following Data Privacy Laws
Machine learning is an aspect of artificial intelligence and as we already read that AI delivers more with time, it is apparent that to train a security software system, an abundant amount of data and information would be required in order to achieve accuracy. While that case is obvious, it might violate “the right to be forgotten” laws. These systems process large amounts of data and any discrepancy could lead to an undesired theft.
V. Data Quality for Training
Machine learning completely banks on the quality and effectiveness of data used in training its algorithm. It is important to either develop a flexible yet not fragile system of data useful for training or to draw real-time data from existing cybersecurity instances. Additionally, to ensure the accuracy of outcomes, the evaluation of classifiers and algorithm models from multiple perspectives cannot be ignored. Developing a precise range of cybersecurity systems could be a daunting task and would count upon the assistance of experts from tech giants in mathematics and artificial intelligence modeling. This is the only way the role of artificial intelligence in cyber security could be estimated to its complete potential.
VI. Still Non-negotiable Need for Teams to Operate
Withstanding artificial intelligence and cybersecurity opportunities and challenges, it is undeniable that AI cybersecurity programs embedded into companies’ networks, immunize internal defense systems to shorten prediction and detection times and prevent shortcoming breaches. Leveraged power of AI allows organizations to knock down malicious attacks. However, the decision-making power of the intelligent system relies upon its critical and creative thinking abilities for which there is a lot more research yet to be fostered. That means, for some more time, machine learning could not be completely depended upon.
VII. Surrounding Risky Risks
The evolution of threats over time is not a slow process anymore and while all those processes of identification and integration of solutions for distinctive threats continue, more threats emerge in the public domain. The amplitude of implementation is complex. The security system could only resource to detect and flag threats as per its learning. Reinforced learning models are required to improve precision. In the absence of so, AI systems might fail to render accurate results.
Substantiation of AI cybersecurity solutions attracts a steady stream of data available on multiple factors and associated risks. As more than half of the cybersecurity breaches go unreported in the public domain, it endorses difficulty for developers to collate data, compile them systematically for analysis, train the algorithms, and ultimately create a vigorous AI security system.
VIII. Complex Encryptions to Data
From the user end, data encryption is undoubtedly a security measure but the use of advanced data encryption strategies makes it difficult for even the security system to nullify any hidden threat. Deep Packet Inspection (DPI) filters external packets. But the predefined code characteristic used to encrypt can also infiltrate the system as a predator.
IX. Vulnerable to Attacks
Despite being security systems, AI cybersecurity can too attract attacks. The regulations that cybersecurity tools are meant to stay within tend to act offensively against them. Manipulation and biases in the data of an AI model can affect the machine learning language and input, leading to incorrect decisions and privacy breaches of confidential data.
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It is important for organizations to consider the successful implications of AI and improvise their securities to shield them better against damages. With this, we end our article. We hope that you learned about the role of artificial intelligence in cyber security and the future of AI in cyber security. Feel free to reach out to us with your queries and suggestions via the comments section below. Also, let us know what you want to learn about next.