Year after year, the technology industry expands at a breakneck pace, resulting in increased data transmission. Software engineers and cyber security analysts rely on artificial intelligence and machine learning algorithms to better defend against hackers due to the vast data size.
By analysing the flow of online traffic, this ground-breaking technology will be able to predict cyberattacks before they happen. And, if AI can predict future threats, it will be better able to protect against them and eradicate them before they cause havoc. What if, on the other hand, hackers can use artificial intelligence to generate more powerful malware capable of breaching even the most sophisticated cyber security systems?
Artificial intelligence is being used by increasing cyber security organisations for a variety of reasons. In this essay, I'll discuss the benefits and drawbacks of AI in cyber security.
AI in Cyber security
Machine learning offers a wide range of uses. It's used by researchers and IT professionals in fields as diverse as medicine, mechanical engineering, marketing, astronomy, and more. The number of users is increasing as devices become more networked and reliant on the internet.
Hackers now have access to more data through destructive activity. They frequently employ AI technologies to limit the number of times malware is exploited.
The Android apps on the Google Play Store, for example, use adware to gain access to your phone. When users launch an app, the latter is software that automatically downloads advertising to their devices. AI is frequently used in such apps to create customised advertising content. On a daily basis, a typical mid-sized organisation receives up to 200,000 security threats. Even the most skilled experts will find it difficult to track because of this. Each analyst would have to go over each threat separately.
However, by repeating the process, more dangers and assaults may go unreported.
Pros of enlisting AI for cyber security
By predicting and preventing threats, artificial intelligence can help to improve cyber security and provide greater protection.
- Processes that are duplicated are reduced -
Detecting possible risks is a process that is repeated and duplicated. Analysts can save a lot of time by using AI-driven algorithms instead of repeating the same process on millions of datasets. In the meantime, cyber security specialists can work on improving algorithms or learning more about new threats on the internet.
- Machine Learning Aids in the Fight Against Scams -
To avoid spam emails and phishing scams, Google employs machine learning algorithms. Phishing is a technique in which hackers trick consumers into clicking on a link that appears to be a popular website such as Facebook or PayPal. Google's algorithms aid in the detection of dangerous emails, allowing users to be warned and protected.
- AI is capable of handling Large Amounts of Data -
Cyber security automation aids businesses in managing massive amounts of data on a regular basis. A robust machine learning algorithm, on the other hand, can predict risks before they occur. It can also quickly skim through a large amount of data to find them. In a sea of chaotic data, the automated procedure streamlines the practise of assessing each cyber security occurrence.
- Algorithms improve their Learning Capacity Over Time -
Machine learning and deep learning algorithms are used by AI-driven applications to learn. They are able to discern patterns and predict changes. The algorithm groups them together once they've been recognised, allowing for the detection and removal of prospective threats with comparable characteristics.
Furthermore, AI cyber security solutions become familiar with typical network activity and can immediately identify any changes before taking action to eliminate threats. Such algorithms can also aid IT security experts in identifying hazards and resolving problems.
- Threats that aren't well-known are easy to spot -
Every day, hackers release millions of pieces of harmful software. According to G Data Software's study, 7.41 million new malware samples were discovered per day in 2017. That number far outnumbers the abilities of professional hackers who frequently play hide-and-seek with the most recent virus.
Instead, automated cyber security looks for changes in the network to spot new threats.
- Improved adaptability -
Machine learning algorithms and deep learning are used by AI-driven applications and systems to learn. AI can readily grasp various IT trends and make modifications to its algorithms based on the most up-to-date data or information using these techniques. In the same way, AI in cyber security is conversant with complex data networks that can swiftly discover and eradicate security problems with minimal human participation.
Cons of enlisting AI for Cyber security
While automated cyber security has a number of advantages, it also has a number of drawbacks. Here's a list of them.
- AI is costly -
The growth of artificial intelligence is primarily due to data science and big data. As a result, experts in this subject are few or impossible to come by. Many businesses are at risk of overspending due to the scarcity of cyber security AI solutions.
- Unemployment -
Automated cyber security, like other AI-driven solutions, poses a risk of job loss. Many businesses do not require IT experts to manually test their networks. Artificial intelligence, on the other hand, is capable of completing the task.
- Evolvement of cyber threats -
Artificial intelligence, as previously said, can process a big amount of data and swiftly recognise a threat in the midst of turmoil. AI-driven solutions, on the other hand, require continual upgrades and improvements to stay up with evolving threats. Hackers can be resourceful and create a variety of changes to mislead a programme.
Before becoming available to the general public, AI systems are frequently subjected to extensive testing. Researchers open-source their work and publish it in open-access journals so that anybody can see it. That includes hackers, who can use such data to plan assaults ahead of time.
- Cybercriminals are also well-versed in Artificial Intelligence -
Everyone has access to AI knowledge. As a result, fraudsters can easily obtain AI-generated cyber security solutions and utilise them to exploit malware. They can construct malevolent, AI-proof applications that can breach websites and organisations more effectively.
Machine learning is used by cybercriminals to discover how AI-based cyber solutions are trained. They can also learn how to work together to avoid cyber threats. This technique will also be used by hackers to contaminate malware and make it appear innocent. IT security professionals will not focus on a "harmless" danger in such a case. They'll concentrate on what they consider to be the more dangerous threat, while the masked threat continues to harm your data.
- The invasion of privacy -
Biometric systems and other AI-powered technologies may pose a threat to our sensitive and secret data. These devices have the ability to send our data to third-party providers, who may then misuse it, infringing on the privacy of both individuals and businesses.
Today's Major Cyber security Challenges
Despite cyber security breakthroughs, internet attacks are getting increasingly deadly. And the challenges that the industry is facing aren't helping matters.
- There are far too many IT systems spread out throughout the globe, making manual tracking more challenging. Despite the fact that many of them have successful manual monitoring, the entire procedure is difficult. Experts in cyber security must overcome infrastructure differences.
- Threat-tracking by hand can be costly and time-consuming. As a result, more attacks may go undetected or untreated in a timely manner.
- Because of the reactive nature of cyber security, we can only tackle problems after they've occurred. For security specialists, predicting threats before they cause damage to IT systems is a huge task.
- To conduct a cyberattack, hackers frequently modify and mask their IP addresses using various methods. They use VPNs (Virtual Private Networks), proxy servers, TOR browsers, and other tools. These methods allow hackers to remain anonymous and undiscovered. As a result, in order to safeguard your data, you must equip your smartphone with these vital tools.
Role of Microsoft in the evolution of AI in Cyber security
In 2017, the evolution of AI in cyber security began. Microsoft announced the acquisition of Hexadite, an artificial intelligence cyber security firm based in the United States and Israel. That's when many businesses understood that the only way to deal with massive amounts of data was to use an efficient algorithm.
The company's cutting-edge technology was one of the key reasons Microsoft purchased it. That technology will be used in Windows Defender's Advanced Threat Protection functionality. It will be able to predict zero-day assaults, ransomware, and other threats thanks to the AI-driven upgrade.
Final thoughts
AI continues to be integrated into futuristic cyber security solutions by cyber security companies and organisations. That trend was expedited by Microsoft's game-changing acquisition. In the battle against cybercrime, AI technologies will improve and become even more effective.
For every firm to run successfully, the interaction between AI and cyber security is critical. It's a proactive method that gives you insight into the ongoing operation so you can anticipate and respond to threats. It encourages the use of artificial intelligence to make data-driven judgments. To comprehend the relationship between AI and cyber security methods, protocols, rules, procedures, and strict measures are required. This gives you control over your risk management system and aids in the development of a cyber security strategy.
With that in mind, there will be a slew of additional benefits to adopting automated methods to combat hackers.
Do you believe that Artificial Intelligence will be able to eliminate cyber threats? In the comments section below, express your thoughts on the subject.
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