The Future of Business Security: AI Detection and Prevention

The current state of business security

Traditional business security methods before AI security detection tools were sufficient and worked for a while, but they all had one clear, defining pitfall.

Generally speaking, commonly used security methods such as firewalls, anti-virus software and access control systems could only identify threats after the initial attack to security had already happened rather than preventing them in the first place.

This is where AI has elevated the security game, putting the businesses that use AI at an advantage against hackers.

Traditional business security methods

A firewall uses previously established security measures to monitor incoming and outgoing traffic.

This method of security allows or blocks traffic based on a programmed set of security rules. This includes blocking malware, reacting to any attacks and carrying out assessments to detect suspicious activity.

These are often established as a first line of defense for many security networks as they can easily filter which networks should be trusted and which should not.

Likewise, anti-virus software is programmed to detect and eliminate viruses or malicious software from your system. Unlike firewalls which act on a network level, anti-virus software is more of an endpoint security solution.

Oftentimes, anti-virus software comes free on computers or laptops and can help to prevent theft, warns about potentially dangerous websites and blocks phishing or fraud.

Access Control Systems, or ACSs, rely on authentication from the user and is a means of controlling who can access or log on to certain portals or places.

This form of security is often used in conjunction with another form of security, such as a firewall or antivirus software, as access control systems have more of a direct impact on logins and keeping people out of certain accounts, as opposed to detecting or removing malware or ransomware.

Limitations and vulnerabilities of current security methods

The main weakness of traditional security methods is their inability to detect new or evolving threats and their susceptibility to human error.

Although they are efficient in counteracting already understood and discovered threats, rather than preemptively being able to block attacks or identify areas of vulnerability. For businesses, this may be unhelpful if new weak spots are detected often after the hacker has already exploited them.

Unlike AI, current security methods do not investigate the identified problem themselves either. Instead, they simply detect the threat, leaving a lot of human work required to understand and investigate the threat. Meanwhile, AI can detect a potential threat by using data from all over the world, appeasing the problem before it arrives at your doorstep.

AI detection and prevention

Cybersecurity uses AI as detectors to diminish the chances of an attack or data breach by analyzing expanding global data in conjunction with any threats in your systems, thus identifying new types of attacks. This is, therefore, a quick and efficient way to reduce breaches and efficiently improve security.

How AI can improve threat detection

AI can improve threat detection by registering what "normal behavior" is to then be able to efficiently pick out malware by spotting the differences. This includes attacks or threats that have not yet been identified. In its ability to sift through a large quantity and breadth of information, AI technology is able to efficiently sort through staggering amounts of data to identify a problem—something that humans are unable to do in the quick, routine manner that an AI can.

Human judgment in certain situations can lead to errors that the AI machine would have made. However, AI is far from perfect, with a higher likelihood of false positives occurring. Therefore, many argue that the strongest form of cybersecurity is a combination of both traditional security measures and AI-powered methods.

Benefits and limitations of AI for security

A key benefit of using AI for security is improved threat detection and being able to detect more threats or attacks than the average traditional security alternatives.

In turn, this therefore reduces the response time as the AI detector system is able to quickly and efficiently detect and remove the malware, even if it has never been detected before and respond to the threat accordingly.

AI can also enhance network security by learning network traffic patterns and recommending better security policies to protect your data. Solutions to handling risks that your cybersecurity may be facing give us, as users, a better understanding of how to mitigate or avoid the problem the next time it may occur.

To further strengthen your security systems, AI detection tools also flag the user with any vulnerable points in the system that hackers could pinpoint and attack.

Again, this mitigates any damages by protecting the points of vulnerability a hacker could target and flagging them before any attack has had the chance to occur.

AI technology can also keep an eye on your data center—full of things that may usually slip under the rug. This could include things like backup power, cooling filters, power consumption, and more. This can save you money in the long run by alerting you to any issues so you can repair it before your equipment suffers severe malfunctions out of the blue.

However, not every company has the time or resources to input all the high-quality data AI detection tools need in order to perform at their best. This reliance on quality data is essential in the AI tool to run efficiently and precisely. It is also time-consuming and expensive to pump money into the necessary computer resources and memory required for AI to work to the best of its ability.

Hackers can also use AI technology, making the cyber attacks launched more complex and advanced too. For instance, AI could be used to disguise malware in a way that's similar to detecting it, counteracting the added layer of security AI gives.

On a similar note, 'neural fuzzing' , a technique that is used by AI to sift through large amounts of data and text, can also be used by hackers to learn about the weaknesses in a system, although there has been recent research into creating more complex code to minimize this issue.

Additionally, the chances of potential false positives increases with AI detection systems. Unlike more traditional security techniques, AI detects the majority of threats, even those that have not yet happened.

This, therefore, causes a lot of false positives to occur. False positives can become an issue because it wastes the time and resources of your team during the investigation process, potentially distracting them from actual cyber-attacks or malware breaches.

The future of business security

So, with new advancements in AI changing the security game, what will new business security systems look like? Will they all be powered in AI?

Well, it's likely that there will be a mix of the traditional security systems that we know with AI technology also because there are a number of benefits to using AI for security, yet there are still some limitations.

Advancements in AI-powered security

AI-powered security has advanced greatly as we progress towards creating an AI tool that is stronger and more progressive.

Growing intelligence has meant that AI-powered security is now more efficient than ever, with a wide database allowing it to have solutions to unsolved problems and identify even the smallest of threats. One of the key ways in which this has developed is through the enhancement of accuracy.

AI uses deep neural networks and deep learning to create an ever-advancing system that now has even more enhanced accuracy.

With each experience, AI gains the more it grows as a system and can provide further accurate results. This has astonishing capabilities, generally speaking, with vast and rapid improvements in medical scenarios, such as identifying illnesses in scans, but is also very beneficial in AI-powered security tools.

Although there is no way for it to be fully reliable, this advanced accuracy has breached past human capabilities with its consumption of learnings - once the AI has been fed data or taught something, it can learn and grow with this knowledge, ensuring it is able to defend against malware, even if it has been edited and mutated to a new form.

There are many AI security detection tools that are available for use and are currently in the market. These include AI cybersecurity companies like CrowdStrike, which specializes in detecting threats and then resolving the problem. Their main focus includes industries such as finance, healthcare and retail.

Other AI cybersecurity companies may be better suited for your business, such as SparkCognition, which similarly hunts threats from malware, ransomware, and more and specializes in a range of industries, including aviation, finance, and manufacturing.

Companies like Tessian use AI to specifically protect against problems with harmful email, including phishing scams and data breaches. Then there are other companies like Darktrace, which focus on identifying patterns in attacks to then, in turn, spot deviations in normal behavior.

Impact of AI on business security

In the long run, the increased efficiency of AI and the proactive approach it takes to the ever-expanding internet space will result in lower costs of security expenses.

Although the lump sum for AI may initially be dearer, AI security means you can save expenses and work on monotonous security routines that the AI can easily cover for you. Therefore, AI technology has tightened cybersecurity and internet security for businesses and has become a very vulnerable asset amongst businesses.

Concerns for the future

Apart from the broad concern of AI in general concerning issues of plagiarism and a lack of need for human-written text, many worry about the long term effects of AI. Like all online systems, AI can also be hacked, malfunctioned or directly attacked.

Although the whole phenomenon of automatic intelligence is still relatively new, this is not to say that hackers or those who try to weave between the lines of internet security will not find a way to purposefully manipulate the AI's data.

This disruption to the data could cause problems for those relying on the intelligence system as a means of protection and security. Of course, rigorous tests are carried out to try and prevent these problems, with policies being put in place, but it is not outside the realm of possibility.

Strengthening the functionality of AI will be an ongoing process and will take time, although it is already proving to be a reliable solution, for the most part. However, when faced with small quantities of data, AI tools do not work as well - an issue for smaller businesses or businesses without the time to provide the tool with large swathes of input.

Implementation of AI security solutions

To reduce losses or any further costs, AI-based cybersecurity tools work alongside human intervention for the best results.

With AI tools tackling all of the simpler security problems, this leaves human analysts to focus on new, more complex issues while AI detection flawlessly analyzes and solves cyber-security issues.

Different AI detection tools have different strengths and focus, so when choosing the AI tool that is right for you, ensure that you read through its purposes carefully to see if they align with what is best for your business.

Stay ahead of the competition and stay protected from cyber criminals by considering a combination of both traditional security methods and AI technology when setting up security for your business or even for personal use.

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