Will The Evolution of IT Security Halt Hackers
In the wake of high-profile data breaches, there has been a growing concern about data privacy. IT professionals are under increasing pressure to protect business data — and fortunately, the evolution of IT security is delivering the goods.
Although you wouldn’t think that is the reality if you’ve been reading mainstream media.
Oh yes, personal data is not the only thing hackers have been stealing. A series of high-profile data breaches have stolen the headlines as well.
Scaremongering, of course, is the nature of the media-marketing beast. The evolution of IT security meanwhile, tells a different story.
Having said that, cybersecurity firms could argue that jolting business owners to take a stance against threat actors is a necessary tactic. These alarming statistics suggest it is:
- 51% of small businesses have no cybersecurity measures in place at all. (Source: Digital)
- 36% of small businesses are “not at all concerned” about cyberattacks. (Source: Unknown)
- Only 14% of SMBs are prepared for cyber attacks (Source: Accenture)
- 17% of small businesses encrypt data. (Source: AdvisorSmith)
- 87% of small businesses have customer data that could be compromised in an attack. (Source: Digital)
- 82% of ransomware attacks in 2021 were against companies with fewer than 1,000 employees. (Source: Coveware)
- Small businesses receive the highest rate of targeted malicious emails at one in 323. (Source: Symantec)
- 47% of businesses with fewer than 50 employees have no cybersecurity budget. (Source: Corvus Insurance)
Despite this rather grim reading, Micro Pro are not into scaremongering. That’s because we are actively seeing how the evolution of IT security is protecting business networks.
We are consistently seeing headlines that scream how “ransomware is on the rise.”
The headlines are not true.
According to a graphic published by antivirus guide.com, ransomware attacks have fallen from a peak of 188m in the second quarter of 2021 to 106m in the second quarter of 2022.
Having said that, it is true that ransomware is the most common form of malware. Perhaps what the headlines mean even if that’s not what they imply.
But cybersecurity statistics show the reality — the evolution of IT security is doing a good job of keeping bad actors at bay. The number of successful data breaches is going down.
In the UK, IT Governance reported 1,063 security incidents in 2022, a decline of 14.8% from 2021 (1,243).
The US also saw a fractional decline from 1,862 breaches in 2021, to 1,802 in 2022.
We expect 2023 to be an even better result for the evolution of IT security.
Listen, You Need IT Security
Let’s not make light of cybersecurity. The threat is real and the damage of a data breach could be devastating.
The evolution of IT security will likely be characterised by an ongoing arms race between attackers and defenders. Both sides are constantly developing their tactics and technologies and will continue to do so.
However, we feel the improvement of IT security in 2022, is largely due to more cyber awareness — probably thanks to the sensationalist headlines. By staying vigilant and proactive, organisations will minimise their risk of a data breach.
It’s worth noting that 82% of data breaches are caused by human error. As a matter of fact, employees are responsible for more lost data than hackers are. This is from the Information Commissioner’s Office which dishes out penalties for data loss by whatever means.
Moving forward, there is likely to be a greater emphasis on the safe storage of sensitive data. Whilst cloud storage aids data recovery and protects forms against ransomware, protecting personal data could be the difference between business continuity and business kaput.
According to reports, one [unnamed] US bank reported that 82% of businesses fail following a data breach due to a loss of customers and investors.
Herein lies the reality for small businesses. Data privacy laws state that firms have an obligation to inform affected parties about a data breach.
And because consumers are increasingly concerned about the privacy and security of their personal information (thanks to media headlines), 68% of consumers lose faith in brands that cannot protect their sensitive data.
The damage to your trust and reputation will cripple you.
What Does the Future of IT Security Look Like?
Emerging technologies designed to improve IT security are becoming more prevalent. Together with a growing awareness of the ethical considerations surrounding the collection, use, and sharing of personal data, the next evolution of IT security promises to keep IT security chiefs one step ahead of hackers.
The next wave of IT security will feature the increased use of artificial intelligence (AI). This emerging technology has the potential to revolutionise the evolution of IT security in a significant way.
That said, as AI technologies continue to develop, it is likely that both attackers and defenders will find new ways to use this technology to their advantage. AI is not a silver bullet for cybersecurity.
Attackers could use AI to automate their attacks. But defenders will have the edge because they have the ability to detect and respond to threats more quickly and effectively.
The only way hackers can win the cyber war is to consistently create new malware that IT security software can’t detect.
Whilst there is a risk that AI-based security systems could produce false positives or overlook subtle threats that a human analyst would be able to identify, it’s better to be alerted to a false alarm than an alarming message informing you that your data has been captured.
Types of AI Solutions in IT Security
Gartner predicts that AI-enabled fraud detection will drive more outsourcing of enterprise trust and focus on security education and awareness by 2025.
Designing cybersecurity solutions will leverage data to improve decision-making and demonstrate security performance. Ai will facilitate this using various methods — all of which are existing technologies that we expect will be upgraded.
Advanced Threat Detection (ATD)
ATD uses machine learning algorithms and other advanced techniques to identify and respond to security threats in real time. The software continuously monitors activity on the network to identify suspicious behaviour that represents potential threats.
The software is capable of analysing large amounts of data, including network traffic, endpoint log files, user behaviour and other sources to identify patterns and anomalies that might indicate a security breach.
Threat detection analysis identifies potential security threats in the background and informs IT security teams of vulnerabilities, in your system. AI software can even take automated action to mitigate the threat without human intervention, such as blocking network traffic or isolating infected endpoints.
We expect the evolution of AI security systems will improve their accuracy by using machine learning techniques. This will allow AI to identify even more subtle and complex patterns of nefarious attempts to access business data.
Automated Security Tasks
AI can be used to automate routine security tasks, such as monitoring network traffic or patching vulnerabilities. This can free up IT staff to focus on more complex tasks and reduce the risk of human error.
Automating security tasks already includes monitoring network traffic, patching vulnerabilities, or managing access control. Automated network monitoring tools identify and alert IT staff to suspicious activity on the network, such as unauthorised access attempts or malware infections.
Patch management services that deploy software updates to endpoints, servers, and other devices on a network, have also proven to be highly valuable tools in the evolution of IT security. Patching solutions help ensure that systems are up-to-date with the latest security patches, reducing the risk of vulnerabilities being exploited.
Cloud computing has helped to strengthen access permissions by identifying devices and locations. Automated identity and access management tools manage user access to systems and data, ensuring that only authorised personnel have access to sensitive information.
The AI evolution of IT security should improve the speed and efficiency of security operations. The technology allows organisations to respond to security threats in advance and in real-time by threat hunting, security monitoring and effective incident response — even if it is a false alarm.
Automating security tasks will also increase scalability, allowing IT teams to manage large and complex security operations more effectively. By automating tasks such as log analysis and incident response, organisations can manage large volumes of data with more accuracy by reducing the risk of manual errors and inconsistencies.
Improving Incident Response
AI can be used to analyse security incidents and provide recommendations for response. This can help organisations respond more quickly and effectively to security incidents, and reduce the impact of an attack.
By analysing data from across an organisation’s business network, AI can identify patterns and anomalies that might indicate a security breach. An automated response is triggered in real-time to mitigate the threat.
For example, AI can be used to detect the misuse of privileged accounts. By monitoring user activity and identifying anomalies, AI can identify unusual activity or unauthorised access to sensitive resources.
Automated incident response processes include isolating infected endpoints, blocking network traffic, or quarantining malicious files. It can also be used to analyse security incidents and provide recommendations for investigation.
The predictive incident response works by analysing historical security data to determine the potential for future security incidents. By identifying potential vulnerabilities or threat vectors, AI can help IT teams to proactively address potential security risks before they become a problem.
The evolution for AI will be to gather deeper layers of threat intelligence data from across the web. This allows analysts to take a deep dive and identify new and emerging security threats.
By staying up-to-date with the latest threat intelligence, can apply patterns and anomalies in security data to their own IT security defences. With access to relevant data, investigators can hone in on previous incidents and reduce the time and resources required to implement cybersecurity details or conduct an investigation.
Predictive and Behavioural Analysis
Detecting threats in real-time largely depends on identifying suspicious behaviour. The evolution of IT security will rely on AI to learn the normal patterns of behaviour that constitute your general business operations. Any anomalies that represent potential security threats will be easier to detect.
AI monitors the day-to-day activities of users, devices, and networks. This gives the software the capacity to identify any behaviour on the network that deviates from the usual patterns. This can help detect insider threats and other forms of malicious activity such as spyware.
The behaviour analytics software in use today, identifies suspicious patterns of activity such as unusual login activity or access to sensitive data outside of normal business hours.
Endpoint behaviour analysis is also used to monitor the location of network traffic or the execution of malicious files.
Behaviour analytics has already been improved by predictive analytics. AI is expected to take this to the next level as the software improves.
Whilst existing behaviour analytics software proactively identifies and addresses potential security threats, leveraging data and machine learning algorithms will improve the security posture of enterprises and reduce the risk of data breaches and other security incidents.
Predictive analytics involves analysing historical data to identify patterns and trends together with statistical algorithms, and machine learning techniques to identify potential security threats before they occur.
As with behavioural analysis, predictive software is able to forecast potential security events in the future and identify proactive measures that can be taken to prevent them.
However, the existing software has limitations. Predictive analytics relies on historical data to make predictions about future events. If there is a lack of data, or the data is of poor quality, the accuracy of predictions will be affected.
But as they say, time is a great healer. Hackers are constantly evolving their attack vectors, and new threats can emerge quickly. Check out our article outlining the new techniques cybercriminals have come up with in 2023.
Predictive analytics models may not be able to keep up with the changing threat landscape right now, but the more data they collect the more efficient they become at forecasting novel attacks and restricting the potential of hackers.
Of course, there will be a few teething problems. Predictive models will always generate false positives which can lead to wasted time and resources investigating false alarms. But a couple of wasted days is better than two weeks of lost profits whilst you get your system back up and running.
Whilst predictive analytics models may not have access to all the necessary information to make accurate predictions right now, AI should improve the future of IT security with enhanced data and sophisticated threat intelligence.
Enhancing Access Control
Cloud computing and multi-factor authentication has enhanced access control in recent years, but the solutions are far from ideal. Users find it a nuisance, and MFA codes sent via SMS can be intercepted (take note of the scaremongering headline).
MFA also has an annoying habit of making end-users jump through hoops if they change their location. This can be disruptive for employees that travel for work and try accessing files from a different city or country.
It also completely fails if the smartphone or laptop that receives the data is stolen. No amount of adaptive access control or continuous authentication will compensate for manual theft.
The only logical solution to improve user access controls is by using biometric data. Granted facial recognition and finger recognition may not be the most popular option with your employees, but they are already accessing their devices with them.
The same biometric data could be used to log into apps on the same device. There is the option to store apps in a virtual environment that can only be accessed with biometric data. This not only solves the problem of stolen devices but also facilitates device sharing in hybrid offices.
AI, of course, can enhance this function in real-time by verifying the identity of the user. We already have existing technology that can analyse typing speed, the motion of mouse movements, and other tactile sensors that can enrich biometric data. This can provide more secure and continuous authentication compared to traditional methods such as passwords, MFA or tokens.
The World Economic Forum has already announced that passwords will be obsolete by 2030. They also say imply that binning passwords is one step to raising cybersecurity awareness across a branders demographic — i.e anyone with a smartphone.
Their website states that the future of IT security will “be less about “defending fortresses” than moving toward acceptance of ongoing cyber-risk.” Cybersecurity will even be taught in primary schools.
Fraud Detection and Prevention
AI will also improve fraud detection and prevention in the future by enabling organisations to detect unstructured data, such as social media posts or chat logs, to detect potential fraud.
The software analyses natural language patterns (NLP) together with the user sentiment within the text. NLP is a subfield of AI that deals with the interaction between computers and human languages.
NLP allows AI systems to analyse, understand, and generate human language data. The AI system first collects unstructured data from various sources, such as social media, emails, customer reviews, and other text-based sources then preprocesses it to remove noise, such as stop words and punctuation, and to convert the data into a structured format that can be processed by the AI system.
Text analysis enables the software to identify techniques such as tokenisation, part-of-speech tagging, and named entity recognition, to analyse the text and extract relevant information.
The text is then compared with the historical data cultivated by the user by using machine learning algorithms, such as clustering or classification, to identify patterns. In most cases, any anomalies will be identified and ranked with a threat level.
Unstructured data will be presented in visual charts or graphs to make it easier for analysts to understand the insights and make informed decisions based on the data.
Growing Importance of IoT Security
With more devices connected to the internet, the potential attack surface for cybercriminals is expanding rapidly. As a result, securing the Internet of Things (IoT) is likely to become a key focus for cybersecurity professionals in the coming years.
While IoT devices harbour the promise of multiple benefits, such as increased convenience and efficiency, they also represent a significant security risk.
The rise in remote working complicates the future of IT security even more. Whilst home Wi-Fi networks can be monitored by IT support professionals with remote monitoring software, an IoT infrastructure doesn’t currently receive any security updates.
This poses a significant problem for IT security teams. If IoT devices are not customised with personal passwords and effective access controls, threat actors have more opportunities to find vulnerabilities to exploit.
Encouraging staff not to leave a default password on any of their home devices is a small step. But once a hacker hijacks one device on a network, they can get data from every other device within the IoT mesh.
As the number of household IoT devices continues to grow, the importance of IoT security in cybersecurity is increasingly apparent. Each IoT device represents a potential entry point for cybercriminals to gain access to a network.
That means that businesses with a distributed workforce could be compromised by a hacker that gets on to your network via an employee’s smart fridge or talking kettle.
The number of smart devices that can provide a gateway is troubling. Just thinking about the number of kitchen appliances we have at home makes my knees buckle. Inexpensive IoT devices are not exactly designed to keep hackers at bay.
IoT devices even pose a threat to a secured business network. These devices often collect and transmit sensitive data, such as personal information or confidential business data. If these devices are not properly secured, this data could be intercepted or stolen.
To address the challenges of IoT, the evolution of IT security needs to include implementing strong encryption, segmenting IoT devices from the main network, regularly updating software and firmware, and implementing effective user identification software.
In addition, it is vitally important for users to be educated about IoT security risks and how to protect themselves from these threats. This will need to be incorporated into your cybersecurity awareness training.
As an aside, to emphasise my earlier point about the effectiveness of cybersecurity defence technologies, software companies like Google and Microsoft invest billions of dollars a year to develop effective IT security solutions.
In 2021, Microsoft increased its cybersecurity budget from $1bn to a staggering $20 bn. That’s how worried Microsoft is about the impending challenge of securing IoT vulnerabilities.
Continued Growth of Cloud Security
As more organisations move their data and applications to the cloud, the importance of cloud security continues to improve. Cloud providers invest heavily in advanced security technologies and features to help their customers stay safe.
The continued growth of cloud security in the future of cybersecurity is inevitable. As more organisations move their applications and data to the cloud, the need for effective cloud security measures will only continue to grow.
But for the evolution of IT security to halt hackers, more advanced and sophisticated cloud security solutions are needed. At present, the best cloud security tools include monitoring and managing security in real-time, as well as automatically detecting suspicious behaviour and responding to security incidents.
Whilst increased automation will further improve cloud security organisations may have to find solutions that allow them to manage security at scale. This will include automated provisioning and de-provisioning of resources, automated patching, and advanced incident response.
We also expect to see more focus on compliance. As more organisations move to the cloud, they will be subject to greater levels of compliance by default.
For example, last year Microsoft released a security update that disables and defines which code is permitted on the system. Most significantly, Microsoft 365 security defences automatically disable Visual Basic for Applications (VBA) macros.
Enforcing compliance, however, will pose problems. Employees will be restricted from accessing pdf documents that contain VBA macros, even when there is a genuine case to do so.
Marketing tactics that use said downloads to solicit lead generation will also be stunted. Whilst it makes sense to set industry standards and regulations, the big players are not doing any favours for small businesses.
But the evolution of IT security may facilitate ways to work around this. Administrators can remove restrictions and cloud security teams will need to collaborate with cloud service providers to develop relevant threat intelligence and security best practices.
More Collaboration Between Public and Private Sectors
Cybersecurity threats are not limited to any one industry or sector, which means that effective cybersecurity solutions will require collaboration between public and private entities.
It has been muted that governments and private companies will work together to develop effective cybersecurity policies and strategies. This will involve sharing threat intelligence data to improve their understanding of potential security threats.
Coordinated cybersecurity policies will help to ensure there is a consistent approach to cybersecurity across different sectors. This can help to reduce vulnerabilities that could be exploited by attackers.
Governments might even help businesses to provide cybersecurity training and education and collaborate with small businesses to develop and deliver cybersecurity training and education programs. We are only saying might on this one though.
Considering that 83% of small businesses do not have the budget to implement full-scale cybersecurity defences, it would make sense for government policies to offer a helping hand — or at the very least relax restrictive regulations.
We do have effective cybersecurity defences for cash-strapped businesses. Read our article titled ‘Cybersecurity Solutions Don’t Have To Be Expensive’ for information and inspiration.
But one thing that is obvious is that a joint venture between governments and private companies to research and develop cybersecurity solutions will expedite the evolution of IT security for businesses of all sizes.
Building Resilience For Remote Workers
It’s pretty obvious that resilience on home networks will become a primary focus in the cybersecurity industry. With a growing number of the workforce working from home on BYOD devices, not to mention the aforementioned IoT minefield, home networks need to be as secure as business networks.
Existing solutions do a pretty good job. We are big advocates of virtual desktops. VPNs, MFA, antivirus software and endpoint protection also play a significant role in existing security solutions despite their limitations.
Many existing IT security solutions rely on identifying and responding to known threats, leaving systems vulnerable to unknown or emerging threats. Subsequently, they offer inadequate protection against new threats.
Whilst SMEs are unlikely to be targeted with new threats because multinational corporations represent a bigger payday, existing IT security tools don’t always provide robust solutions to effectively protect against sophisticated attacks.
Limited visibility into the network, applications, and endpoints can make it difficult to identify and respond to security incidents in a timely manner.
In addition, the complexity of IT environments and the variety of security solutions available can make it challenging to implement and manage a comprehensive security strategy.
Remote workers should be trained on IT security best practices to help them identify and avoid phishing scams, protect their passwords, and secure their devices. And as mentioned above, cybersecurity awareness training should include the threat posed by IoT devices.
Installing a second Wi-Fi network to separate personal internet activity from the work-related activity is a simple and cost-effective solution. But there could still be an issue with employees using the same device for work and play. Resolving that issue inevitably ramps up your business costs.
IT Support Specialists in London
Planning an effective IT strategy is easier when you have a team of IT specialists on hand. Our dedicated professionals have many years of experience and are already well acquainted with the evolution of IT security solutions. We continue to keep an eye out for the latest developments.
Knowledge of IT security is invaluable. Our highly experienced consultants are able to advise you about the best solutions for your budget. So you don’t have to push all your budget into IT security at the expense of other areas of your business that also needs investment. Our IT support services are designed to help you grow.