The Internet has brought many good benefits to the world. These include better productivity, fast communication capabilities, and access to a wealth of information. But despite all its advantages, it has attracted a lot of unwanted threats.
Internet users today need to understand the many threats they may encounter when using the internet. This includes the risks posed by social engineering, phishing, and malware. Furthermore, it may be difficult for people who are less tech-savvy to recognize these concerns.
Antivirus software can prevent some of these online attacks but cannot protect against every online threat. However, using machine learning and natural language processing, artificial intelligence holds great promise in reducing online threats.
Continue reading to learn about the shortcomings of conventional online threat detection, how artificial intelligence (AI) may stop online attacks, and the difficulties associated with AI threat detection. We’ll also provide some actual instances of how businesses are already utilizing AI to improve cybersecurity.
Drawbacks of Traditional Online Threat Detection
Traditional online threat detection methods, such as antivirus software, have several drawbacks. For example, these methods:
- Utilize established guidelines and recognized hazard indicators to render them useless in the face of emerging and changing dangers.
- Struggle to stay ahead of the ever-evolving dangers, making systems susceptible to increasingly complex assaults.
- Generate a large number of false positives, flooding security staff with false alarms.
- Antivirus software needs manual updates and maintenance, which is laborious and prone to mistakes.
How AI Ensures Online Security?
AI outperforms traditional security methods by leveraging machine learning algorithms to detect sophisticated threats.
AI models are trained on large datasets that include both safe online behavior and online threats. By learning to spot both normal online behavior and online threats, AI gets better at detecting threats and preventing them before they do any damage.
For example, AI can learn to spot unusual login times, which could be a sign of an online attack. Once AI knows this signal, it can immediately notify the user.
Large data sets can be analyzed by AI nearly instantly, allowing it to identify malware, phishing schemes, and other online risks much faster than human agents could. Additionally, it may learn from previous security attacks and spot dangers before they become critical.
Tools like AI chatbots also make it easy for users and businesses to use AI for online threat detection. Chatbots can help users while they use the internet, guide them through security processes, and detect phishing attempts. Similarly, businesses can also automate routine processes like standup meetings with tools like a standup bot for Slack, streamlining communication and improving productivity.
AI can help protect against some of the most common cyber attacks, including social engineering attacks, fraud, and malware.
The Power of Browser-Based AI Security
Web browsers are often thought of as the first line of defense against online threats, because they are the main interface through which users interact with the internet. Therefore, the strength of your security system depends on browser security. As AI is enhancing browser security, it’s crucial to implement these tools into web browser security.
AI-powered browser tools can analyze web traffic and user behavior in real time, finding online threats like malicious websites, phishing attempts, and malware. By utilizing AI solutions in browser security, users can detect and block threats before they can cause harm or compromise sensitive information.
AI-powered browser security solutions also offer customizable security policies, which let users adjust security measures to their specific needs and risk tolerance.
For example, with some AI tools, businesses can block certain website categories, block downloads from untrusted sources, or set up stricter authentication for sensitive transactions. Some of the browser security solutions that already use AI today include:
Google Safe Browsing: Google’s Safe Browsing technology employs algorithms to examine web pages for dangers like malware and phishing. This technology operates with major web browsers including Google Chrome, Mozilla Firefox, and Apple Safari, offering users immediate protection while browsing.
Microsoft Defender SmartScreen: Microsoft’s SmartScreen also uses AI and algorithms to guard users against malicious websites, phishing scams, and malware downloads. This feature is part of Microsoft Edge, Internet Explorer, and Windows systems. SmartScreen checks suspicious web content and matches it to a current list of threats for better security.
Although AI can boost browser security, there are difficulties for companies wanting to implement AI browser extensions. Since these extensions gather a lot of user data, they must prioritize data privacy. Companies need to make sure that any extension they use follows ethical and clear data handling practices.
How SMEs Can Leverage AI-Powered Security?
AI applications in online security are not limited to big companies with their own cybersecurity departments. Many smaller businesses are now adopting AI to safeguard themselves against online risks. And there is a good reason for this:
A recent report indicates that small businesses face three times the risk of experiencing a cyber attack compared to larger firms.
Here are some real-world examples of how SMEs are using AI to stay safe online:
Pets at Home Uses AI to Spot Fraud
Pets at Home, a UK pet shop, has an e-commerce store that has struggled with fraud. To solve this problem, they chose to try AI technology.
Using Microsoft Copilot, the company built an AI agent that could help them find potential cases of fraud and send a report to a human security team agent.
For human agents, going through transaction data and looking for potential cases of fraud can be incredibly time-consuming. However, the AI agent was able to sort through tons of transaction data in seconds and easily spot signs of fraud.
WhyBuy Uses AI to Write Secure Code
WhyBuy, a subscription appliance store in Australia, has been using AI to rewrite their coding and boost the security of their website. Plugin codes are easily accessible and hackers can use them to access websites and cause harm.
WhyBuy uses AI to rewrite plugin codes, making them more unique and secure. Without AI, this task would take days, but with tools like ChatGPT, WhyBuy can do it in minutes.
TRJ Telecom Turns to AI Technology to Secure Their Cloud
TRJ Telecom, a Canadian telecommunications company, was looking for a way to protect its cloud infrastructure from unknown and sophisticated online threats.
They turned to a popular AI cybersecurity provider, Darktrace. This security platform used machine learning and AI algorithms to gain an understanding of every user and device on TRJ Telecom’s cloud.
Through its detailed understanding of TRJ’s cloud infrastructure, the AI technology can easily spot and autonomously respond to online threats in their early stages, helping TRJ Telecom avoid the negative consequences of cyber attacks.
Challenges of Using AI for Online Threat Detection
Some of the most common challenges with using AI for threat detection include:
False positives
When normal online behavior is flagged as a scam or online attack, security teams can spend unnecessary time evaluating the threat.
To get fewer false positives, users must continuously train AI models using large and diverse datasets. By learning from many different scenarios, an AI model can start to differentiate between normal online behavior and legitimate threats.
Human security agents can also give feedback on the accuracy of AI’s predictions to improve accuracy and reduce false positives over time.
Capabilities of Attackers
Unfortunately, malicious parties also use AI to enhance the sophistication of their online attacks, making it hard for security teams to defend against online threats.
One of the ways security teams can combat emerging online attacks is by training AI models on adversarial examples. These are examples of an attacker who has provided an AI model to intentionally cause the AI model to make a mistake. By training AI models on these examples, they can become more resilient.
Collaborating with others who are facing similar cybersecurity threats can also help businesses stay up to date on the latest threats and solutions.
Data Privacy
Since AI works with large data sets, often including sensitive information, there is always the question of data privacy. Companies that use AI for security must ensure they comply with data regulations to protect the information of all online users.
To ensure data privacy, a business should set organizational standards and guidelines that outline data use practices. When AI models align with ethical AI principles and regulatory requirements, businesses can prevent the misuse of data.
There are some other techniques businesses can use to protect data. For example, data masking protects sensitive data by replacing real data with fictitious data that can be used in AI models. Pseudonymization replaces personally identifiable information (PII) with an artificial identifier, which means AI modes can analyze the data without revealing the original PII.
The Need for Human-AI Collaboration in Online Security
There are so many benefits of AI for online security. AI can look at vast datasets in a fraction of the time it would take human agents. At the same time, AI can use predictive analytics to spot threat signals and predict them before they cause significant harm to a computer system.
However, AI cannot completely replace human-guided cybersecurity. Seeing the full benefits of AI requires an approach that includes the participation of both humans and AI models.
Human security agents should continuously train and evaluate AI models to make them more precise and reduce false positives. AI can detect a threat, but human agents must be able to respond to it.
AI can provide significant insights, while cybersecurity professionals can provide context, understand nuances, and make decisions based on their extensive knowledge and experience.
In Conclusion
In order to identify security risks, traditional internet security systems, such as antivirus software, depend on recognized threat signatures. This makes internet users susceptible to new kinds of assaults in a world where technology is developing quickly. Thankfully, enhanced defense against internet attacks is now possible thanks to AI-powered security.
By analyzing vast datasets and learning to identify the patterns and anomalies that come with online attacks, AI can detect new online threats in real time. AI also uses predictive analytics to predict threats before they occur, saving time for security teams and preventing online attacks from incurring significant damage.
Users may defend themselves against many online threats, such as malware, fraud, and social engineering attempts, with the use of AI-powered security solutions. Businesses must, however, integrate human knowledge, judgment, and experience with the amazing processing capacity of AI to get the greatest security results.
