Top 6 Ways AI is Changing Data Security

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By Lisa Duprey   |   January 27, 2023   |   0 Comments

AI is changing data security. It protects your data using advanced encryption algorithms.



In this post, we outline 6 ways that AI is changing data security and why you should use AI too. Artificial intelligence has become more defined and well-established as technology advances. These advances come with cutting-edge ways to secure your organization’s data and information. AI is being used in all 6 steps of the data security lifecycle from data creation to its destruction. Every industry can use AI to better support their cyber security practices and procedures. The following are some of the top ways artificial intelligence is making its influence felt in the field.


Why is AI Important for Data Security?

The first step is understanding what “AI” is. AI refers to computer systems capable of performing tasks that normally require human intelligence — like making decisions or learning from experience — without explicit programming instructions.

AIs can make quick decisions. They learn from their mistakes and keep improving. AIs do not get tired or slow down, they work around the clock if necessary. AIs are cheaper than managing large staffs of security experts. Even their training is cheaper because they use less electricity and other utilities to run their systems.

AI technology is becoming more affordable every day, making it accessible to small business owners who were previously priced out of the market for cutting-edge information technology products and services. AI can help businesses protect themselves against cybercriminals by quickly identifying threats and neutralizing them before they can do damage to an organization’s computer network or steal its valuable data files, such as customer lists and financial records, or its intellectual property, such as software source code, product designs, research data and formulas for proprietary products like drugs or video games that have been tested but have not yet been released to the public.

Machine learning, a form of AI technology, can utilize pattern recognition to identify unusual activity on a network through a clustering algorithm. Another form of AI is used in encryption or tokenization using an algorithm to randomize the encryption pattern and log the decryption key for user authentication on a scheduled basis. Let’s dig a little deeper to see how you can keep your data safe and secure from more sophisticated cyber security threats.


Neural Networks Revolutionize Data Encryption

Neural networks are a type of machine learning that can be used to create a data encryption system. They are based on a biological model where neurons are connected to each other in a network, which then processes information. These networks can be used to create encryption systems that change the level of encryption at any given moment. This means that when someone tries to hack into your systems, they will have to constantly change their method of attack because the encryption is always changing. This will make it very difficult for hackers to crack the code and steal your information. The neural network uses a neural encryption key (NEK), which is a string of bits that allows it to encrypt data in an adaptive manner. AI and Neural networks is changing data security through encryption.


Automate Data Backups and Ransomware Recovery

Machine learning is changing the way we backup and recover from ransomware attacks.

Cybercriminals continue to develop new ways to infect their victims. Effective security solutions are required to can protect against the latest threats. Protecting your business from ransomware attacks is one of the most important tasks for any IT professional or security manager.

With automated data backups, you can rest assured that your data will be safe even if your computer is infected with ransomware. Automated backups also make it easier to recover from an attack by allowing you to restore your system without having to manually copy files from a backup. By using machine learning models, you can take this one step further by applying these models to detect potential risks and prevent future attacks before they happen.


Identify Unauthorized Access and Stop Cyber Attacks

AI provides insights into existing security systems. It analyzes data from multiple sources including network traffic logs, user behavior logs, endpoint logs etc., using machine learning algorithms. These algorithms detect anomalies in the log records to help identify new threats before they cause damage to the system.

AI identifies malware trying to bypass existing security systems or fake users trying to login into the network through unauthorized routes. In addition, it helps identify insider threats like disgruntled employees who may try to steal confidential data or sabotage systems if they feel they have been mistreated by their employers leading them to become cyber criminals.


Automate Repetitive Data Security Tasks

Data security is a never-ending task. It is impossible to keep track of it all with the amount of data being generated in the world today. The only way to protect your company’s data is by continuously monitor and analyze it. However, it is very time-consuming to do this manually.

Fortunately, plenty of tools are available for automating repetitive tasks in data security. Tasks like vulnerability scanning and CIS Compliance Scanning. SecureMyDesktop is a good example of how cyber security professionals are automating CIS Level 1 Benchmark Compliance.

Machine learning (ML) has been around for quite some time now. It is now a tool for automating repetitive data security tasks. ML algorithms analyze large amounts of data and detect anomalies or patterns that may be indicative of malicious activity. Machine learning isn’t new. However, there are many new innovative ways companies can implement it into their data security strategies.

For instance, some companies use ML to identify potential threats based on certain criteria such as IP addresses or URLs. Other companies predict what attack might be coming next so they can take preemptive measures against them.


Identify and Stop Zero-Day Attacks

With the rise of machine learning, there is hope that it can help close vulnerabilities, particularly zero-day threats and others target unsecured IoT devices. There is proactive work in this area: A team at Arizona State University used machine learning to monitor traffic on the dark web to identify data relating to zero-day exploits, according to Forbes. Armed with this type of insight, organizations close vulnerabilities and stop patch exploits before they result in a data breach.

Efforts are now underway to use AI to identify cyberattacks in real time. For example, IBM has created a security platform called “Sentinel” detects anomalies within network traffic and predict attacks based on user behavior. Organizations use Sentinel with limited security budgets or expertise — it works as an appliance or cloud service.


Enhance Cyber Security Professionals Capabilities

The reality is that organizations will always need cyber security professionals. However, organizations need people who are able to get the most out of their existing tools and resources.

This is where AI and ML come in. Cyber security professionals access powerful AI and ML enhanced software and tools. AI is changing Data Security security forever. AI and Machine Learning has become the new norm when it comes to security.

No matter how sophisticated these tools become, they will never be able to replace human intelligence entirely. Experts recommend organizations employ both humans and machines when it comes to protecting against cyberattacks — one person simply cannot be everywhere at once.

In fact, there is no reason why AI should not be used for malicious intent either! Hackers use machine learning algorithms to scan massive amounts of data for vulnerabilities in systems or networks. They then use that information to exploit them for malicious purposes such as ransomware attacks or DDoS attacks. This is where human intelligence comes into play: although there may be many automated scans conducted by hackers, it requires a human mind to decide on which threats are worth following up on based on their relevance.


Putting It All Together

Modern cyber security systems use AI. AI and ML is changing data security as we speak. It has become an essential part of your antivirus, firewall, and encryption software. As security threats ecosystem gets more complicated, you should integrate into your overall data protection strategy.

If you want to start using AI and Machine Learning to secure your organization’s data, contact us here for a free consultation.

Learn more about how we keep your businesses data secure here.


Category: Cyber Security