How it works and why it’s critical for Cybersecurity

With ground-breaking technology becoming more publicly available each day, securing sensitive data is becoming an increasing threat in the Cyber Security landscape. Encryption is a key part of cyber security, and it’s important to understand what it is and how it works. To keep data and documents confidential and accessible only by the intended users, encryption plays a critical role in achieving this. Encryption is embedded into so many products you may not realise you are already using it regularly! So, what is Encryption and how does it work? 

What is Encryption?

Encryption is the process of encoding information. In simpler terms, it is the process of converting plain text into a code or cipher using keys. By encrypting data, anyone who manages to intercept the information cannot read the contents without the cryptographic key. Sort of like a secret code only you and the other person know and understand. Encryption is similar to a cryptogram word puzzle, in which you are given a key to decipher encoded text: 

Ciphertext: “QFJNIPNRXI MY OWYV”  

Key: 

Q = c, F = l, J = o, N = u, I = d, P = g, R = a, X = r, M = i Y = s, O = b, W = e, V = t 

How does it work? 

There are a few different types of encryptions and each one behaves slightly differently, but ultimately data is encrypted and decrypted using specified cryptographic keys.  

The most common form of encryption is ‘Symmetric Encryption’. As the name suggests, symmetric encryption is where one key is used to both encrypt and decrypt the information. This method of encryption is very fast and efficient, however, the major flaw with symmetric encryption is that the cryptographic key needs to be securely sent to the recipient for them to decode the message. The symmetric key must not be exposed publicly otherwise all confidentiality is breached.  

‘Asymmetric Encryption’ (also known as Public-key encryption) behaves like symmetric encryption, except a pair of keys are used instead of one. A public key is used to encrypt the data and a private key is used to decrypt it. This example below will help explain how it works in a real-world scenario: 

Alice would like to send a message to Bob. This message contains sensitive information, such as home addresses and payment details. Alice needs to ensure the message is delivered confidentially and cannot be intercepted. 

Bob generates a public key – private key pair. The public key is used to encrypt the data and can be shared with anyone without causing a security risk. The private key can decrypt any message that has been encrypted with the public key. The private key should not be shared with anyone. 

Alice encrypts her private message with Bob’s public key and emails the encoded message to Bob. 

Bob receives the email and uses the private key from the pair to decrypt the message and receive Alice’s original message securely. 

Asymmetric encryption provides a more secure method of encryption but comes with the drawback of being less efficient and slower. 

What should my next steps be? 

Now you have a better grasp of what encryption is, you are probably curious about how this impacts you and what changes you can make going forward. 

Fortunately, thanks to compliance and regulations, most software must include a base level of encryption. However, it is always best to check that devices and applications are using a high level of encryption by default, especially if they are regularly used. This can usually be found within the ‘About’ or ‘Settings’ section. 

One step you can take to include more encryption within your network is making use of Virtual Private Networks (VPNs). A VPN is typically a paid service that will encrypt all internet traffic from a device, providing a higher level of security when using online services. This can assure you that an attacker is not intercepting any sensitive information or communications across the internet. 

You may also wish to migrate to more encryption-focused messaging platforms like WhatsApp or ProtonMail. These messaging/email services utilise end-to-end encryption to secure the content of any messages or emails from unwanted readers. You can take this another layer deeper by using third-party encryption tools such as VeraCrypt to encrypt the individual files you wish to send to another person. 

In summary, it is important to understand how you can safely send information to another person and the tools you can use to achieve this in your personal or work life. 

How does Sentinel use encryption?

At the core of CloudGuard’s protection is Sentinel. Sentinel is Microsoft’s SIEM solution, which in layman’s terms is a security tool that ingests data, monitors, and alerts on any suspicious information it discovers. 

 To provide robust security and protect customer data, Sentinel uses encryption in various methods to achieve this:

• Encryption at Rest: Sentinel uses Azure Storage Service Encryption (SSE) for any data stored within Azure. SSE uses AES-256 for its encryption method.

• Encryption in transit: For data being transferred between Azure and/or Sentinel, Transport Layer Security (TLS) encryption is implemented for end-to-end encryption meaning the data is encrypted at the source, transmitted, and only decrypted once delivered to the recipient.

• Azure Key Vault: Within Azure, a service named Key Vault allows users to store and manage encryption keys. Key Vault is a secure key management system that uses Hardware Security Modules (HSMs) to store keys.  

How does CloudGuard utilise encryption? 

Within the CloudGuard service, encryption is baked into every aspect. We use encryption for our messaging platforms, emails, web applications, sharing files, and much more! When handling passwords or sensitive information, CloudGuard will always configure the highest level of encryption available for the service (Typically AES-256 and TLS 1.2 and 1.3 where available).  

The most common areas CloudGuard makes use of encryption is within our databases and data transmission. Databases can contain an assortment of sensitive and critical information which could be fatal in the hands of an attacker. Using the strongest Advanced Encryption Standard (AES-256), we are able to protect data stored on disks within the database servers. This gives us the confidence that our data is secured and resilient to any attacks on our databases. 

Data transmission requires a different type of encryption to ensure the communications are secured whilst the data is being transferred over the internet. Data transmission can consist of sharing data or messages typically over the internet or private network. To secure data in transit, a connection is established and authenticated between the sender and recipient. The data is then encrypted and transferred between the two users. CloudGuard enables the securest level of TLS to achieve this goal and transfers data through VPN tunnels (private networks) where possible to assure the data’s confidentiality.  

Keeping your information safe is CloudGuard’s highest priority and utilising encryption allows us to retain data’s confidentiality and ensure it is only visible to those it is intended for. 

Machine Learning As Our First Line Of Digital Defense 

Machine learning is a type of artificial intelligence that allows computers to evaluate data and learn its meaning. The goal of combining machine learning and threat intelligence is to encourage users to find vulnerabilities faster than humans can and stop them before they cause more damage. Furthermore, conventional detection technologies invariably generate too many false-positive results due to a large number of security threats.

Machine learning can reduce the number of false positives by analyzing threat intelligence and condensing it into a smaller subset of features to watch for.

According to a global advanced threat intelligence consultant, artificial intelligence is becoming more important in deterring, detecting, and resolving cyber-threats as the evolution of attacks adapts and adversaries function in well-organized, highly skilled organizations.

The Security Threat Of Today Has Become An Industry Of Its Own

Many of today’s adversaries operate in large networks, relying on a “crime-as-a-service” business model that involves hundreds of people disseminating threats for a commission. Threat actors are using automation as a weapon to extend their reach. As a result, having A.I.-enabled structures in place to sift through massive amounts of security threats and react promptly becomes even more critical.

Machine learning-based AI threat intelligence products work by taking inputs, evaluating them, and generating results. Machine learning’s inputs for detection systems include threat intelligence, and its outputs are either alerts implying attacks or computerized actions that stop attacks. If the threat intelligence contains errors, it will provide “bad” details to the attack tracking tools, resulting in “bad” outputs from the tools’ machine learning techniques.

The Magic Of AI Threat Intelligence

There’s too much data and not enough time. Because of this, as well as the high cost of labor, machines have been at the frontline of cyber defense for nearly 50 years. It’s also why cybersecurity providers and consumers continuously leverage major innovations in software design, machine learning, and artificial intelligence (AI).

In contrast to the human brain, none of the other AI cyber technologies are completely autonomous or otherwise dubbed “intelligent.” Instead, they use complex algorithms and massive amounts of computing power to ‘intelligently’ process data. But that hasn’t stopped AI from becoming more prevalent in cybersecurity.

Cybersecurity: AI vs. Human Beings

AI and machine learning play a key role on both sides of the cybersecurity battle, allowing attackers and defenders to operate at unprecedented speeds and scales.

On the assault side, the rise of so-called “adversarial AI” has included relatively simple machine learning algorithms that have been used to disastrous impact in spear-phishing attacks. The human cyber attacker can use effective social engineering tactics with a high probability of winning and almost no effort by extracting open-source intelligence and studying communications obtained from a corrupted account in a computerized and ‘intelligent’ manner.

DeepFake attacks, which use AI to emulate individuals’ voices and visual appeal in audio and video files, are another example. IBM’s DeepLocker pilot project is one of many demonstrating how artificial intelligence will speed up the development of advanced malicious software.

Threat Intelligence with AI

Artificial intelligence and machine learning are essential for effective threat intelligence in various aspects: coping with massive amounts of data and guaranteeing that the data is current.

Volumes are massive, and they’re only getting bigger. Without a sophisticated software suite, processing data to be used in real-time, making decisions is impossible. Sensors that use algorithms, sinkholes, and phishing sites can greatly increase threat data exploration and classification and peruse through it all at a different speed to identify unusual behavior.

Adding To Human Intelligence And Experience

We know that cyber skills are in high demand worldwide, with up to 3.5 million job openings unfilled right now. This adds to the difficulty of implementing an AI-driven cyber strategy that requires little human intervention.

Human analysts are more than just supervisors of computerization in good security threats. It sees the value-added knowledge of knowledgeable professionals who can break the mold, think creatively, and add context to the ‘almost-finished product delivered merely through AI and machine learning processes.

Another of AI’s achievements in cyber defense is mimicking applicable scenarios, which requires human/machine collaboration. Because of their capacity to assist, prevent, and detect new attacks, these technologies are becoming increasingly important in the ethical hacking toolkit.

Conclusion

While AI is becoming more prevalent in both cyber-attack and defense, neither side achieves their goals when they entirely depend on it. In the same manner that threat actors benefit the most when they combine human intelligence with machines’ incredibly advanced logic and industry, security teams have found that this is the best formula.

Nothing, at least not yet, compares to the unique ability of people to think. Only people can add the final 10% – the missing link in the chain that ensures the whole makes perfect sense – and make the kinds of critical decisions that corporate leaders would rather not delegate to a computer. They form the best possible team when they work as a team.