How AI in cyber defense is revolutionizing communication platforms?

The risk of cyber attacks is continually soaring. The number of data breaches between 2021 and 2023 grew by 72%, surpassing previous records.

Communication platforms used by businesses for workplace communication are particularly at risk.

Also, breaches of shared confidential data lead to substantial financial losses and damage to a company's reputation.

‍For instance, the global indicator 'Estimated Cost of Cybercrime' was forecast to increase by $ 6.4 trillion between 2024 and 2029.

In this scenario, a zero-trust cybersecurity approach can be a perfect solution for businesses. This strategic approach to data security is where nothing is trusted—from users to devices—until verified.

The success of the strategy lies in continual verification, which is made possible through the use of Artificial Intelligence (AI). For instance, the use of AI in cyber defense is helping to strengthen threat detection and prevention, user authentication protocols, and privacy preservation in communication platforms.

But can it overhaul the enterprise security mechanisms?

The unique cybersecurity challenges of communication platforms

Here’s a snapshot of key challenges:

Large volumes of data

Communication platforms handle massive volumes of data, giving rise to large-scale privacy concerns. The type of data includes communication between users and shared documents in a wide range of formats.

Scale of engagement

Communication happens in real-time across onsite, hybrid, and remote work contexts. Thus, the platform is being accessed outside the office premises, making data very vulnerable.

Cross-platform usage

Users log in to the communication platform via diverse devices. The same user may also access the platform from their laptop, smartphone, and tablet, which increases cross-platform security issues.

The large volume of users

As businesses scale, the number of users continues to rise. Authenticating such a large volume of users and authorizing access multiple times a day, comes with its own complexities.

Compliance challenges

Regulatory guidelines (such as GDPR/ CCPA) are continually evolving to help strengthen the privacy of data and prevention of cyber attacks. Hence, platforms find it challenging to get up to speed with compliance.

AI-powered threat detection and prevention

Let's understand how AI in cyber defense can help address the common challenges by providing multilevel security:

Machine Learning for anomaly detection

The adoption of Machine Learning (ML), a subset of AI, helps strengthen the security of communication platforms by flagging anomalies in two ways. For example, ML:

Has the capability to recognize, identify, and flag unusual user behavior patterns, swiftly.
Can instantly detect and flag suspicious message content, or file transfers in the system.

Natural Language Processing (NLP) for content analysis

The adoption of NLP, a subset of ML, helps communication platforms analyze content minutely. It has capabilities to closely interpret and comprehend human language and language patterns, in detail.

Superior communication platforms leverage NLP to:

Analyze communication and flag potential spam. For instance, it has phishing detection in messages.
Strengthen communication platforms to identify potential social engineering attempts early on. Examples of social engineering methods include tailgating, pretexting, whaling, and watering hole attacks.

Deep learning for zero-day threat identification

Communication spans a wide range of elements. Deep learning, another subset of ML, can recognize patterns across images, text, emojis, audio, and other formats.

This technology has emerged as the go-to option for tech companies in zero-day threat identification. In the case of communication platforms, developers can identify vulnerabilities in the software before they launch new features and functionalities.

AI-driven encryption and secure communication protocols

AI can strengthen encryption and data protection capabilities by adjusting the encryption parameters as to the complexity of threats and risks.

An advanced AI system has the potential to make encryption a more robust process in the face of potential attacks, through the dynamic adjustment of protocols, or generating cryptographic keys in a fast-shifting threat landscape.

Adaptive security measures using AI‍

Here’s a snapshot of how AI can quickly adapt security measures based on the type and complexity of the cyber threat:

Strengthens risk assessment

It can activate dynamic risk assessment and security policy adjustment.

Automates key processes

AI can completely automate the patch management process, and activate necessary system updates.

Reduces response time

AI-assisted incident response and mitigation helps to cut short the timeframe to respond and mitigate a cyber attack.

Powers continuous improvements

The technology can also ensure continuous learning and improvement of security models on an ongoing basis.

AI in user authentication and access control

Businesses need to ensure that only authorized users can log in to the platform, participate in sensitive conversations, and be privy to confidential data.

The use of AI improves user authentication and access control in the following ways:

Recognizes minute inconsistencies

Biometric authentication is enhanced by AI, which can recognize any inconsistencies during the authentication process.

Continuous monitoring

Authentication is no longer a one-time activity but a continuous process; AI has capabilities to track behavioral biometrics and flag unusual user interactions.

Multi-factor authentication

AI-powered multi-factor authentication systems entail that users log in using multiple authentication factors rather than just username and password.

Superior session management

Users often forget to log out of their sessions, opening the system up to potential misuse and cyber attacks. The use of AI can power intelligent session management and automatic logouts.

Privacy-preserving AI techniques for cyber defense

As massive volumes of proprietary, and sensitive data are shared by business teams, AI in cyber defense, has capabilities to deliver on the enhanced privacy preservation expectations.

Here are some key advantages of AI-enhanced cybersecurity for communication platforms:

Decentralization approach

The adoption of a federated learning approach for distributed threat intelligence helps decentralize data governance and boost security and privacy. This approach makes communication platforms more resilient to attacks.

Maintains data confidentiality

The adoption of homomorphic encryption for secure AI model training helps to execute the analysis of data without revealing the contents of data. This approach helps in boosting data privacy standards.

Maintains user confidentiality

The use of AI helps boost differential privacy in user data analysis i.e. the power to execute data analysis without revealing the identity of users.

Transparency in security decisions

Harnessing explainable AI enables better comprehension of ML algorithm results, paving the way for greater transparency in security decisions.

Challenges and considerations in implementing AI in cyber defense

The adoption of AI in cyber defense has the potential to revolutionize security, privacy, and management of data. However, the technology needs to be harnessed effectively. Here are some potential challenges and considerations:

Balancing priorities

Security enhancement needs to be balanced with user experience and performance. One priority cannot be compromised for the benefit of the other for the software to be effective.

Integrity in AI usage

Ethical considerations and potential AI biases can put some users in a team chat at a disadvantage. Care must be taken to leverage AI to build inclusive, diverse cultures and practices.

Seamless integration

Businesses that leverage communication platforms with AI-enhanced security, must be able to seamlessly integrate this interface with existing security infrastructure.

Software agility

Cyber threats, attacks, and other issues continue to evolve every day. AI models need to be up-to-date with new developments and be in a position to fight evolving threats.

Key takeaways

Today, the most secure messaging apps are leveraging AI in cyber defense to boost the security of data. This approach helps exponentially improve team collaboration and team performance.

The use of AI in communication platforms comes with unique advantages. This technology can be transformational in boosting data security, in the face of continuously evolving cyber threats. Businesses are advised to partner with a communication platform that harnesses AI in cyber defense without compromising the user experience and bringing in.

Consider partnering with Rocket.Chat, a secure and compliant communications platform, designed to enhance team performance.

The tool can ramp up your cyber defense by:

Harnessing AI to boost data security, privacy, interpolarity, flexibility, and sovereignty
Guaranteeing full ownership of data to businesses leveraging the platform
Supporting all aspects of workplace communication such as search; threads, channel discussions; mobile; live chat; recording; scheduling, and pop-up chat
Serving businesses in highly regulated sectors such as healthcare, government, and defense.
Offering deployment in both on-premise and cloud settings.