AI/ML Devices Security Testing

Digital ecosystems shape the backbone of our everyday lives. Nowadays, Cyber-attacks are majorly focused on the digital ecosystems. As advances in artificial Intelligence (AI) and machine learning (ML) circulate at breakneck speed, use of AI and ML is expected to develop at heartening pace in cyber defences and will add tremendous intelligence and power to combat against cyber-attacks.
Cyber security attacks keep growing at an alarming speed and keep getting more sophisticated with IoT attacks, data breaches, spam and phishing, crypto jacking, mobile malware and ransom ware. Data losses and disruption due to these attacks continue to be significant for companies and organizations, each in economic terms and in harm to their reputations.
So, the fight continues towards these attacks with all weapons possible. Two significant ones are artificial intelligence (AI) and machine learning (ML). AI and ML can be extraordinarily effective in detecting cyber security threats and anomalies promptly to thwart attacks. One big benefit of machine learning is its capability to analyse large data units and become aware of anomalies and suspicious patterns immediately. Automatic updates to existing software primarily based on sophisticated analysis by means of ML and AI can prevent cyber security attacks at scale.

When it comes to fighting an ever-growing number of cyber-attacks and vulnerabilities it can only be termed as an ‘ever-evolving’ risk landscape, organizations need to recognize the significance of common protection tests, and the role that they play in fostering cyber security within organizations.

The objective of AI/ML Devices Security Testing is to

• Make sure that the organisation stay up to date with the frequently overwhelming volume of threats, which includes methods, vulnerabilities, targets and bad actors.
• Help organisations in turning out to be extra proactive about future cyber security threats.
• Keep leaders, stakeholders and users informed about the latest threats and repercussions they could have on the business.

The AI/ML Devices Security Testing solution acquire raw data about emerging or present threat actors and threats from a number of sources. This data is then analysed and filtered to produce threat intelligence feeds and management reports that incorporate information which can be utilized by automated security control solutions. The primary purpose of this sort of security is to keep corporations informed of the risks of advanced persistent threats, 0-day threats and exploits, and a way to protect against them.

The solution uses unsupervised machine learning to examine network data at scale and make billions of probability-based calculations based on the evidence that it sees. These platforms then, rather than relying on knowledge of past threats, independently classify data and detect deviations in patterns and flag them for attention.