Organizations have never been so dependent on the digital ecosystem and the Internet. They implement new technologies hastily without realizing that these new technologies could pose new cyber threats. Globally, businesses of all sizes experience reputationnal damage due to hacker attacks and suffer appalling losses that increase every year.
In 2018 alone, cybercrime revenues hit $1.5 trillion and are expected to exceed $2 trillion by the end of 2019. According to a recent study by Accenture, cybercrime could cost businesses over $5 trillion within the next 5 years. Today, only 30% of companies invest heavily in their IT security, adopting state-of-the-art technologies like offline password storage or complex data protection systems.
For that matter, are there any emerging solutions that might change this doom-and-gloom scenario?
Organizations have never been so dependent on the digital ecosystem and the Internet
Machine learning (ML) is changing the cybersecurity landscape now. It is a type of Artificial intelligence (AI) capable of learning from experience. Actually. ML is as old as computers, but it is gaining momentum due to the rapid growth of data in the digital sphere. As of today, the volume of such data is about 33 ZB (zettabytes) (one zettabyte corresponds to one trillion gigabytes). It is estimated to reach 175 ZB by 2025. Intelligent systems that utilize machine learning and deep learning can help businesses in two ways: 1) they simplify the analysis of big data, and 2) they use this data to grow their intelligence and solve complex tasks.
In a nutshell, ML-powered tools can analyze huge sets of data, detect anomalies, and predict threats. Let’s find out how these ML capabilities help businesses:
Most companies—from giants such as Google, Apple, Amazon, Microsoft, Cisco, PayPal, etc., to various startups—are moving away from rule-based technologies and introducing ML systems.
Millions of people log into Google’s Gmail every day. Using machine learning, Google easily detects unauthorized logins and tracks different aspects of user behavior during and even after a login session. It also allows for early phishing, malware, and spam detection. Over time, the accuracy of algorithms improves, and the cost of security maintenance decreases.
No doubt, ML tools, and systems are reshaping the future of cybersecurity. Researchers are constantly experimenting with ML to polish the technology and make it more efficient in detecting and preventing cyber threats. Currently, however, ML alone is not sufficient to completely eliminate cyber attacks. Therefore, machine learning will likely be combined with other technologies to enhance security. Will these duos be effective?
IoT is a network of different interconnected devices (things) that are able to share data and process it without human interaction. It’s one of the fastest developing and popular technologies and is expected to control over 30 billion connected devices by 2020. IoT is changing the online business ecosystem a lot, but security remains the top concern.
Since IoT connects billions of devices, it’s impossible to manually identify and stop suspicious activity. This is where ML comes in handy. Processing large data sets, machine learning tools effectively detect vulnerabilities and threats at early stages, before critical situations arise. ML-powered systems automate security practices while evolving and becoming even more efficient in the long run.
Cutting-edge technologies like ML and blockchain are robust on their own, but they can produce incredible results when combined together.
Blockchain is a distributed ledger (or database) protected against unauthorized tampering. Machine learning can maximize a blockchain’s potential, improve the deployment of blockchain-based apps, enhance the security of blockchain nodes, and prevent system breaches. While the experiments on combining these two technologies are carried out, it’s already obvious that they complement each other, bringing security to new levels. ML will benefit from access to big data, which it will manage and learn from, while the blockchain will take advantage of faster transaction verification and validation.
Since there is no single system that ensures ultimate security at all layers, cybersecurity somewhat remains an art, where the greatest minds compete using the most innovative technology available today.