More and more enterprises are moving their systems and data to the Cloud and IoT to better manage their data, and to improve efficiency across various processes. However, this also expands the enterprise network perimeter beyond a physical IT infrastructure, increasing the surface area that needs to be protected against cyber security threats and potential breaches.
In addition, there will be 50 billion connected devices by 2020, a development that will further complicate IT security for most organizations as 99% of these new computing devices are vulnerable to cyber-attacks, allowing attackers to penetrate the larger network through any one of these connected devices.
At the same time cyber criminals have brought increasingly powerful tools to bear, allowing them to exploit existing vulnerabilities and to perpetrate sophisticated, multi-channel attacks under the cover of high network traffic— all while remaining virtually untraceable. The frequency and inevitability of such attacks is only growing. Organizations are now bombarded with hundreds—or even thousands—of alerts each day across their various end-points.
Enterprises and CISOs, therefore, need to understand that a conventional approach to data and IT security is no longer enough to tackle the challenges constantly emerging across the cyber security threat landscape. Traditional, outdated security frontiers can only defend against known threats and attacks types. They are not equipped to analyze the new threat data being created across various sources of potential vulnerabilities. And human-led security monitoring and threat detection methods are not strong enough to protect networks against the onslaught of AI-driven automated attacks.
Enterprises need to understand, Cloud and IoT have created an urgent need for cyber security solutions that can consistently and effectively monitor multiple end-points, detect threats, and appropriately respond to multi-dimensional attacks. And this is where advanced data analytics and Artificial Intelligence can play a critical role.
How AI driven cyber security Network works?
Enterprises and organizations continue to face new challenges and vulnerabilities from the modern cyber security threat landscape. Most critical, they must deal with a huge amount of data being created across the enterprise. AI-driven security platforms can take an organization’s IT security to a whole new level by analyzing this data to enhance both the speed and accuracy of predicting, monitoring, detecting, and responding to threats.
An AI-driven security platform collects and processes a huge amount of data via advanced data analytics, in order to first identify patterns within attacks and threats, and then to produce insights on how to counter them. Every attack—even those from unknown sources—leaves a discernible network trail, and analyzing this trail helps security teams identify where exactly the attack took place in the network.
You see, most modern cyber-attacks are perpetrated through multiple vulnerable points. Each attack navigates through its own distinct progression of servers, networks, systems, and files to reach the intended target. It is critical, therefore, to analyze every piece of data from your logs and forensics, as various data points, when analyzed collectively, provide a holistic picture of how strong the existing security systems are, and how they can be improved.
Deep analytics of multiple points can map the exact steps taken by an attacker, uncover what vulnerabilities they have exploited, and identify the actual target of the breach. This analysis helps the organization begin to monitor and respond to new, unknown threats, and prevent major damage in the future.
How to bring AI driven cyber security to your organization
When transforming your enterprise security by leveraging AI, start by adopting an effective Managed Detection and Response (MDR) service. An effective MDR closely – and constantly – monitors entire systems, searching for advanced threats, validating any suspected system exploitation, and investigating confirmed incidents. This allows you to proactively identify security threats and data breaches in real-time.
In addition, an effective MDR service will also quickly contain breaches to limit the extent of damage you suffer from a successful attack, and then evolve your defences to prevent the same attack from succeeding again in the future.
And most important: don’t believe your traditional security measures are enough. When it comes to cyber security, complacency is extremely expensive for enterprises. They need to remain on their toes and to evolve in-step with their fast-changing threat landscape. Organization’s hit by cyber-attacks or frequent data breaches not lose revenue, but they also suffer irreparable damage to their reputation and loss of confidence from their customers and business partners.
Since most enterprises run on systems that are not designed to handle evolving threats and attacks, they must proactively reconsider their security strategy. They must leverage emerging technologies like deep analytics—along with AI-driven methods like Managed Detection and Response—to secure their data and their business interests. Those enterprises that fail to take the right steps early on will likely hamper their growth prospects in the future.
Nirmal Kumar, Associate VP at Paladion Networks
