As the hyper-connected businesses continue to evolve and expand, they have been witnessing a strong challenge to the cybersecurity. Not only are the cyber threats increasing in numbers, but also aggravating. Cyber-security skills shortage has, in turn, made it need of the hour for network security teams to leverage advanced technologies like machine learning and other AI-based capabilities to detect, secure, and eliminate the cyber-security attacks. With an expansion of the threat landscape comes the ever-increasing demand to integrate AI-powered solutions to the security ecosystem. This not only helps you establish high-end security standards but also provides a way to maintain them.
Having said that, the cyber-criminals are no way lagging. They walk head-to-head with the businesses and are also offering tough offense by adopting modern approaches like agile software development, automation, and machine learning to crack security loopholes and make the best of it.
The variety of Internet of Things (IoT) and Operational Technology (OT) devices, in turn, offers them gateways to initiate complex attacks into the corporate networks rapidly.
The war between the cyber-security experts and cyber-criminals is taking the AI turn as both of them explore newer ways to beat each other. But can you defeat the enemy without actually decoding the methodology they follow, or without even understanding their weapons? Of course not, probably this is the reason that IT teams need to really gear up and gain an in-depth understanding of the AI-driven threat environment to trace the cyber-criminal strategies. This also involves harnessing AI to the fullest and ensuring that security standards rise to the challenges as network realm continues to expand.
Changing Paradigms of Threat Landscape
Cybercriminals have started harnessing the potential of automated and scripting language to level up the game of cyber attacks. Their success is pretty much visible as the number of attacks has drastically increased by as much as 240 percent in the year 2018 itself. AI has, in turn, enabled the cybercriminals to upgrade their skills and gain better access to map networks automatically, analyze vulnerable gateways, choose attack vectors, and carry out penetration testing for deploying advanced attacks.
This only implies that the AI-based digital transformation is not just a trait of the security professionals, but also the cybercriminals. And why not? Adoption of AI for enhancing the security makes it inevitable for the cybercriminals to adopt it in order to keep up with the pace. Not only this, adoption of latest practices like agile methodology enables them to beat manual threat analysis and advanced security solutions. Integrating AI will just make them more powerful.
The dramatic advancement of the cybercriminals’ skills makes it mandatory for the network engineers to upgrade their security ecosystem. While most of the organizations still depend on the conventional methods and hinge upon the full range of independent products, they terribly fail to secure networks from the attacks. That is, the enterprises still applying manual threat analysis and security-as-you-go strategies only end up proving themselves incapable of standing firm on the ground of cybersecurity.
How IoT and OT Devices Fail at the Security Level?
For most of the organizations, digital transformation synonymizes with the incorporation of IoT and OT devices and be a part of the hyper-connected world. As the volume of these connected devices increases, it is inevitable not to expect the drastic explosion of IoT data. This data is stored freely between the widespread physical and cloud-based networks. Availability of this enormous amount of data poses a high degree of challenges for the cybersecurity experts. And with the IoT devices adding up at a rapid pace, it becomes vital for the network security professionals to deeply understand the metrics that affect cybersecurity in the IoT ecosystem. Here are some of them:
As the demand for IoT devices sparked, multiple vendors ventured into device manufacturing. Consequently, businesses took up to buying products from various sources. Higher the volume of sources, more difficult it becomes for the network security professionals to implement standards, analyze the security for each device, and guard them.
Poor Network Visibility
This is one of the biggest challenges posed by IoT data explosion. The issue mainly lies with the fact that the IoT ecosystem now comprises multiple devices connected in a network. These devices can access the network through various locations spread across remote offices and newly connected OT networks. Hence, cybersecurity professionals are required to identify each device in the system, assign the ownership and policy, and segment them accordingly. The task does not end here. It is followed by actively monitoring and tracking those devices to secure them. This mammoth set of tasks cannot be just catered to by manual security procedures as it eventually causes unknown devices, rogue access points, and shadow them to operate in an unidentified network.
Cost is one of the major concerns for the IoT devices, given their dramatic demand. Hence, most of the vendors manufacture devices that fulfill bare essential requirements. These features are enough to offer frictionless functionality strived by conventional devices. This is why they potentially fall behind owing to the traditional user interface, making it difficult to update them. Moreover, a plethora of such devices is exposed to blatant vulnerabilities including hard-coded backdoors. These, if left unprotected or are not provided with adequate security, render perfect gateways for the cybercriminals to exploit. They deploy AI-powered attacks that can effectively identify the vulnerable areas. In other words, the technology transforms devices into malware proxies having a potential to attack networks on a large scale while being a part of it.
Cryptojacking is Still One of the Major Concerns
Cryptojacking is a process by which the computing devices are secretly used to mine cryptocurrency. Now that IoT and OT devices are potentially less visible, they provide opportunities for the cryptojacking attacks that exploit these devices to mine cryptocurrency. This poses a more significant threat for the networks that use IT for managing the operations. The success of cryptojacking efforts directly affect the efficiency of the overall system and cause it to slow down.
Applying Artificial Intelligence to Level Up the IoT Security Game
IT professionals have been applying their proactive outlook in order to secure the IoT and OT devices and minimize the threat landscape by restructuring the security posture using AI. This particular technology, called Artificial Intelligence, empowers integrated and automated security fabric thus strengthening the security of the digital transformation efforts like IoT implementation. And the best part is, it does so while having least impact on the network integrity.
Let’s trace down some of the benefits offered by AI or fabric-based defense mechanism:
- Comprehensive Device Visibility: AI-enabled network access controls enable the IT professionals to gain a better a clear visibility of each device in a network, at every point of time. This, in turn, makes it possible for them to monitor, track, and analyze the security parameters at machine speed, thus strengthening the IoT infrastructure.
- Unified Threat Analysis: Digital transformation does not come easy. It includes integration of a wide array of devices along with the rapid expansion of the network parameters regardless of the fact that they are physical or cloud-based. AI does precisely this for you. By automating the threat security infrastructure, it allows cybersecurity teams to leverage the latest analysis data for detecting vulnerable parameters and apply the security solutions to keep the threats at bay.
- Automated Threat Containment: Every particular moment matters when it comes to a security breach. Longer the network breach remains undetected, higher the casualties. This aspect is more significant when it comes to sectors like healthcare, financial industry, and critical infrastructure areas where every device needs to function at all the time. Small negligence might not only lead to massive financial losses, but also take a toll on the lives of employees, patience, or citizens. However, with AI-powered security measures, this problem can be solved. By keeping the IoT and OT containment processes automated, it makes it possible to segment the affected devices or taken offline before the threat expands to other nodes in the network.
As we said, the digital transformation efforts of organizations have sparked a trend towards IoT and OT adoption. However, the cybercriminals are posing shoulder-to-shoulder defense expanding their capabilities, harnessing the potential of new technologies and techniques to brainchild advanced and more serious threats. To offer a robust defense mechanism against security threats, IT teams need to stand at the forefront of this challenge by leveraging AI-assisted security solutions in their app development processes. These solutions should be capable of providing quicker detection and response capabilities much-needed to beat the cybercriminals.
Apoorv Gehlot is the founder of Matellio LLC, a software engineering studio based in California, USA. Being an avid learner, he takes a keen interest in exploring various aspects of the digital realm, and ideate some of the finest solutions with his team of innovators. Apoorv believes in sharing his time-tested experience and deep-rooted knowledge with the readers across the world to enlighten the audience through concise and meaningful write-ups.