The advancement in technologies are helping to fuel an unprecedented rise in consumer expectations. For today’s businesses, harnessing evolving digital transformations in order to redefine products, services, and consumer experiences is often the new cost of doing business. Connections to IoT devices, cloud services, and digital wallet systems are exposing businesses to more cyber threats.
Cyber attacks continue to rise and impact both small and large organizations worldwide. Despite all the efforts and measures to take preventive actions, these attacks keep wreaking havoc, with no signs of backing down.
If cybercriminals are anything, they are adaptive. The risk vectors global businesses face continue to evolve, and hackers are finding new ways to attack unseen vulnerabilities. The technology landscape and today’s inter-connected world are changing the cyber security environment, too. There are more attacks proliferating everywhere through the digital associations businesses have with vendors, partners, customers, and online sources.
Transformations in cybercrime techniques mean that businesses need to be sure their tactics from security practices to cyber counter measures and detection—keep pace. The criminals learn about the circumstances and the behavior of their targets.
Any advancement in cybersecurity appears to be only a temporary defense to prevent the entry of malware. Cybersecurity experts have been regularly upgrading and improving their techniques to keep on shoring up their defenses. In the same light, the cybercriminals may only be one-step behind the security experts, as they keep on finding ways to catch up with their own upgrades and improvements. The result is that a completely new approach is needed to stop future attacks, which may come from within or outside the company.
Fighting Cybercriminals with Behavioral Analysis
A new age of defenses are focusing on stopping hackers in their tracks and identifying them instead of just building so called “impenetrable walls”. The new technology harnesses the user’s profiles and patterns. It then uses this as the basis of comparison in subsequent visits to identify a user’s pattern of behavior in applications and IoT devices.
A visitor who transverses an e-commerce site moves his cursor using a certain pattern, type at a certain speed, and taps at a certain force. The security system will learn after a few logins how a particular user browses slowly, types at an average speed, tap icons with a strong force, and swipes at a unique pattern. If a cybercriminal gets hold of the user’s login information, but browses at a different speed, types very fast, taps icons with a weak force, and swipes using a different pattern, the security system will learn that person is not the original user. The system, noticing that it is a different person who used the login information, may ask the hacker to provide further authentication. Most likely, the hacker will not have any of that. The system will then prevent the hacker from logging in.
In a retail environment, there are a ton of different aspects of the store that may be potential security exposures — ranging from the interconnected devices on the network to the Point of Sale (POS) and selling systems, to HVAC, and other systems that are powering each store location. Each of these systems create signatures that have a normal pattern of behavior. A behavior-based system can notify security or system administrators as it detects an abnormal pattern. This allows them to take proactive measures in real time.
NitroDefenderTM to the Rescue
NitroDefenderTM is one the most progressive cyber-defense technology companies on the tech scene. It uses unsupervised deep neural networks that mimic the way the human immune system responds to an external threat. The system self-learns the user’s normal network and raises the red flag when it senses an anomaly. The system then works to stop an attack without any program or human telling it what to look for.
NitroDefenderTM takes inspiration from the ability of the human body to detect when it is compromised. It triggers an immune response as a defense against the anomalies. NitroDefenderTM delivers a more comprehensive, more intelligent, and faster defense against threat than other existing cybersecurity solutions.
The defense system extensively uses machine learning, deep neural networks and recurrent neural networks to predict an attack. It learns about users, devices, and networks they use in order to establish what normal behavior is and distinguish it from abnormal behavior.
NitroDefenderTM is a bold move in the right direction. A new frontier in cyber defense now provides progressive companies and government institutions a way to thwart internal or external security attacks.
