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The Future of Cyber Security Is Autonomous

The Future of Cyber Security Is Autonomous

In the last few years, cybersecurity has been a hot topic among major defense contractors and government agencies. However despite being neglected in decades past, cybercrime is rapidly becoming more dangerous than terrorism. With the proliferation of cheap hacking tools and custom malware infections, small-time players can carry out attacks which used to only be possible by state actors with deep pockets. This has prompted the development of new defense systems that are designed to counteract these threats – but can they succeed?

Advances in technology are expected to bring about even greater changes in the coming years. Artificial intelligence, smart machines, and other innovations will change how wars are fought. But while some military leaders have expressed concerns over this potential paradigm shift, others are more optimistic. Many of them are taking advantage of these advancements to create new security tools that will surely be vital in the future.

But at what point does technology stop being a defense tool and start becoming an offensive weapon? As cyberwarfare becomes increasingly automated, it could happen sooner than anyone realizes.

Ransomware Defense

Cyber security has come a long way in recent years, with AI becoming more valuable than ever before. The future of cyber security is autonomous; instead of waiting to respond to attacks after they happen, it may be possible for computers to predict cyber crime behavior before it actually takes place. This could include everything from predicting the location and time of the attack to precisely identifying the origin of the threat.

Autonomous cyber security systems could then be used to defend against these attacks before they happen, making computer systems more resilient and lowering risk for all involved. Even if an autonomous system is not able to prevent every cyber crime incident from happening, it can help reduce their frequency while increasing detection rates, which is still a big upgrade over current reactive security measures.

Currently, many companies are taking their first steps in this direction using machine learning algorithms to establish baselines of normal behavior in order to then flag any activity that deviates from that norm. For example, if an employee typically logs into their financial software between 9am and 5pm on Wednesdays from their desktop computer, an algorithm may determine that anything deviating from this behavior could be a threat. If the behavior indicates a threat, the company can then take proactive measures to address it before any harm is done.

Technical Account Management

Technical Account Management (TAM) can be described as an approach to securing software. It is a process that incorporates security assessments, recommendations, and compliance with industry standards into the development life cycle of a given application. TAM is designed to ensure that all infrastructure components are adequately protected by identifying weaknesses in design or implementation that could potentially allow unauthorized access to an application or the underlying information systems.

Cloud Data Backup 

The first step for any business looking to improve or implement their cyber security plan is an assessment of how current policies and systems protect their information assets. Every company has different goals, priorities, and tolerance for risk, which means no single solution will work for everyone. A better cyber security solution helps you choose the right cloud data backup plan that fulfills your business needs.

As cyber security problems expand and new vulnerabilities are discovered, a paradigm shift in how we manage this data is necessary to minimize risk. For example, the Equifax hack compromised 145 million Americans personal information. In this event, these individuals had their social security numbers stolen from a central database where they were stored. In order to combat such data breaches, a new paradigm for cloud data storage is required. The amount of data being collected from our smartphones, credit cards, and other personal devices is absurdly large and will only continue to grow exponentially. In order to manage the growing collection of user digital footprint, researchers are looking into a new type of database that can securely store an individual’s information without a central authority. Specifically, researchers are working on a decentralized database that will have no singular point of failure and where control is distributed among the user network. This paradigm shift in cloud storage would ensure that our digital footprint is never lost to a single hack again.

Next Generation Endpoint Monitoring

Endpoint security products monitor activity on endpoints by scanning files and communications to detect known patterns that may indicate suspicious behavior. They also monitor endpoint configuration and system settings for unauthorized changes. Endpoint security products can be installed on a user’s machine or a server to protect the entire network infrastructure.

New research by the Ponemon Institute shows that organizations that invest in endpoint monitoring and machine learning-based solutions to gain at least a basic level of protection against cyber attacks, see fewer targeted email attacks than those companies without any form of security. The companies using these types of products were attacked on average 3 times compared with the companies that didn’t use endpoint monitoring or machine learning-based solutions, which were attacked an average of eight times.” 

While this is bad news for companies without these products, it highlights the importance of using technological advances in cyber security alongside other best practices.

Endpoint security products monitor activity on endpoints by scanning files and communications to detect known patterns that may indicate suspicious behavior. They also monitor endpoint configuration and system settings for unauthorized changes. Endpoint security products can be installed on a user’s machine or a server to protect the entire network infrastructure.

Real Time Network Monitoring

Today, the world of cyber security is dominated by humans fighting against machines. No longer can we rely on  defending  our computer systems; what we need now is the  ability to  anticipate  our opponents’ next move, and that is what autonomous systems provide.

Autonomous systems are only the beginning of how artificial intelligence will change cyber security. First, real time network monitoring using neural networks can be used to identify threats faster than our opponents can use them. For example, recently Google revealed its latest project: a “forced” neural network, which the company claims is so effective that it can identify malware files that were trained on for months and have never been seen. And if we take into consideration how popular software-as-a-service solutions are becoming, it’s clear that this technology will soon spread throughout cyber security.

Finally, artificial intelligence provides completely new ways to defend our systems against cyber attacks. For example, autonomous systems are being devised that will identify intrusions into company networks quickly and stop them before any damage can be done.

The future of cyber security is autonomous systems that will learn from their mistakes and constantly adapt to new threats. Contact Bayshore Interactive and stay ahead of the curve with A.I. powered security.