nervous-system

Getting Started with Predictive Security Analytics

The amount of digital fraud taking place is increasing rapidly. The combination of a wide variety of different payment methods and an increasing propensity towards online retail has led to a perfect storm in which hackers are threatening businesses all over the world. In this context, the reporting of suspicious activity is steadily increasing, with new types of fraud and angles emerging on an almost weekly basis.

According to the Internet Crime Complaint Center, cybercrime complaints to the FBI topped 300,000 for the third year in a row in 2011. This growing trend for cybercrime necessitates organizations to develop the ability to effectively respond and plan for criminal activities targeting not only their business, but also customers and partners. Recent high profile breaches of security have put this issue even more markedly under the spotlight.

In an increasingly digitalized economy, and one in which new economic elements such as mobile payment systems are coming online with rapidity, predictive or anticipatory mechanisms are becoming essential baseline requirements for any business wishing to satisfactorily manage risk. Such technology can also assist with refining an organization’s internal processes, and play a part in educating a workforce to more satisfactorily monitor and analyze important transactions, trades, procedures and behaviors which can be exploited by criminals.

Unfortunately, many businesses are facing up to the fact that they have already been infiltrated. When utilizing conventional security methods, no matter how well these have been implemented, routine breakdowns within control systems are virtually inevitable. These create massive opportunities for functional cybercrime to be carried out, taking advantage of such flaws in a network as compromised credentials, malware intrusions, and unaccounted privileged access.

What should be understood is that it is almost without exception far more costly to mend and explain what has gone wrong rather than allocating funds to address it before it does. Ensuring that security processes are improved, mistakes are not duplicated, and vulnerabilities within a network are appropriately addressed should be considered absolutely essential. But the best way to deal with the threat of fraud is to stop it before it can take place, and this is where predictive security analytics comes in.

Although this is not a new concept, the sophisticated algorithms which are being developed by companies such as Gurucul ensure that the efficiency of this technique has reached a new level of proficiency. What such software should ideally be able to tell a business is where it is most likely to be attacked next, which facets of the company are most vulnerable and likely to be targeted, how the early warning signs of an attack will manifest themselves, and how quickly and effectively the predictive software can identify these signs.

Truly effective predictive security analytics software will also draw together all of the security information accumulated across the network to create a truly holistic impression of the entirety of the security environment within a particular company. Prediction is not just about looking into the future, it is also about bringing together resources to identify trends and assess attacks before they materialize.

The whole concept of predicting threats before they occur is obviously a valuable one, But it should be understood that it has become particularly important in recent years. If we jumped back a decade, then attacks on a system such as Internet worms, e-mail spam and opportunistic hacks were the prevalent security issues of the day, and these could be fairly easily dealt with via firewalls, antivirus software and spam filtering mechanisms.

Today, though, attacks against any business are likely to be stealthier, targeted in a far more sophisticated manner, and gradually emerging. They’re carried out by highly skilled individuals, often information technology professionals, who have built up vast knowledge on the best way to make companies vulnerable. They move quietly within your organization, sometimes for periods of years rather than months, steadily acquiring everything they need for their malicious attacks. Without predictive software, identifying them can be simply impossible.

Thankfully, software such as Gurucul Risk Analytics (GRA) is providing companies with the ability to respond to these threats. GRA is built around Actionable Risk Intelligence, a flexible and sophisticated system which is able to profile systems and users rapidly, and which even features self-learning algorithms.

Securing a network may be more complex that it has ever been previously, but predictive security analytics solutions are enabling businesses to successfully fight back against attackers.

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