Companies across different industries around the globe, along with government institutions, cite cyber attacks as one of the biggest security threats to their existence. As a matter of fact, in a recent Forbes survey of over 700 companies from 79 countries, 88 percent of respondents said that they are “extremely concerned” or “concerned” by the risk of getting attacked by hackers.
This fact is a clear indication that organizations have to ramp up efforts for enhancing their cyber resilience, but to do that successfully and in the most effective manner, they need to have a clear understanding of where the biggest cyber threats come from nowadays so that they can shape their cyber defenses accordingly. We take a look at the most common cybersecurity threats today, ranging from internal threats, cyber criminals looking for financial gains, and nation states.
When talking about cyber security, some of the first things that usually come to mind are freelance hackers and state-sponsored attacks between hostile nations. But, many cyber security incidents actually come from within organizations, or to be more specific, from their own employees.
Pretty much all experts agree that employees are some of the weakest links in the cyber defense of every organization, in part due to low cyber security awareness, and sometimes due to criminal intent.
Employees often put their companies at risk of getting hacked without meaning to, by opening phishing emails or sharing confidential files through insecure channels, which is why organizations should make sure their staff knows the basics of cyber security and how to avoid the common cyber scams and protect data.
With so many devices connected to the Internet nowadays, including video cameras, smart phones, tablets, sensors, POS terminals, medical devices, printers, scanners, among others, organizations are at an increased risk of falling victim of a data breach. The Internet of Things is a real and ever-increasing cyber threat to businesses and institutions, deteriorating their vulnerability to cyber attacks by adding more endpoints that hackers can use to gain access to networks, and by making it easier for hackers to spread malicious software throughout networks at a faster rate.
The Internet of Things is one of the factors that make DDoS attacks more possible and more easily conducted, and these types of attacks can have a significant and long-lasting impact on organizations, both in terms of financial losses and reputation damage.
Private entities and government institutions that are part of the critical infrastructure in their countries are under a constant threat of different types of attacks by hostile nations. As the number of channels and methods that stand at the disposal of hackers aiming to gain access to computer networks grows, organizations in the public and private sector are facing a growing risk of cyber attacks sponsored by nation-states that might have an interest in damaging the critical infrastructure of other countries, hurting their economies, obtaining top-secret information, or getting the upper hand in diplomatic disputes.
Most commonly, nation-state-sponsored cyber attacks use malware, such as ransomware and spyware, to access computer networks of organizations, as a means of gaining control over certain aspects of the critical infrastructure of another country.
No matter what types of attacks are common today, the number and level of sophistication of cyber threats to organizations are certainly going to grow in the future, which is why they have to constantly update and adjust their cyber defenses accordingly.
I can remember sometime around late 2001 or early 2002, GREPing Snort logs for that needle in a haystack until I thought I was going to go blind. I further recall around the same time cheering the release of the Analysis Console for Intrusion Databases (ACID) tool which helped to organize the information into something that I could start using to correlate events by way of analysis of traffic patterns.
Skip ahead and the issues we faced while correlating data subtly changed from a one-off analysis to a lack of standardization for the alert formats that were available in the EDR marketplace. Each vendor was producing significant amounts of what was arguably critical information, but unfortunately all in their own proprietary format. This rendered log analysis and information tools constantly behind the 8-ball when trying to ingest all of these critical pieces of disparate event information.
We have since evolved to the point that log file information sharing can be easily facilitated through a number of industry standards, i.e., RFC 6872. Unfortunately, with the advent of the Internet of Things (IoT), we have also created new challenges that must be addressed in order to make the most effective use of data during event correlation. Specifically, how do we quickly correlate and review:
a. Large amounts of data;
b. Data delivered from a number of different resources (IoT);
c. Data which may be trickling in over an extended period of time and,
d. Data segments that, when evaluated separately, will not give insight into the “Big Picture”
How can we now ingest these large amounts of data from disparate devices and rapidly draw conclusions that allow us to make educated decisions during the incident response life cycle? I can envision success coming through the intersection of 4 coordinated activities, all facilitated through event automation:
1. Event filtering – This consists of discarding events that are deemed to be irrelevant by the event correlator. This is also important when we seek to avoid alarm fatigue due to a proliferation of nuisance alarms.
2. Event aggregation – This is a technique where a collection of many similar events (not necessarily identical) are combined into an aggregate that represents the underlying event data.
3. Event Masking – This consists of ignoring events pertaining to systems that are downstream of a failed system.
4. Root cause analysis – This is the last and quite possibly the most complex step of event correlation. Through root cause analysis, we can visualize data juxtapositions to identify similarities or matches between events to detect, determine whether some events can be explained by others, or identify causational factors between security events.
The results of these 4 event activities will promote the identification and correlation of similar cyber security incidents, events and epidemiologies.
According to psychology experts, up to 90% of information is transmitted to the human brain visually. Taking that into consideration, when we are seeking to construct an associational link between large amounts of data we, therefore, must be able to process the information utilizing a visual model. DFLabs IncMan™ provides a feature rich correlation engine that is able to extrapolate information from cyber incidents in order to present the analyst with a contextualized representation of current and historical cyber incident data.
As we can see from the correlation graph above, IncMan has helped simplify and speed up a comprehensive response to identifying the original infection point of entry into the network and then visual representing the network nodes that were subsequently affected, denoted by their associational links.
The ability to ingest large amounts of data and conduct associational link analysis and correlation, while critical, does not have to be overly complicated, provided of course that you have the right tools. If you’re interested in seeing additional capabilities available to simplify your cyber incident response processes, please contact us for a demo at [email protected]