Why Knowledge Transfer is Crucial in Incident Response

One common challenge for organizations in both the public and private sector that’s almost ubiquitous, is how successfully knowledge transfer happens between employees in a consistent way. A process for training and knowledge transfer often seems to be a low priority when other items are competing for time and money. As a result, knowledge transfer becomes somewhat an ad-hoc process. There’s frequently no formalized processes in place and this leads to inconsistent and unreliable performance of security team members.

What is knowledge transfer and why do we need it?

Essentially, it’s the transfer of knowledge related to incident response processes, intelligence, and procedures from senior, more experienced incident responders to less experienced ones, acting as an organizational force multiplier. “Force multiplier” here means taking existing resources and preparing them in a way that improves your organization’s or team’s processes. Depending on the industry, sometimes this is referred to as “tribal knowledge”.

Why do we need knowledge transfer as part of our IR infrastructure?

As threats evolve, our response capabilities have to evolve too. So how do we make sure that the knowledge picked up during an investigation by one incident responder is effectively communicated to the other team members? We all know that experience is the best teacher, but transferring the experience they have garnered from previous investigations can be time-consuming. One thing that incident response teams don’t have is a plethora of time to afford spending on all the tasks that need to be done. Therefore, a training program has to be built on a foundation of knowledge application (how it was effectively used), and not merely on the provision of knowledge (this usually comes out as anecdotal examples that frequently lack validity).

Knowledge transfer provides us with three key elements needed for a successful incident management process. That process has to be repeatable, defensible and consistent. Unfortunately, there are still many organizations that lack the capacity to transfer the knowledge and skills among employees, and a lot of the time as a senior more experienced expert leaves so does their knowledge. This is a significant issue that should be addressed and steps need to be taken in order to manage and mitigate this in the future.

Knowledge transfer is such an important segment of cybersecurity, it is strange how it’s still not a core part of SOC operations. There is hardware and software personnel leading to a growing necessity for integrating knowledge transfer into SOCs. Unfortunately, training doesn’t have a high priority when team members get so many alerts daily and are always reacting to the next potential serious incident. Typically an analyst joins an organization and they’re handed basic information and are thrown into the deep, without really having a good knowledge foundation.

Another important point to highlight is the difficulty to gauge the ROI. If you take an analyst that is untrained and measure how long it takes them to work on an incident compared to an analyst who is trained, it is a time-consuming process in itself. So, if we can’t gauge the ROI (it quickly becomes a non-priority considering the importance of SOC metrics, for example, mean time to detection, mean time to response and the number of incidents handled.

There are other alternatives to a formalized process, but with no structure it is easy for something such as an internal shared drive to become a dumping ground for information, leaving small positive impact on the daily operations.

Knowledge transfer doesn’t just concern incident responders. Legal experts need to be included for GDPR compliance and HR for personnel issues considering the dangers of insider threats. HR should be working closely with all teams and must be aware at all times of the processes taking place within the security team.

And finally, the stakeholders for ROI considerations and funding. It’s important that they know exactly how your processes and procedures work, even if it’s at a high level, so when the time comes to present quarterly reports and present them to the board, they’re have firm understanding exactly how it contributes to a positive ROI.

These are just some of the factors that determine why knowledge transfer should be a fundamental part of SOC operations and if knowledge transfer can be effectively facilitated it can have a positive impact on individual analysts, security teams and overall performance.  

In a future blog we will discuss the 5 key elements of implementing successful knowledge transfer in incident response, but if you can’t wait, why not check out our recent webinar on-demand now “How to Facilitate Knowledge Transfer in SecOps Utilizing SOAR Technology”.

Leveraging SOAR Technology to Facilitate Knowledge Transfer in Security Operations

Earlier this year I was talking to a colleague about the state of SOC operations and how I was looking forward to going to the SANS Security Operations Summit in New Orleans in July. The folks who attend SANS events are at the top of their game and let’s be honest, SANS provides some of the best training in our industry, so what’s not to love?

The conversation quickly turned to how to provide better scalability within SOC operations. Given that our teams are confronted with an increased number of alerts coming from more sophisticated actors on a daily basis, how do we keep up? We spoke about the need for better security automation to enrich the information available at the onset of an incident and how malware has been automating since the Morris worm 30 years ago.

At one point she asked me how best we can handle the transfer of incident handling “tribal knowledge” from the senior Incident Response personnel to the junior members, given the daily workload they carry. I thought about it for a moment and threw out that perhaps increased spending for machine learning or AI could help bridge the knowledge gap. She then asked, “Couldn’t we take that money and invest in knowledge transfer within the team instead?”. That simple and simultaneously complex question got me to thinking about how we can better utilize existing resources to provide that knowledge transfer in an environment as dynamic and rapidly changing as an Incident Response organization.

I thought this topic was interesting enough to make it my focus for my upcoming speaking engagement at SANS.

As we already know an increased workload coupled with an industry-wide shortage of skilled responders is heavily impacting operational performance in Security Operations Centers (SOC) globally and an integral part of the solution is formulating a methodology to ensure that crucial knowledge is retained and transferred between incident responders. By utilizing Security Orchestration, Automation and Response (SOAR) technology, security teams can combine traditional methods of knowledge transfer with more modern techniques and technologies.

Join me at the SANS Security Operations Summit on July 30, 2018 at Noon for an informal “Lunch and Learn” session to discuss how we ensure that the Incident Response knowledge possessed by our senior responders can be consistently and accurately passed along to the more junior team members while simultaneously contributing to the Incident Response process. I look forward to meeting you there.

If you are not attending the summit, don’t worry, you can visit our website to find out more information about the benefits of utilizing a SOAR solution with DFLabs’ IncMan SOAR platform.  Alternatively, if you would like to have a more in-depth discussion, you can arrange a demo to see IncMan live in action.

Transitioning Your SOC Analysts from Data Gatherers to Threat Hunters

Threat hunting is defined as an iterative and focused approach to searching, understanding and identifying internal adversaries that are found in the defender’s network. It’s been shown that incident response automation tools can provide Security Operations Center (SOC) team members with additional time that can be leveraged in a more focused, threat hunting role within the SOC environment.

The SOC staff members should have some understanding of how they can use this additional time provided by incident response automation to enable them to hunt for threats, rather than spending valuable time and resources gathering threat information which could otherwise be done in an automated fashion.  It’s long been established as we make the migration from threat prevention to threat discovery that malicious actors and processes are frequently well-hidden within the organizations infrastructure and in order to effectively locate and investigate them we must start by asking the 5 W’s, who, what where, when, why and perhaps most importantly, how.

SOC team members must first understand what threat hunting is to be truly effective. The staff members should channel their question on the three tenets that make up the threat triangle; capability, intent, and the opportunity. By focusing on these three tenets, threat hunters can leverage orchestration to accomplish not only the system monitoring but the automated data gathering to support this expanded role without adding additional infrastructure. Additionally, team members must understand that the threats can be human and not just, for example, malware that is directed at them. This, coupled with an understanding of the affected systems function, will help provide the insight into possible contributing factors to the incident.

As the level of automation scales upward, we’ve seen a corresponding scaling of the transition from simple incident data gatherers to data hunters. Additional time and resources will become available to teams that leverage incident automation, permitting them to forego the traditional gatherer role and begin to embrace a more proactive hunter role. The good news is both of these roles can be supported within the SOC and also within the same Security Orchestration, Automation and Response (SOAR) platform. IncMan SOAR from DFLabs provides the necessary combination of force multiplication and machine learning to ensure that not only are incidents capable of being prioritized automatically, but the necessary actions for successful resolution are available at incident inception.

If you would like to see how a SOAR platform can give your incident response team the necessary tools to make the migration from simple data gatherers to threat hunters, reach out to us for a free, no obligation demo.

The Importance of Integrating Threat Intelligence into Security Operations Center Response Infrastructure

Cyber threat intelligence (CTI) is an advanced process that helps an organization to collect valuable insights into situational and contextual risks that can be chained with the organization’s specific threat landscape, markets, and industrial processes. Having said this, deploying a Threat Intelligence Platform alone is rarely sufficient enough to address the complexities experienced in today’s Security Operations Center (SOC) environment.

These sources of threat intelligence can be of significant value when assessing organizational vulnerabilities and provide the necessary insight into more than just infection vectors. Threat intelligence provides organizations with the knowledge to effectively correlate data from a number of disparate sources to anticipate attacks before they occur. This directly addresses the three issues most commonly facing responders today; the prioritization of incoming incidents, reducing response time and aggregating data from a number of sources to provide the clearest picture of an incident.  

Designing the most appropriate method of integrating threat intelligence into your information security infrastructure has never been easier. Orchestration and automation platforms such as IncMan SOAR from DFLabs has successfully been used to rapidly integrate threat intelligence into the incident response infrastructure, including Structured Threat Information eXpression (STIX), Trusted Automated eXchange of Indicator Information (TAXII) and other threat intelligence sources. These repositories are based upon community standards that enable the transportation of cyber threat intelligence between intelligence sources and IT security teams.  Further, they strive to facilitate the re-alignment of efforts in proactive IT security that are based on real-time information that exchanges threat information between commercial suppliers, the government, non-profit efforts and industrial partners.

These sources of threat intelligence, once integrated into an incident orchestration platform can now be leveraged to evaluate risks, assess potential damages and proactively correlate threat vectors. By doing so they can automate the prioritization of incoming incidents based on expert forecasts which will help assess the threat tactics, techniques and procedures (TTPs), and provide the formation of a comprehensive incident response strategy by not only identifying the possible attack vector but possible actors as well.

Today’s cybercrime environment involves tactics and techniques that can wreak havoc within our networks in a very brief period of time. These threats have a far reach irrespective of industry or infrastructure classification. Given this speed, it is imperative that we implement a comprehensive threat intelligence program that leverages a centralized orchestration and response platform and permits organizations to aggressively address the constantly changing threat landscapes as a combined effort.

Overcoming the Tower of Babel in Your Cybersecurity Program

Best practices for communicating cybersecurity risks and efficiency

One of the most difficult challenges encountered within risk management in today’s ever-changing cybersecurity environment is the ability to communicate the risks posed to an organization effectively. Security executives expect communication to be in their own language, focusing on the financial implications regarding gain, loss, and risk, and the difficulty of translating traditional security terms and nomenclature into risk statements expected by business executives poses a serious challenge. Therefore, it is the responsibility of a cybersecurity professional to ensure that security risks are communicated to all levels of the organization using language that can be easily understood.

The communication of security metrics plays a crucial role in ensuring the effectiveness of a cybersecurity program. When disseminating information on cyber risks, several aspects of communication should be considered. For example, a security professional should be cognizant of the credibility of the information’s source, the targeted audience and how to place the risk into perspective. We firmly believe that the success of a business today is directly related to the success of its cybersecurity program. This is largely due to the fact that all organizations depend on technology. Specifically, the interconnectedness of digital technologies translates to a significant potential for damage to an organization’s operational integrity and brand credibility, if its digital assets are not meticulously safeguarded. We only need to look at the recent Equifax breach for an illustrative example of this. Considering the potential impact of cyber attacks and data breaches, organizations must improve how they communicate cybersecurity risk.

The first step to ensuring effective communication of cyber risks involves a comprehensive business impact assessment. This must consider the organization’s business goals and objectives. Business impact assessments focus on how the loss of critical data and operational integrity of core services and infrastructure will impact a business. Furthermore, it acts as a basis for evaluating business continuity and disaster recovery strategies.

The second step is the identification of key stakeholders and their responsibilities. According to experts, this step plays a significant role in being prepared to mitigate the impact of cyber risks. Stakeholders are directly affected by a breach and have the most skin in the game. Identifying stakeholders should not be a one-off exercise but must be conducted regularly. An important consideration is that the more stakeholders there are, the greater the scope for miscommunication. Failure to identify the responsible stakeholders will increase the probability that risk is miscommunicated. In the case of a breach, it means that the response will be ineffective.

The third and most critical step is the identification of Key Risk Indicators (KRIs) tied to your program’s Key Performance Indicators (KPIs). Doing this correctly will mean communicating cyber risks to executives in a way that allows them to make informed decisions. As an example, the amount or the severity of vulnerabilities on a critical system is meaningless to non-technical executives. Stating that a critical system that processes credit card data is vulnerable to data loss is more meaningful. Once business impacts have been assessed, stakeholders have been identified, and meaningful security metrics have been determined, regular communication to various stakeholders can take place.

Different stakeholders have unique needs. This must be considered when communicating KRIs and KPIs. When delivering information, we must accommodate both the stakeholders that prefer summaries and those that prefer reviewing data to make their conclusions. DFLabs’ IncMan generates customizable KPI and incident reports designed to cater to both audiences. Cybersecurity program metrics1 must also focus on costs in time and money to fulfill business needs. The ability to track these metrics is a key differentiator for DFLabs IncMan.

DFLabs’ IncMan is designed to not only provide the best in class incident orchestration and response capabilities but also provides the ability to generate customizable KPI reports that accurately reflect up-to-the-minute metrics on the health of your cybersecurity infrastructure. If your organization needs to get a true, customizable view that incorporates all stakeholders please contact us at [email protected] for a free, no-obligation demonstration of how we can truly keep your cyber incidents under control.

Using Incident Correlation to Reduce Cyber Threat Dwell Time

Attackers spend a considerable amount of time conducting reconnaissance on compromised networks to gain the information that they need to complete their objectives for criminal activity, including fraud and intellectual property theft. Dwell time, the amount of time an attacker is present in an enterprise is currently measured in the hundreds of days.

One of the most effective technologies available to incident response teams to help to reduce the threat actor dwell time and limit the loss of confidential data and damage, are Security Automation and Orchestration platforms. Security Automation and Orchestration technologies process alerts and correlates these with threat actors’ Tactics, Techniques, and Procedures. The ability to determine not only the initial ingress point of the attacker but any lateral movement inside the enterprise significantly reduces the time to deploy containment actions. In this scenario, the incident correlation engine is utilized not only as a mechanism for responding and orchestrating the response but also to proactively search for related IoC’s and artefacts. The synergy of response, automation and correlation provide organizations with a holistic approach to reducing cyber incident dwell time. In more mature organizations, these measures are leveraged frequently by IR responders to transition from being threat gatherers to threat hunters.

incman dwell time
Figure 1DFLabs IncMan Observables Hunter and Correlation Engine

When Incident correlation is available within the SAO platform, cyber threat dwell time is reduced through 3 separate but complementary capabilities:

  1. Category based correlation – Correlating incidents by type.
  2.  Asset based correlation – Contextualizing the criticality and function of an asset
  3. Temporal correlation -Providing insight into suspicious activity or anomalous access

Defense in Depth strategies is designed so that high-value targets, such as privileged accounts, are monitored for increased or suspicious activity (Marcu et al. 5). The incident correlation engine not only visualizes this but also provides information to help determine the source of an incident by identifying the points of entry into the affected infrastructure.

“Patient Zero” identification is accomplished through tracking the movement from a source to an end user, and assists responders in determining the epidemiology of the attack, and also possible intruder motives. The correlation engine can achieve this objective through correlating similar TTP amongst incidents and visualizing associational link analysis between hosts. This comparison produces a topology of the lateral movement and can easily identify and visualize the path of an intrusion and the nature of an attack. This permits incident responders to initiate containment actions in real time, as the intentions and objectives of hackers are readily determined.

Dwell time of cyber threats can be significantly reduced from the industry average length, currently measured in the 100s of days, to only a few hours by providing a system capable of identifying not only the magnitude of the attack but by providing a roadmap to successfully hunt the incident genesis point to prevent further proliferation.

Integrating Lessons Learned into Incident Response

Let me start by saying that total prevention is not attainable with today’s technology. Whether through negligence or ignorance, any data stored on a network is subject to unauthorized access by 3rd parties. Instead, we must combine Prevention with Detect and Respond. We know we are going to get breached, so we must focus on the how we deal with that.

One significant activity that can improve cyber incident response and enable the timely mitigation of threats is the transfer of knowledge after an incident as part of a formalized “Lessons Learned” phase of the incident response life cycle. Integrating successful processes and procedures from previously successful incident response activities can play a critical role in determining whether a business will suffer in terms of operational integrity, reputation and legal liability. A publicized security breach will lower customer confidence in the services offered by an organization as well as call into question the safety of their sensitive 3rd party information. This impacts a business credibility and translates directly into lost revenue.

In regulated industries, increased regulatory scrutiny is an additional consequence of a breach. This involves evaluating if the tools and procedures used in responding to security threats were sufficient. Integrating lessons learned into existing and future incident response playbooks ensures that the proper technologies and processes are deployed, and avoids accusations of gross negligence, expensive and time-consuming investigations and regulatory demands.

Procedural improvements can be incorporated into incident workflows via incident playbooks and ensure that all stages of the incident response process have been acknowledged and addressed. It also ensures that required security measures and procedures are documented and relevant stakeholders informed of their roles in case of an incident.

This process can be augmented through machine learning. Applying machine learning to this problem requires that all relevant data associated with incidents are analyzed and automatically applied to future incidents. DFLabs recently released DF-ARK machine learning capability to do precisely this. Our patent-pending Automated Responder Knowledge (DF-ARK) module applies machine learning to historical responses to threats and recommends relevant runbooks and paths of action to manage and mitigate them. DF-ARK requires sufficient training data – it begins with no knowledge, but learns from the experience and actions of your security team, becoming more effective over time. DF-ARK implements supervised case-based reasoning machine learning.

Figure 1DFLabs IncMan Automated Responder Knowledge

It also involves combining automated workflows and manual procedures to keep a human in the loop. This can be constantly improved by applying new observations and data, to fine tune existing methods and procedures identified in the lessons learned phase.

IncMan offers the R3 Rapid Response Runbook engine and Dual Mode playbooks to facilitate this. R3 Runbooks are created using a visual editor and support granular, stateful and conditional workflows to orchestrate and automate incident response activities such as incident triage, stakeholder notification, data and context enrichment and threat containment. Dual Mode Playbooks support manual, semi-automated and automated actions, meaning that users can automate the action without automating the decision.

Adding all of this together, here are 5 best practices for increasing the effectiveness of incident response via lessons learned:

  1. Encourage feedback from responders at every level. First, second and third line SOC operators and incident handlers each have a unique perspective that must be incorporated into future response playbooks.
  2. Review all relevant documentation to ensure compliance. This includes organizational policies or regulatory mandates to ensure any disparities are addressed in future playbooks.
  3. Chronicle any unanticipated or unusual events to extend procedures to mitigate similar occurrences in the future
  4. Annotate enhancements to existing processes that were identified during the incident response cycle.
  5. Designate a business unit or individual to be responsible for making necessary changes to existing playbooks, processes or procedures and to distribute these to stakeholders.

Capitalizing on lessons learned during incident response provides immediate and long-term benefits that contribute crucial time savings necessary to successfully mitigate future threats. Deploying a platform designed to facilitate the rapid inclusion of identified improvements to the incident workflow, such as DFLabs’ IncMan, can not only reduce the time it takes to fully investigate an incident but also reduces the overheads required to do so. If you want more information please contact us at DFLabs for a no obligation demonstration of exactly how we can improve your response time, workflows and remediation activities.

Demolishing the Ivory Tower – Collaboration and Communication in Incident Response

A collaborative environment between IT and security groups is critical. The number of cyber security incidents currently impacting networks and customers is increasing exponentially and mitigating security incidents and risks is more complex than ever before. Timely and effective communication are keys to improved collaboration between all parties involved in the cyber incident response process. One of the simplest and most effective methods to improve communication between all relevant IT and security groups is to deploy a common, shared platform where stakeholders can review and analyze incidents across the entire cyber landscape. A cross-departmental platform enables them to focus on correlating cyber incidents and risks with contextual information relevant to their role and responsibilities plays a significant part in organizational success in this regard.

Incorporating knowledge transfer between disparate business entities often separated both geographically and functionally is essential to facilitate a better understanding of the current IT and security challenges. The preferred method to provide this collaborative environment is via electronic based communication mediums and devices. To tie all of these channels together, an organization should consider deploying a cyber incident response platform, and the platform must be able to integrate these technologies, be it SMS, email or other messaging medium, to cover the broadest range of communication channels to transmit critical information to stake holders.

Another successful strategy that focuses on effectively communicating timely, critical information to relevant stakeholders is via the creation of an incident notification group. IncMan supports the creation of groups of Watchers that are appraised of incidents and activities automatically via SMS, email or an integrated communications system. A Watcher group can ensure that information is properly communicated to the appropriate stakeholder(s). This provides differing stakeholders with the capability of monitoring incidents that may impact business continuity. Additionally, IncMan has integrated communications capabilities comply with industry best practices which recommend having a separate, secure and hardened communications channel if email or other internal communication channels are compromised. This independent messaging capability also provides additional benefits such as asymmetric encryption capabilities.

Leveraging a dedicated solution that can orchestrate the communications to stakeholders standardizes the process of cyber incident response and mitigation and is the key to ensuring a more effective response. If you would like more information or a free no obligation demonstration of how IncMan from DFLabs can more effectively automate and orchestrate your incidents please contact us at [email protected]

 

Security Event Automation and Orchestration in the Age of Ransomware

We have recently experienced a devastating wave of ransomware attacks such as Wannacry or ‘WannCrypt’ which spread to more than 200 countries across the globe. While Russia was hit hard, Spain and the United Kingdom saw significant damage to their National Health Services. Hospitals were forced to unplug their computers to stop the malware from spreading even further. This is just one of the security threats posed by special malware that encrypts computer files, network file shares, and even databases thereby preventing user access (Green 18-19). It happens in spite of heavy investments in a wide array of security automation and orchestration solutions and staff required to triage, investigate and resolve threats.

The primary problem is that organizations seem to be losing the battle against cyber attackers (Radichel, 2). The security administrators are overburdened and compelled to manually perform time-consuming and repetitive tasks to identify, track, and resolve security concerns across various security platforms. Notwithstanding the time and effort, it is difficult to analyze and adequately prioritize the security events and alerts necessary to protect their networks. Still, the inadequate visibility into the present activities of the security teams, metrics and performance leave security managers struggling to justify additional resources. It has long been accepted that the organizational efficiency depends heavily on the ability of the security system to reduce false positives so that analysts can focus on the critical events along with indicators of compromise.

Security event automation and orchestration ensures that an organization detects a compromise in real time. A rapid incident response ensures a quick containment of the threat. Through the automation of common investigation enrichment and response actions, as well as the use of a centralized workflow for performing incident response, it is possible to minimize response times and thus make the organization more secure. Security events automation and orchestration expedites workflows across the threat life-cycle in various phases. However, for the security team to deploy security automation and orchestration of event-driven security, there must be access to data concerning events occurring in the environment that warrant a response. To effectively employ event-driven security, automation should be embedded into processes that could introduce new threats to the environment (Goutam, Kamal and Ingle, 431). The approach requires that there be a way to audit the environment securely and trigger event based on data patterns that indicate security threat or intrusion. Of particular importance, continuous fine tuning of processes is required to make certain the events automation and orchestration being deployed is not merely automating the process, but providing long-term value in the form of machine learning and automated application of incident response workflows that have previously resolved incidents successfully.

At a time of increased cybersecurity threats, a structured approach can expedite the entire response management process from event notification to remediation and closure through automated orchestration and workflow. An automatic gathering of key information, the building of decision cases and the execution of critical actions to prevent and/or remediate cyber threats based on logical incident response processes are enabled. With security orchestration and event automation, various benefits are realized such as cost effectiveness, mitigation of security incidents and improved speed and effectiveness of the response. Hence, security event automation and orchestration is the real deal in containing security threats before real damage takes place.

Visual Event Correlation Is Critical in Cyber Incident Associational Analysis

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]