As organizations are hosting their critical data on virtual servers and with greater use of networking, automation, and the internet, the risks associated have increased manifold in cyberattacks. As in any other activity, intelligence is critical to ward off any attack by enemies. In the IT context, threat intelligence and detection are the knowledge that allows businesses and government organizations to prepare and prevent such attacks.
Threat intelligence is backed by data that allows one to know in advance the attackers’ identity, their motivation, how capable they are. This also indicates that areas in the system are weak or vulnerable, which could be the potential target. By knowing this crucial information’s as an intelligence input, cyber experts make informed decisions on how to beef up the security.
Threat detection is addressed by Seceon through User Entity Behavior Analytics (UEBA) riding on Machine Learning algorithms to identify various tactics and techniques used the perpetrators.
This activity is carried out in the IT ecosystem that helps scan and analyze the entire network and identify if there is any malicious activity that can compromise the network. If any threat is detected, the efforts to mitigate and neutralize them before they can exploit the vulnerabilities present in the system.
Getting breached can be a nightmare for any organization, and almost all organizations are now prioritizing their cyber security controls. They are putting the smart technologies and people to work on the information received by creating a defensive barrier in anticipation of anyone trying to cause trouble. Cyber security is an ongoing process and continuously needs to be alert as it is not a guarantee against attacks.
The concept of threat detection is multifaceted when reviewed against specific security programs of different organizations. The worst-case scenarios must always be considered when irrespective of the best security program of an organization, something slips past the defensive or preventive technology and becomes a threat to the system.
Threat Detection and Response
Speed is the essence when it comes to threat detection and mitigation. It is crucial for security programs to detect threats efficiently and quickly so that attackers do not get enough time to zero into sensitive data. A defensive program is wired to prevent most threats based on their past experience and analysis. This means they know the attack pattern and how to fight them. These threats are considered “known threats.” In addition to them, there are other threats of the “unknown’ variety which organizations have to detect and battle against. This implies that these threats have not been encountered before, as the attackers may be using new techniques and technologies to circumvent the existing barricades.
It is also seen that even the known threats can sometimes slip through the defensive measures. This is why organizations should look out for both known and unknown varieties in their IT environment.
So how can an organization ensure that they detect both known and unknown threats before any damage is caused? There are several ways one can boost one’s defense arsenal.
- Threat intelligence leverage
Threat intelligence helps to understand past attacks and compare them with enterprise data to identify new threats. This is effective when detecting known threats but may not provide valuable inputs for unknown ones. Threat intelligence is used frequently in antivirus, IDS or intrusion detection systems, Security Information Event Management, and web proxy technology.
- Setting traps for attackers
Attackers find some targets too tempting to leave them. Many security teams know this and set up bait for the attacker, hoping that they succumb. An intruder trap could be a honey trap within the in-house network services. They might appear appealing to the attacker, who prefers using the honey credentials with all the user privileges. This attacker goes after triggers an alarm to the security system data. The security team gets alerted to potentially suspicious activity in the network and nudges them to investigate even if nothing has happened.
- Behavior analytics of users and attackers
Using tools for user behavior analytics, an organization will be able to understand the expected behavior of its employees. For example, what kind of data employees typically access, what time they usually login into the system, and from which location. A sudden change in their behavioral pattern, like login into the organization systems at 2 am from another location, arouses suspicion as the concerned employee usually works from 9 am to 5 pm and never travels. This unusual behavior calls for an immediate investigation by the security team.
For attacker behavior analytics, it is challenging as there is no reference or baseline benchmark for activity comparison. Here one has to look out for unrelated activities detected on the network, which attackers leave behind as breadcrumbs activity. Here, both the human mind and technology get together to put in place pieces of crucial information that help form a clear picture of what the attacker could be up to on the organization network.
- Carrying out threat hunts
Instead of waiting for threats to appear, the security team takes a proactive approach. It goes outside their network endpoint to look for attackers that may be lurking nearby. This is an advanced technique used by security experts and analysts who are threat veterans. Also, using all the above combinations of approaches is an excellent proactive way to monitor data, assets, and employees.
Two-pronged approach for threat detection
For an effective threat detection strategy, both human and technology is required. The human component is the security analysts who analyze the trends, behavior, patterns, data, and reports and identify deviant data that indicates a potential threat.
Technology also plays a crucial role in detecting threats though no single tool can do this job. Instead, there is a combination of tools that are collated across the network that helps to identify the threats. A robust detection mechanism that needs to be deployed includes.
- Aggregate data from events in the network, including logins, network access, authentications.
- Monitoring the traffic patterns and understanding them in the organization network and the internet.
- Detecting endpoint activity on users’ machines to understand any malicious activity.
- A compromised Credential is a clear indicator of an insider trying to gain access to information that he or she could potentially misuse. As shown in the screenshot below (aiSIEM Portal), a particular user was found to be logging into an unexpected host – which was a departure from profiled behavior.
- Data Exfiltration is also an activity that may be undertaken by the insider. In this case, there may be indicators of increased communication with a high-value host. The techniques applied are similar to Data Breach Detection use case.
By employing a combination of defensive strategies and methods, organizations increase their chances of detecting threats quickly and effectively canceling them out before any damage to the network is done. Cyber security is a continuous process, and service providers like Seceon use the most advanced artificial intelligence for the technology required for threat detection. They provide remedial platforms for organizations beyond traditional defense tools that are often silos in nature. By providing a comprehensive real-time analysis of vulnerabilities, they detect threats and eliminate them in real-time.