How to detect a Targeted Cyber Attack
A targeted attack is any malicious attack that is targeted at a specific individual, company, system or software. Targeted cyber attacks are considered higher risk with higher rewards for attackers than the average random attack. Attackers’ main motivations are usually always financial, with the goal to steal information and extort money from the victims. All organisations should Your company should be ready for a targeted cyber attack and have set processes and protocols in place to best deal with the possibility of this occurring.
Detecting a targeted attack is difficult, especially because attackers have mastered the art of being almost invisible to avoid the repercussions, such as prosecution for their illegal actions. Attackers use tools that are familiar to your environment and they generally stay away from tactics that might cause suspicion.
It is advisable to implement monitoring systems that record all events that take place on a network. The information that has been collected in this way can then be used to investigate real threats. However, monitoring solutions typically capture millions of events per month which is far too many alerts for security teams to handle individually. Too many of these alerts also turn out to be false positives and all these false alarms end up detracting from the real incidents that actually matter.
So how does a company really detect a targeted attack? The answer is to use a detection and response solution that not only picks up suspicious events, but does the background work to investigate the context of the events using machine learning and behavioural analysis. Placing each event into the proper context, the automated system can filter out the false positives without the IT team wasting their valuable time.
With technology advancing at such a rapid rate, it’s great to know that detecting threats efficiently is possible with F-Secure, which uses their innovative technology in vulnerability solutions like their RADAR product to hone in on the incidents that matter.