Hackers’ reconnaissance activities are shrouded within massive amounts of data, and are difficult to detect.
Chris Smith is director of cybersecurity strategy at SAS.
By the time a cyberattack is discovered, the hackers responsible may have been inside a network for months. During that time, hackers lurk persistently and become increasingly undetectable within the network, where they uncover and later extract an organization’s most valuable information.
Hackers’ reconnaissance activities are shrouded within massive amounts of data and are difficult to detect. By harnessing and enriching all this data in real-time and applying complex behavioral analytics, agencies can do just that – adding an essential layer of cyber defense.
To be successful, hackers need three elements, including:
There is little in the way of means, or resources, that can be done to prevent a cybercrime. Once a person develops sufficiently sophisticated coding methods, they can use their skills in whatever way they choose.
Whether they choose to act benevolently or maliciously, it is up to the coder to decide how they apply their techniques. The most common are phishing, man-in-the-middle, backdoor, zero-day and keylogging. The availability of pre-packaged scripts (like Lizard Squad’s distributed denial-of-service script) also contributes to means, even if the attacker lacks the technical sophistication needed.
Most people are motivated by money; there is a financial gain from stealing information either directly – for example, stealing credit card numbers – or in a more round-about way – like selling personal information. Recent trends show hackers are increasingly focused on breaching information systems that hold identity data.
Why? It is simple: Breaching identity data is the same amount of work for a hacker as breaching any other system, but yields a greater return on their investment.
Hackers may be ruthless in their attempts to access systems and services and want to tilt the risk to reward ratio in their favor. Infiltrating Home Depot’s database versus an insurance carrier’s may be minimally different, but the value of the data exfiltrated is far higher with identity data.
This information is more valuable because it opens the door to purchasing large dollar items directly, and gives them the opportunity to open new credit accounts based on the information breached. This leads to a greater number of fraud schemes becoming operational prior to detection. Instead of stealing a bag of money from a bank, they are stealing the bank’s key.
From the nation-state point of view, data obtained from a breach – such as the Office of Personnel Management incident – can provide an adversary with a complete understanding of federally employed individuals. Employees’ affiliations, organizations, locations, family and other information can all be gleaned based on identity data and could be extremely useful in intelligence operations.
Organizations will always be at risk based on the security of their downstream providers, such as insurance providers, and third-party business services. If a hacker cannot walk directly in the front door of their target, why not leverage the weakened security posture of downstream providers to the target, and use this information to gain greater access or information that will finally help to breach the target organization?
There are many elements that go into keeping data secure: encryption, database infrastructure, as well as document locking and tracking. While infrastructure may be a larger transition and require more effort for an agency, the smaller steps to security may mitigate risk of data breaches – such as implementing analytics.
This gives an organization a better understanding of where vulnerabilities and risks lie within their security or personnel. With that knowledge, leaders can assess how to strategically reinforce their cyber posture and eventually prevent more breaches.
Agencies can remove a hacker’s opportunity for stealing data – applying cyber analytics to private or confidential information can mitigate the risk of that data being stolen. At the very least, it provides a means to decipher how the information is being used and by whom.
Cyber analytics has a wide range of capabilities, for example, near real-time monitoring, data aggregation for increased visibility, anomaly detection, behavioral analytics and risk prioritization. Each of these put the advantage back in the agency’s court, enabling them to mitigate a hacker’s means, motives and opportunities.
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