Sanjay Aurora wrote an interesting blog post about using the immune system as an analogy to inspire CISOs to rethink how we do cyber security:
By understanding and continuously refining our grasp on what is inside us — the “self” and what is “normal” — the human body can detect abnormalities and respond in real-time to anything it identifies as a threat.
…We do not expect our skin to protect us from viruses — so we should not expect a firewall to stop advanced cyber threats which, in many cases, originate from the inside in the first place.
…Enterprises that have been successful in mitigating threats have acknowledged that security professionals cannot be expected to do all the heavy lifting. It is impossible to manually track and secure every part of an organisation’s network. Hence, they have turned to unsupervised machine-learning technology that mirrors the mechanism of the human immune system, allowing them to eliminate more than 18,000 serious early-stage threats globally in the past two years.
Aurora addresses two types of threats that we must identify with cyber security immune system: trust attacks and insider threats:
Today’s most savvy attackers are moving away from pure data theft or website hacking, to attacks that have a more subtle target — data integrity….attackers will use their ability to hack information systems not to just make a quick buck, but to cause long-term, reputational damage to individuals or groups by eroding trust in data itself.
Let’s not forgot the potential impact of these “Trust Attacks”:
The scenario is worrying for industries that rely heavily on public confidence. A laboratory that cannot vouch for the fidelity of medical test results, or a bank that has had account balances tampered with, are examples of organisations at risk. Governments may also fall foul of such attacks, as critical data repositories are altered and public distrust in national institutions rises. Local firms will not be immune from such attacks, especially as they digitise and consequently become more reliant on online data.
The threats within are:
…often the source of the most dangerous attacks. They are harder to detect, because they use legitimate user credentials. They can do maximum damage, because they have knowledge of and privileged access to the information required for their jobs, and can hop between network segments. A disgruntled employee looking to do damage stands a good chance through a cyber attack.
But insider threats are not just staff with chips on their shoulders. Non-malicious insiders are just as much of a vulnerability as deliberate saboteurs. How many times have links been clicked before checking email addresses? Or security policy contravened to get a job done quicker, such as uploading confidential documents on less secure public file hosting services?
The Takeaways from Aurora are:
- Gain more visibility into internal systems instead of reinforce the network perimeter (i.e., skin)
- Acknowledge that you are going to have a harder time distinguishing between insiders and external attackers who have hijacked legitimate user credentials
- Have an answer to the following question: How do you stop an attacker already inside your network, before it escalates into a crisis?
- Begin researching and investing in technology that leverages unsupervised machine-learning.
