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I agree with your first statement, "humans will always be the easiest attack vector for hackers". But I have increasingly come to realize that your second statement, "we need to continue training users", is not the logical conclusion.
This may seem paradoxical at first: if humans are the weak link, why not train them? But as attacks become more and more sophisticated, the sheer effort of training will become unbearable -- and start paying off less and less. Similarly, as the number of versions of the attacks we see mushroom, it will be harder for regular mortals to keep things straight. And this is what is happening.
So what can we do to deal with the fact that humans are, and will remain, the easiest attack vector? We need software that reflects the perspective of the human victims. What makes people fall for attacks? If we can create filters that identifies what is deceptive -- to people -- then we hare addresssing the problem.
Am I talking about artificial intelligence? Not necessarily. This can be solved using expert system, machine learning, and combinations thereof. What I am really talking about is software that interprets things like people do, and then filters out what is risky. Can we call this "artificial empathy"?
I agree with your first statement, "humans will always be the easiest attack vector for hackers". But I have increasingly come to realize that your second statement, "we need to continue training users", is not the logical conclusion.
This may seem paradoxical at first: if humans are the weak link, why not train them? But as attacks become more and more sophisticated, the sheer effort of training will become unbearable -- and start paying off less and less. Similarly, as the number of versions of the attacks we see mushroom, it will be harder for regular mortals to keep things straight. And this is what is happening.
So what can we do to deal with the fact that humans are, and will remain, the easiest attack vector? We need software that reflects the perspective of the human victims. What makes people fall for attacks? If we can create filters that identifies what is deceptive -- to people -- then we hare addresssing the problem.
Am I talking about artificial intelligence? Not necessarily. This can be solved using expert system, machine learning, and combinations thereof. What I am really talking about is software that interprets things like people do, and then filters out what is risky. Can we call this "artificial empathy"?
Everything You Need to Know About DNS AttacksIt's important to understand DNS, potential attacks against it, and the tools and techniques required to defend DNS infrastructure. This report answers all the questions you were afraid to ask.
Domain Name Service (DNS) is a critical part of any organization's digital infrastructure, but it's also one of the least understood. DNS is designed to be invisible to business professionals, IT stakeholders, and many security professionals, but DNS's threat surface is large and widely targeted.
Attackers are causing a great deal of damage with an array of attacks such as denial of service, DNS cache poisoning, DNS hijackin, DNS tunneling, and DNS dangling. They are using DNS infrastructure to take control of inbound and outbound communications and preventing users from accessing the applications they are looking for. To stop attacks on DNS, security teams need to shore up the organization's security hygiene around DNS infrastructure, implement controls such as DNSSEC, and monitor DNS traffic
Incident Readiness and Building Response Playbook
In this special report, learn the Xs and Os of any good security incident readiness and response playbook.
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User Rank: Ninja
3/29/2017 | 10:02:27 AM