정보 보안 분석가

Arjun Mepa (적당한)이 말합니다.

The main reason for a SOC analyst or information security analyst role will be automated is because of alert fatigue. The current model responding doesn't work anymore especially when you have thousands of alerts to deal with. No one has the time threat detection rules to for each event or a malicious event. ML will either aim to replace or optimize this.

Meh이 말합니다.

Once "ai" models are implemented with a dash of agency/cognitive architecture to find novel vulnerabilities and models are implemented to fix those vulnerabilities in tandem, finding exploitable bugs will become increasingly difficult with little ROI for the pentesters, hunters, whatever.

It'll be a race between red and blue team businesses to implement increasingly better models. Social engineering sure, but meh honestly. Will you be able to find incredibly difficult scraps or oversights the model missed? Will it be worth the risk and investment of the pentester? Overall bleak outlook.

Old Spice (기회 없음)이 말합니다.

You can't trust AI to protect your networks, it will probably be able to get manipulated by hackers in the future.

Anon이 말합니다.

In the Cyber Threat Intelligence circles automation is already occuring. My job is being replaced by automated scripts that create and generate documentation and use APIs to scrape the data. most of it will be junk and not targeted the same way as a human but hey that's what the company is doing oh and they are asking me to work with the programmer who is literally making me firable. So angry. Would avoid this role if possible.

Jack (낮은)이 말합니다.

Social engineering risks are highly unlikely to be detected by AI.

James (낮은)이 말합니다.

Unlikely. Security analysis often have to think outside the box to find novel vulnerabilities.

Richard P (적당한)이 말합니다.

Could be disrupted by Quantum computers

FD이 말합니다.

New regulations will force the software developing companies to create less vulnerabilities in products (at the source.) Hardware vendors will similarly have to sell networked devices with secure settings programmed in by default.

This will increase the ability of automated systems to detect any remaining vulnerabilities, but will not completely remove the need for technicians to maintain, remediate, and upgrade the systems. There will still be a need to touch the hardware. Depending on individual situation, some companies will use more of AI tech than the others. We can already see something similar in the engineering, accounting, and law practice, where paralegals and drafters have not been completely replaced by software. Sole practitioners might use automation more extensively than the large corporations, but there will be a legal requirement for a human audit.

In addition, location-independent digital nomads who train themselves to use the automation tools could do a lot of accurate work in a short amount of time, as independent consultants and freelancers, and do business with multiple clients.

Making the choice to transition from repetitive and tedious manual work to automation, will be akin to transitioning from flintstones to nuclear power. Nuclear power still needs humans, and so will information security solutions.

Fakiha (낮은)이 말합니다.

I believe that is is less likely because mostly automatically finding vulnerabilities may be performed by AI but it will be the security analyst to enable computer do it, help it learn by giving feedback, as the result may not always be right. AI will help make task easier and fast for security analyst

Michael (낮은)이 말합니다.

there are some areas such as malware detection and IPS , IDS that will be fully automated , but others like policy and social engineering are very hard to .

frankie (매우 가능성이 높음)이 말합니다.

Automated penetration testing