How AI, ML, and automation can improve cybersecurity protection | 7wData

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How AI, ML, and automation can improve cybersecurity protection
Traditional cybersecurity tools such as mere anti- malware software or login audits aren't going to be sufficient in 2020--additional resources will be needed to protect organizations and their employees from cyberthreats. Artificial intelligence (AI) and machine learning (ML) are making productive inroads in the cybersecurity space.
I spoke with Anish Joshi, vice president  of technology at AI solutions provider Fusemachines, and Greg Martin, general manager of the Security Business Unit at Sumo Logic , a machine data analytics organization to get their input on the topic. The interviews have been lightly edited.
Scott Matteson: What are the common pain points with cybersecurity?
Anish Joshi: Security risks in applications are ever growing in number as well as complexity. With the advent of technology like web, mobile, and even the Internet of Things (loT), applications have pervaded personal and professional lives as they use tech for a variety of different purposes, potentially increasing its footprint for damage. There is probably no organization that doesn't have its own application. However, the number of applications that are vulnerable to threats has catapulted due to problems like a shortage in skilled technical manpower, whose expertise is necessary to build and protect such software. There is also a tendency to cut down application development costs through outsourcing , leading to the creation of software of low quality.
An even more dreadful fact is that application security and privacy is being overlooked by startups that lack the resources to address such concerns and are often bogged down by fierce competition in a cutthroat environment.
It all boils down to there being no in-depth cybersecurity strategy. Cybersecurity management becomes a very cumbersome and demanding task as technology pervades into every part of business. A lot of companies suffer from a lack of a reliable and systematic risk-based security strategy. Many also lack an application security program, with the exception of a few who have an updated backlog of their applications, processed data, and implemented security controls. It seems improbable to secure these applications without any proper knowledge.
Greg Martin: Attackers have learned to largely automate their attacks, increasing the frequency of attacks by an order of magnitude. Because of this, alert fatigue, false positive alerts, and the sheer volume of attacks and the amount of raw data available to analyze makes reacting accordingly a near-impossible task for humans. This is all magnified by the widely recognized skills gap/talent shortage in cybersecurity.
Scott Matteson: What are the most prevalent risks?
Anish Joshi: The most prevalent risk is the stealing of private and confidential information through phishing emails. When phishing emails are opened by employees of a company, this can cause malware to infiltrate the company's computer system, eventually causing it to lose a lot of money, trade secrets, as well as its name and reputation.
This does not just affect companies as a whole but also individuals, as their privacy is violated, and their information can be used to commit fraud. One example would be stealing money from their bank account.
Greg Martin: The sophistication of attacks advances daily, and we are seeing a notable rise in fileless attacks, which is increasingly enabling attackers to "live off the land," meaning they are leveraging existing scripting capabilities like PowerShell and existing network management tools to propagate and laterally move within enterprise networks.
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