Artificial intelligence solutions are now essential weapons in the insurers' battle against fraud. FREMONT, CA: The insurance industry is held responsible for a mass of sensitive data concerning both its customers and employees. Any data breach in an insurance firm could compromise the personal information of multiple users in no time. But insurers now have the option of attaining better cybersecurity posture by utilizing groundbreaking technologies available to them. Artificial Intelligence (AI) among those, is truly reforming insurance systems by making it more secure and enhancing the interaction between humans and machines.
This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Cybersecurity, a huge industry worth over $100 billion, is regularly subject to buzzwords. Cybersecurity companies often (pretend) to use new state-of-the-art technologies to attract customers and sell their solutions. Naturally, with artificial intelligence being in one of its craziest hype cycles, we're seeing plenty of solutions that claim to use machine learning, deep learning and other AI-related technologies to automatically secure the networks and digital assets of their clients. But contrary to what many companies profess, machine learning is not a silver bullet that will automatically protect individuals and organizations against security threats, says Ilia Kolochenko, CEO of ImmuniWeb, a company that uses AI to test the security of web and mobile applications.
Just the way the deficiency of vitamin and poor hygiene can make the human body fell seriously ill, the deficient access points and lack of hygiene in cyber environments can lead to cyberattacks in the hyper-connected workplaces. The likelihood of cyberattacks is increasing with continuous ballooning of the data feeding into the network. It's a sign, the organizations are living in the fear of becoming a victim of the cyberattacks and willing to spend big bundles on cybersecurity tools and services. According to IDC research, "The organizations will spend $101.6 billion on cybersecurity software, services, and hardware by 2020." The leading organizations are integrating the tens of security products in the environment, but yet, they afraid of being exposed and vulnerable.
Scalable cognitive solutions that meet these objectives must leverage machine learning to manage the vast amount of data that is produced by security sensors. Security expertise, data science and the math behind machine learning are all essential to developing the complex mechanisms, timing and features of machine learning systems. Thus, taking the right action by creating security tactics enabled by machine learning is dependent on three things: resources, confidence in the science, and actionability. In this paper, Jon Ramsey, Secureworks CTO, provides his vision of Machine Learning and how these three things above can enable "Smart Security" to benefit CIOs and businesses.
High-profile data breaches of enterprise companies and large government agencies gain a lot of news coverage. But does the lack of reporting involving small and medium-sized businesses mean that, for them, the cybersecurity risk is much smaller? SMBs have information and credentials that are indeed valuable for cybercriminals, including: employee and customer records, access to business financial information including bank accounts, and access to larger companies and their networks through the supply chain.
Artificial intelligence has come to change the way we do things and can help us solve many problems in different areas. A major problem we currently face are threats to cybersecurity. Especially now that we live in a world that is permanently connected to the internet, it is more important than ever to make systems secure. Organizations are now expected to increase the use of cryptography to improve cybersecurity. However, to keep up with this process, they will need to incorporate advanced tools, like artificial intelligence (AI), to prevent, detect and remedy potential threats.
In recent years, deep learning and machine learning have gained traction in so many areas that have a direct positive effect on our lives as well as complex tasks such as computer vision (image recognition), machine translation, and natural language processing. And with like so many other technologies that are changing our lives for good, it has the destructive potential to change it for bad, there is no reason why it won't also be used for malicious activities as well. Up until now, we haven't seen the use of AI for malicious activities in cybersecurity due to the high costs, lack of skills and the tools available. But just like any other technology, it's a matter of time before it happens in cybersecurity. Think about what would happen when attackers start using the power of deep learning and machine learning for their advantage?
TAIWAN-BASED technology firm CyCraft, which provides artificial intelligence (AI) solutions to enhance cybersecurity of businesses, on Friday announced a US$5.65 million fundraise in a Series B round. In total, CyCraft's total funding now amounts to US$8.15 million. Backers of this investment include Singapore-based investment company Pavilion Capital, and CID Group, an investment company based in Taiwan. Funds raised will propel the startup's research efforts in enhancing its AI technology and support market expansion in Asia. The firm has also formally launched SecOps Platform, an AI-driven platform which offers three variations of automated cybersecurity solutions.
Despite advancing threats from hackers and nation states, human error remains the top cybersecurity concern for both C-suite executives and policymakers, according to a Wednesday report from Oracle. To combat this issue, professionals must invest more in employees--via training and hiring--than in technologies in the coming two years, the report found. Only 38% of C-suite executives said they plan to invest in artificial intelligence (AI) and machine learning to improve security in the next two years, though these technologies can aid in minimizing human error, the report said. In terms of other security investments over that time frame, 44% of C-suite executives said they plan to purchase new software with improved security, and 37% said they plan to invest in new infrastructure solutions, according to the report. In the last five years, C-suite executives said they have upgraded existing software (60%), trained existing staff (57%), purchased new software with enhanced security features (54%), and invested in new infrastructure solutions (40%) to improve security, the report found.
The media makes sensationalist claims about AI, but let's take a closer look at the facts: AI is not a trend! Cisco has been doing it for years to help businesses across the globe quickly and easily identify banking trojans, botnets, phishing and ransomware. A taxonomy of AI algorithms used in cyber threat detection What AI can and can't do for your organisation How to leverage AI as a preventative measure to help detect & uncover threats before they hit your business Best practices on how to incorporate AI into your threat detection and defence systems What AI can and can't do for your organisation During this webinar, we'll go beyond the hype and show you real-world examples of AI algorithms that helps us keep our customers safe on the internet, anywhere their users go. See how Cisco Umbrella uses AI to effectively detect current and emerging threats.