Cyberwarfare


Global Bigdata Conference

#artificialintelligence

Machine learning is critical to the future of cybersecurity and helping security teams overcome the challenges of modern cybersecurity attacks. Indeed, its ability to'outthink' humans can boost return on investment (ROI), drastically improve productivity and minimise resource expenditure. However, machine learning is also not just a'set and forget' solution. In fact, companies need to treat machine like an intern on their first day. Security teams should not assume a machine learning programme can hit the ground running – there needs to be an onboarding process where you check in on the models frequently and spend time getting them started in the right direction.


Algorithmic Warfare AI A Tool For Good and Bad

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With promises of crunching mounds of data into bite-sized nuggets of actionable information, machine learning could be a breakthrough for the intelligence community. However, vulnerabilities within such systems could open them up to cyber attacks. Jason Matheny, director of the Intelligence Advanced Research Projects Activity, said his organization funds research at over 500 universities, colleges, businesses and labs. A third of his portfolio focuses on machine learning, speech recognition and video analytics. "For us, machine learning is an approach to dealing with this deluge of data that the intelligence community is confronted with," he said during a panel discussion at a Defense One event focusing on artificial intelligence.


Why security teams should treat machine learning like a junior employee

#artificialintelligence

Machine learning is critical to the future of cybersecurity and helping security teams overcome the challenges of modern cybersecurity attacks. Indeed, its ability to'outthink' humans can boost return on investment (ROI), drastically improve productivity and minimise resource expenditure. However, machine learning is also not just a'set and forget' solution. In fact, companies need to treat machine like an intern on their first day. Security teams should not assume a machine learning programme can hit the ground running – there needs to be an onboarding process where you check in on the models frequently and spend time getting them started in the right direction.


Seizing the Benefits of AI and IoT Through Data Security

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As Artificial Intelligence (AI) and Internet of Things (IoT) applications are becoming more prominent, businesses must consider how to best process and analyze such data. Think of the countless business efficiencies and consumer-centric conveniences that have been offered up by the connected home or smart city. However, this new era of connectivity has introduced disruption for many businesses. As data becomes an organization's most valuable resource, it becomes a target for criminals around the world. As we become more connected, the threat of data breaches and cyberattacks negates the promise of a smarter and more sustainable working world.


How To Approach AI-Enhanced Cybersecurity

#artificialintelligence

The continual increase in security threats combined with an overwhelming amount of data and false positives is creating major headaches for IT security teams. Additionally, the cybersecurity industry faces a colossal shortage of talent, making it nearly impossible to stay on top of the latest threats. According to data from ESG research, 12 percent of enterprise organizations have already deployed AI-based security analytics extensively, while another 27 percent have deployed AI-based security analytics on a more limited basis. The relationship between AI and Machine Learning (ML) is often poorly articulated. Artificial Intelligence is simply concerned with causing machines to perform tasks characteristic of human intelligence.


From The Olympics To A Unicorn: How 'Cyber Immune System' Darktrace Hit A $1.3BN Valuation

Forbes Technology

Darktrace has become a rarity in the British tech scene: a Unicorn. The cybersecurity company, which provides what it calls a network "immune system" powered by artificial intelligence, hit a $1.25 billion valuation last month, two sources close to the deal told Forbes. The new valuation came after a secondary round of financing in which former investors sold off their stakes. Vitruvian Partners, sources said, is the acquirer of the stock. How did Darktrace find itself at the vaunted Unicorn status?


Role Of Machine Learning And AI In Healthcare Cybersecurity - Forbes Middle East

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Security threats are major concerns to healthcare organizations due to the value and vulnerability of clinical data that is being recorded and distributed. The value of the data comes from the fact that it is historical in nature; it directly affects our ability to safely treat patients, it takes a long time to rebuild, and it contains more than just clinical data, but also a lot of personal, financial, and demographic data, which allows it to be used for wider identity theft. It is persistent, whereas you can change credit cards and their passwords, PINs and account numbers in the event of a breach, you cannot change your mother's maiden name. The vulnerability comes from the fact that there has been a revolution in healthcare with the interconnection of systems, cloud computing, Internet of Health Things (IoHT) and mobile devices and the changes in working practices of clinicians, such as remote monitoring, telemedicine, and working from home. This revolution has not always been matched with the security awareness, policies, practices, and budgets of health care organizations.


Machine Learning: Practical Applications for Cybersecurity

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If you've walked around any security conferences recently, you'll have heard dozens of vendors talking about artificial intelligence (AI) and machine learning. But what do they actually do? Are they really going to usher in a grand age of cybersecurity? And are security analysts about to be collectively out of a job? Recently, Recorded Future co-hosted a webinar with SANS Institute with the goal of helping security conscious organizations understand how machine learning can help them process an almost infinite number of inputs into a small number of actionable outputs.


The Fundamentals of Deep Learning

@machinelearnbot

Advanced computing enables us to make connections like never before. We can teach machines to detect cancer, identify cybersecurity threats before they happen, and optimize business operations – the possibilities are endless. So how can machines continue to learn, without the dedication of abundant resources? Deep learning, a sub-mechanism of machine intelligence (MI), is a computing process that enables machines to find patterns in data. Deep learning sifts through data and makes connections, identifying odd trends that would be unfindable by the human senses.