Criminals are using AI-generated audio to impersonate a CEO's voice and con subordinates into transferring funds to a scammer's account. However, the UK CEO was in fact taking instructions from a scammer who'd used AI-powered voice technology to impersonate the German CEO. Our FREE Tools can help! How will you protect yourself from this?
The world is going digital at an unprecedentedly fast pace, and the change is only going to go even faster. The digitalization means everything is moving at lightning speed – business, entertainment, trends, new products, etc. The consumer gets what he or she wants instantly because the service provider has the means to deliver it. Click here to view original webpage at www.entrepreneur.com
Why has machine learning become so critical to cybersecurity? With machine learning, cybersecurity systems can analyze patterns and learn from them to help prevent similar attacks and respond to changing behavior. Machine learning helps cybersecurity teams be more pro-active in preventing threats and responding to active attacks in real time. Machine learning can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, machine learning can make cybersecurity simpler, more proactive, less expensive and far more effective.
As the US launches a cyberattack against Iranian weapons systems and escalates their infiltration of the Russian power grid in the same month, it's clear a new chapter of warfare is well and truly underway. Fueled by the same complex mix of diplomatic breakdowns, economic sanctions and historical grievances as regular conflicts, cyberwarfare is the new threat facing developing nations. The crisis faced by every technologically advanced state is highlighted in the World Economic Forum's Global Risks Report 2019 which ranked cyberattacks as the 5th global risk of our time. The US is certainly not alone in developing a cyberwarfare arsenal, as preemptive strikes, espionage and counter-attacks all require nations to develop cybersecurity defenses and demonstrate their clout. Here, we know exactly what the digital battleground looks like, and the attempts nations can take to develop defenses against the latest cyberwarfare threats.
The world is going digital at an unprecedentedly fast pace, and the change is only going to go even faster. The digitalization means everything is moving at lightning speed – business, entertainment, trends, new products, etc. The consumer gets what he or she wants instantly because the service provider has the means to deliver it. While the conveniences and benefits of this digital era are many, it also brings with it several negatives. One of the most significant and destructive threats it poses is that our private information is at risk like never before.
Malware analysts routinely use the Strings program during static analysis in order to inspect a binary's printable characters. However, identifying relevant strings by hand is time consuming and prone to human error. Larger binaries produce upwards of thousands of strings that can quickly evoke analyst fatigue, relevant strings occur less often than irrelevant ones, and the definition of "relevant" can vary significantly among analysts. Mistakes can lead to missed clues that would have reduced overall time spent performing malware analysis, or even worse, incomplete or incorrect investigatory conclusions. Earlier this year, the FireEye Data Science (FDS) and FireEye Labs Reverse Engineering (FLARE) teams published a blog post describing a machine learning model that automatically ranked strings to address these concerns.
Infosec techies should prepare to both fend off AI attacks and welcome the technology into their armoury of tools, reckons Trend Micro's director of cybercrime research. The security world is standing on the brink of an AI-powered arms race, claimed Rob McArdle at the firm's Cloudsec conference in London today. Speaking on stage alongside Rik Ferguson, Trend's refreshingly British research veep, McArdle warned that "deepfake ransomware" was one potential attack vector of the near future. Describing the technique, McArdle said an attacker could use deepfake tech to create a video with blackmail potential: the obvious use case is something involving nudity, or perhaps someone making outrageous statements. The attacker could then upload that video somewhere and send the mark a private link along with threats to publish the video widely unless large sums of money were paid immediately.
Book a suite in a luxury hotel in Moscow, send the room number encrypted to a pre-determined mobile number and then wait for a return message indicating a precise time: Meeting Edward Snwoden is pretty much exactly how children imagine the grand game of espionage is played. But then, on Monday, there he was, standing in our room on the first floor of the Hotel Metropol, as pale and boyish-looking as the was when the world first saw him in June 2013. For the last six years, he has been living in Russian exile. The U.S. has considered him to be an enemy of the state, right up there with Julian Assange, ever since he revealed, with the help of journalists, the full scope of the surveillance system operated by the National Security Agency (NSA). For quite some time, though, he remained silent about how he smuggled the secrets out of the country and what his personal motivations were. Now, though, he has written a book about it. It will be published worldwide on September 17 under the title "Permanent Record." Ahead of publication, Snowden spent over two-and-a-half hours patiently responding to questions from DER SPIEGEL. DER SPIEGEL: Mr. Snowden, you always said: "I am not the story."
In December 2018, a man driving an authorized Uber vehicle picked up an intoxicated woman leaving a Christmas party -- and then brought her to his home and raped her. But the man, who The Age reports was sentenced to five and a half years in prison on Wednesday, was not an authorized Uber driver. Rather, he was able to easily fool Uber's verification system by holding up a photo of a real driver. In other words, the AI technology that Uber uses to verify that its drivers are who they claim to be -- like Amazon delivery drivers, Uber contractors take a selfie when signing on -- wasn't sophisticated enough to spot a printed headshot. It's a horrifying story that illustrates the perils of big tech offloading security to dodgy AI systems.