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Exploiting AI: How Cybercriminals Misuse and Abuse AI and ML

#artificialintelligence

Artificial intelligence (AI) is swiftly fueling the development of a more dynamic world. AI, a subfield of computer science that is interconnected with other disciplines, promises greater efficiency and higher levels of automation and autonomy. Simply put, it is a dual-use technology at the heart of the fourth industrial revolution. Together with machine learning (ML) -- a subfield of AI that analyzes large volumes of data to find patterns via algorithms -- enterprises, organizations, and governments are able to perform impressive feats that ultimately drive innovation and better business. The use of both AI and ML in business is rampant.


Applications of Differential Privacy to European Privacy Law (GDPR) and Machine Learning

#artificialintelligence

Differential privacy is a data anonymization technique that's used by major technology companies such as Apple and Google. The goal of differential privacy is simple: allow data analysts to build accurate models without sacrificing the privacy of the individual data points. But what does "sacrificing the privacy of the data points" mean? Well, let's think about an example. Suppose I have a dataset that contains information (age, gender, treatment, marriage status, other medical conditions, etc.) about every person who was treated for breast cancer at Hospital X.


AI could be the next big defence against cybercrime

#artificialintelligence

The future of corporate cybersecurity seems to lie in artificial intelligence (AI) and machine learning (ML) solutions, a new report from global IT company Wipro suggests. According to Wipro's annual State of Cybersecurity Report (SOCR), almost half (49 percent) of all cybersecurity-related patents filed in the last four years have centered on AI and ML application. Almost half of the 200 organizations that participated in the report also said they are expanding cognitive detection capabilities to tackle unknown attacks in their Security Operations Centers (SOC). From a global perspective, one of the main threats for organizations in the private sector seems to be potential espionage attacks from nation-states. Almost all (86 percent) cyberattacks that came from state-sponsored actors fall under the espionage category and almost half (46 percent) of those attacks targeted the private sector.


KRAFTON, Inc. Announces Global Collaboration With Microsoft Azure

#artificialintelligence

KRAFTON, Inc. announced it is working with Microsoft Azure to host its portfolio of multiplatform products. The deal will include products directly operated by the company and its subsidiaries, including PUBG Corporation's multiplayer battle royale PLAYERUNKNOWN'S BATTLEGROUNDS (PUBG) on PC and consoles, in addition to PUBG MOBILE. Azure is Microsoft's public cloud computing service empowering game creators to build, run, and grow their games on a global scale. With privacy and data security being a top priority for KRAFTON, the company will be working with Microsoft to ensure personal data protection through Azure. The collaboration will ensure that privacy rights are respected and relevant software will be in full compliance with all applicable laws and regulations.


6 Privacy Solutions for Big Data and Machine Learning

#artificialintelligence

Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Halong Bay, then head up to the highlands of Sapa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vien while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.


How Security Systems are Implementing AI and ML for Threat Detection

#artificialintelligence

A recent study showed that over 90% of security operating centres are now implementing or considering the use of AI and machine learning to detect and defend against digital threats. What is the traditional method for threat detection, what has AI and ML allowed, and how is the hardware world reacting to threats? Since their introduction, computers have played a key role in modern life, providing services such as internet access, online banking, message exchange, and remote work. However, the transmission of sensitive information along with the processing capabilities of any single computer has also resulted in the development of malware by cybercriminals. These programs fall under several categories, including viruses, trojans, and worms, all of which perform different tasks. Of these, their exact function can be separated further; some malware works to destroy a system while others may steal sensitive information.


6 Privacy Solutions for Big Data and Machine Learning

#artificialintelligence

Travelers who wander the banana pancake trail through Southeast Asia will all get roughly the same experience. They'll eat crummy food on one of fifty boats floating around Ha Long Bay, then head up to the highlands of Sa Pa for a faux cultural experience with hill tribes that grow dreadful cannabis. After that, it's on to Laos to float the river in Vang Vieng while smashed on opium tea. Eventually, you'll see someone wearing a t-shirt with the classic slogan – "same same, but different." The origins of this phrase surround the Southeast Asian vendors who often respond to queries about the authenticity of fake goods they're selling with "same same, but different." It's a phrase that appropriately describes how the technology world loves to spin things as fresh and new when they've hardly changed at all.


How Might Artificial Intelligence Applications Impact Risk Management?

#artificialintelligence

Artificial intelligence (AI) applications have attracted considerable ethical attention for good reasons. Although AI models might advance human welfare in unprecedented ways, progress will not occur without substantial risks. This article considers 3 such risks: system malfunctions, privacy protections, and consent to data repurposing. To meet these challenges, traditional risk managers will likely need to collaborate intensively with computer scientists, bioinformaticists, information technologists, and data privacy and security experts. This essay will speculate on the degree to which these AI risks might be embraced or dismissed by risk management.


Does Palantir See Too Much?

#artificialintelligence

On a bright Tuesday afternoon in Paris last fall, Alex Karp was doing tai chi in the Luxembourg Gardens. He wore blue Nike sweatpants, a blue polo shirt, orange socks, charcoal-gray sneakers and white-framed sunglasses with red accents that inevitably drew attention to his most distinctive feature, a tangle of salt-and-pepper hair rising skyward from his head. Under a canopy of chestnut trees, Karp executed a series of elegant tai chi and qigong moves, shifting the pebbles and dirt gently under his feet as he twisted and turned. A group of teenagers watched in amusement. After 10 minutes or so, Karp walked to a nearby bench, where one of his bodyguards had placed a cooler and what looked like an instrument case. The cooler held several bottles of the nonalcoholic German beer that Karp drinks (he would crack one open on the way out of the park). The case contained a wooden sword, which he needed for the next part of his routine. "I brought a real sword the last time I was here, but the police stopped me," he said matter of factly as he began slashing the air with the sword. Those gendarmes evidently didn't know that Karp, far from being a public menace, was the chief executive of an American company whose software has been deployed on behalf of public safety in France. The company, Palantir Technologies, is named after the seeing stones in J.R.R. Tolkien's "The Lord of the Rings." Its two primary software programs, Gotham and Foundry, gather and process vast quantities of data in order to identify connections, patterns and trends that might elude human analysts. The stated goal of all this "data integration" is to help organizations make better decisions, and many of Palantir's customers consider its technology to be transformative. Karp claims a loftier ambition, however. "We built our company to support the West," he says. To that end, Palantir says it does not do business in countries that it considers adversarial to the U.S. and its allies, namely China and Russia. In the company's early days, Palantir employees, invoking Tolkien, described their mission as "saving the shire." The brainchild of Karp's friend and law-school classmate Peter Thiel, Palantir was founded in 2003. It was seeded in part by In-Q-Tel, the C.I.A.'s venture-capital arm, and the C.I.A. remains a client. Palantir's technology is rumored to have been used to track down Osama bin Laden -- a claim that has never been verified but one that has conferred an enduring mystique on the company. These days, Palantir is used for counterterrorism by a number of Western governments.


Using Data and Respecting Users

Communications of the ACM

Transaction data is like a friendship tie: both parties must respect the relationship and if one party exploits it the relationship sours. As data becomes increasingly valuable, firms must take care not to exploit their users or they will sour their ties. Ethical uses of data cover a spectrum: at one end, using patient data in healthcare to cure patients is little cause for concern. At the other end, selling data to third parties who exploit users is serious cause for concern.2 Between these two extremes lies a vast gray area where firms need better ways to frame data risks and rewards in order to make better legal and ethical choices.