Set the buzz factor aside for a minute, and understand that artificial intelligence is doing real work for real companies. Even in the early stages of implementation, AI is providing enterprise organizations with benefits: Efficiency in operations, cybersecurity protections, innovation, and stronger customer relationships. However, the race to implement AI and machine learning also raises citizen privacy concerns. There have been revelations about the potential for algorithmic bias reflected in data sources. There has been speculation about AI applications going rogue.
Researchers simulated a real-looking "Industrial prototyping" organization with fake employees, PLCs, and websites to study the types of cyber-attacks that commonly on such networks. The elaborately fake organization's website and the network worked on a highly advanced interactive "honeypot" network that worked extensively on attracting the attention of potential hackers. The plan was to create such a legitimate-looking network that no one could even doubt it's being phony and to accumulate serious information related to cyber-threats and attacks to study and analyze them. Behind researching these threats and attack mechanisms the motive was to dig out the threats that the "Industrial control system" (ICS) sector faces today. Per sources, the sham company specifically let some ports of its network be susceptible to attack and Voila!
"We are already at the point where you can't tell the difference between deepfakes and the real thing," Professor Hao Li of the University of Southern California tells the BBC. We are at the computer scientist's deepfake installation at the World Economic Forum in Davos which gives a hint of what he means. Like other deepfake tools, his software creates computer-manipulated videos of people - often politicians or celebrities - that are designed to look real. Most often this involves "face swapping", whereby the face of a celebrity is overlaid onto the likeness of someone else. As I sit, a camera films my face and projects it onto a screen in front of me; my features are then digitally mapped.
In order to advance cybersecurity awareness and effectiveness around the globe the FICO Cyber Risk Score is now available, free of charge, to all organizations. It is designed to provide Chief Risk Officers an independent perspective of data breach risk while utilizing the same machine learning models used by vendor managers and cyber insurance underwriters to quantify 3rd party risk exposure. This complimentary subscription to the Portrait portal of the FICO Enterprise Security Suite includes immediate, self-service curation of organizations' Internet-facing assets in order to ensure fair and accurate security ratings as defined by the U.S. Chamber of Commerce. These Principles for Fair and Accurate Security Ratings promote accuracy, fairness, utility, and transparency in the provision of cyber risk scores and security ratings. FICO supports these Principles through its adherence to empirical cyber risk scoring, prudent disclosure of contributing risk factors, sound model governance practices, and the enablement of direct client involvement in the resolution of data and definitional issues.
Privacy cannot be a "luxury good" in 2020, the CEO of Google warned on Wednesday, as he pointed to the European Union's GDPR regulation as a template for other similar privacy laws around the world. Sundar Pichai said that he believed that the tech giant's products should be "privacy-enhancing," noting that Google was increasingly giving users control and choice around privacy decisions. "For us, privacy is at the heart of what we do. Users come to Google at very important moments, ask us questions. We deal with people's sensitive information in Gmail, Google Photos, and so on. And so we have to earn that trust," he said.
In the past few years, there's been a lot of buzz around artificial intelligence (AI) in cybersecurity. Can AI really help businesses improve their security posture? How can we determine which solutions actually use AI versus which ones make hyped-up claims? For solutions that can help, how do they help? Obtaining clarity around this subject will help us understand the areas in which AI can help and what value it can add, which will, in turn, help us make more informed decisions.
The global deep learning market is expected to grow at a CAGR of 51.1% from forecast period 2019 to 2026 and expected to reach the value of around US$ 56,427.2 Deep learning is a subdivision of machine learning in artificial intelligence (AI) concerned with the algorithm inspired by the functioning of human brain termed as artificial neural networks. It is also termed as deep neural learning or deep neural network. Deep learning is evolved with the increasing amount of unstructured data due to digitalization. The available amount of data is utilized in deep learning to process or understand that data for effective decision making in various industry verticals including healthcare, manufacturing, automotive, agriculture, retail, security, human resources, marketing, law, and fintech.
After a draft white paper about the EU's position on AI regulation was leaked earlier this month, Google chief Sundar Pichai, on Monday (20 January), warned the bloc about imposing its own regulations and called for an "international alignment" on the core values of the future laws of the sector. However, ahead of what is expected to be the fourth industrial revolution, the European Commission wants to ensure an "appropriate" ethical and legal framework for the development of AI, which promises to boost innovation while making EU citizens' rights a priority. In November, commission chief Ursula von der Leyen pledged to develop AI legislation similar to the General Data Protection Regulation (GDPR), an EU law on privacy. "It is not about damming up the flow of data, it is about making rules that define how to handle data responsibly," she told MEPs back then. "For us, the protection of a person's digital identity is the overriding priority," she added.
Cybercriminals are always evolving their efforts and coming up with more advanced ways to target their victims. And while there are many tools available to stop them, there is a lot of space for improvement. Especially if you take automation into account. Machine learning and artificial intelligence are playing a significant role in cybersecurity. Automation tools can prevent, detect, and deal with tons of cyber threats way more efficiently and faster than humans.