Tag: ARTICLE
IntroductionTrustworthy vs Responsible AITrustworthy AIAttributes of trustworthy AI1. Transparent, interpretable and explainable2. Accountable3. Reliable, resilient, safe and secure4. Fair and non-discriminatory5. Committed to privacy...
The automotive industry has revolutionized manufacturing twice.
The first time was in 1913 when Henry Ford introduced a moving assembly line at his Highland Park...
Our physical world is becoming more connected – which makes it more dependent on the cyber world. Many physical objects around us are no...
The rapid development of AI brings both extraordinary potential and unprecedented risks. AI systems are increasingly demonstrating emergent behaviors, and in some cases, are...
In the U.S. alone, SIM-swapping attacks resulted in $72 million worth of losses last year, four-million dollars more than 2021, according to the Federal...
Verified crypto-exchange accounts have become a hot commodity on the dark web, with login credentials available for as little as $20, according to May...
It seems everyone is talking about artificial intelligence (AI). Everyone. From senior executives to school kids, the hype - or dread - around this...
Annualized data from blockchain forensics provider Chainalysis indicates that crypto-enabled crime has dropped precipitously through the first half of 2023, but cybercriminals are also...
Last week, the Saudi Data and Artificial Intelligence Authority (SDAIA) launched a nationwide awareness campaign called “Ask Before”, intended to educate the public about the significance...
Artificial Intelligence (AI) is no longer just a buzzword; it’s an integral part of our daily lives, powering everything from our search for a...
With AI’s breakneck expansion, the distinctions between ‘cybersecurity’ and ‘AI security’ are becoming increasingly pronounced. While both disciplines aim to safeguard digital assets, their focus and the challenges they address diverge in significant ways. Traditional cybersecurity is primarily about defending digital infrastructures from external threats, breaches, and unauthorized access. On the other hand, AI security has to address unique challenges posed by artificial intelligence systems, ensuring not just their robustness but also their ethical and transparent operation as well as unique internal vulnerabilities intrinsic to AI models and algorithms.
Neural networks learn from data. They are trained on large datasets to recognize patterns or make decisions. A Trojan attack in a neural network typically involves injecting malicious data into this training dataset. This 'poisoned' data is crafted in such a way that the neural network begins to associate it with a certain output, creating a hidden vulnerability. When activated, this vulnerability can cause the neural network to behave unpredictably or make incorrect decisions, often without any noticeable signs of tampering.
Ask most people what they remember from 2016 - if they remember anything at all - and there are usually two big events that...
Homo sapiens is an incredibly adaptable species, arguably the most adaptable ever. But it is also a forgetful one, quick to take things for...
Model fragmentation is the phenomenon where a single machine-learning model is not used uniformly across all instances, platforms, or applications. Instead, different versions, configurations, or subsets of the model are deployed based on specific needs, constraints, or local optimizations. This can result in multiple fragmented instances of the original model operating in parallel, each potentially having different performance characteristics, data sensitivities, and security vulnerabilities.