Emerging Tech Security
AI security, cyber-kinetic security, 5G and mIoT security, blockchain and crypto security, and emerging technology risk domains adjacent to quantum.
-
5G Security
Is 5G security being sacrificed at the altar of profit, politics and process?
Homo sapiens is an incredibly adaptable species, arguably the most adaptable ever. But it is also a forgetful one, quick to take things for granted. Many of us can remember when cell phones first emerged, when the internet first became…
Read More » -
AI Security
Model Fragmentation and What it Means for Security
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…
Read More » -
AI Security
Outsmarting AI with Model Evasion
Model Evasion in the context of machine learning for cybersecurity refers to the tactical manipulation of input data, algorithmic processes, or outputs to mislead or subvert the intended operations of a machine learning model. In mathematical terms, evasion can be…
Read More » -
AI Security
AI and Canada: Pioneering Innovation, Searching for Homegrown Success
It’s easy to forget, amid the hype around Silicon Valley’s AI giants, that many of the foundational breakthroughs of modern AI were born in Canada. In fact, two of the three “godfathers of AI” - Yoshua Bengio and Geoffrey Hinton…
Read More » -
AI Security
Securing Machine Learning Workflows through Homomorphic Encryption
Homomorphic Encryption has transitioned from being a mathematical curiosity to a linchpin in fortifying machine learning workflows against data vulnerabilities. Its complex nature notwithstanding, the unparalleled privacy and security benefits it offers are compelling enough to warrant its growing ubiquity.…
Read More » -
Post-Quantum, PQC, Quantum Security
Quantum Readiness for Mission-Critical Communications (MCC)
Mission-critical communications (MCC) networks are the specialized communication systems used by “blue light” emergency and disaster response services (police, fire, EMS), military units, utilities, and other critical operators to relay vital information when lives or infrastructure are at stake. These…
Read More » -
AI Security
Understanding Data Poisoning: How It Compromises Machine Learning Models
Data poisoning is a targeted form of attack wherein an adversary deliberately manipulates the training data to compromise the efficacy of machine learning models. The training phase of a machine learning model is particularly vulnerable to this type of attack…
Read More » -
AI Security
Semantic Adversarial Attacks: When Meaning Gets Twisted
Semantic adversarial attacks represent a specialized form of adversarial manipulation where the attacker focuses not on random or arbitrary alterations to the data but specifically on twisting the semantic meaning or context behind it. Unlike traditional adversarial attacks that often…
Read More » -
AI Security
The AI Alignment Problem
The AI alignment problem sits at the core of all future predictions of AI’s safety. It describes the complex challenge of ensuring AI systems act in ways that are beneficial and not harmful to humans, aligning AI goals and decision-making…
Read More » -
AI Security
A (Very) Brief History of AI
As early as the mid-19th century, Charles Babbage and Ada Lovelace created the Analytical Engine, a mechanical general-purpose computer. Lovelace is often credited with the idea of a machine that could manipulate symbols in accordance with rules and that it…
Read More » -
AI Security
Understanding and Addressing Biases in Machine Learning
While ML offers extensive benefits, it also presents significant challenges, among them, one of the most prominent ones is biases in ML models. Bias in ML refers to systematic errors or influences in a model's predictions that lead to unequal…
Read More » -
AI Security
Adversarial Attacks: The Hidden Risk in AI Security
Adversarial attacks specifically target the vulnerabilities in AI and ML systems. At a high level, these attacks involve inputting carefully crafted data into an AI system to trick it into making an incorrect decision or classification. For instance, an adversarial…
Read More » -
AI Security
Gradient-Based Attacks: A Dive into Optimization Exploits
Gradient-based attacks refer to a suite of methods employed by adversaries to exploit the vulnerabilities inherent in ML models, focusing particularly on the optimization processes these models utilize to learn and make predictions. These attacks are called “gradient-based” because they…
Read More » -
Crypto Security
How Blockchain Security Differs From Traditional Cybersecurity – 4 – Security Operations (SOC)
This article concludes our four-part series on the basic differences between traditional IT security and blockchain security. Previous articles discussed the security differences critical for node operators, smart contract developers, and end users. In many ways, Security Operations Center (SOC)…
Read More » -
AI Security
Introduction to AI-Enabled Disinformation
In recent years, the rise of artificial intelligence (AI) has revolutionized many sectors, bringing about significant advancements in various fields. However, one area where AI has presented a dual-edged sword is in information operations, specifically in the propagation of disinformation.…
Read More »
