Networks like those of healthcare infrastructure have been a primary target of cyberattacks for over a decade. From just a single cyberattack, a healthcare facility would expect to see millions of dollars in losses from legal fines, business interruption, and malpractice lawsuits. As more medical devices become interconnected, more cyber vulnerabilities...

Cyber risk has emerged as a significant threat to businesses that have increasingly relied on new and existing information technologies. Across various businesses in different industries and sectors, a distinct pattern of IT network architectures, such as the client-server network architecture, may expose those businesses, which share it, to similar...

The architecture information of a Deep Neural Network (DNN) model is considered a valuable, sensitive piece of property for a company. Knowledge of a DNN’s exact architecture allows any adversary to build a substitute model and use this substitute model to launch devastating adversarial attacks. Side-channel based DNN architecture stealing can...

In the rapidly advancing landscape of deep reinforcement learning (RL), recent studies have highlighted vulnerabilities in control policies learned through deep RL. These vulnerabilities raise concerns surrounding adversarial attacks, especially in risk-sensitive domains such as autonomous driving. In these scenarios, the learned policies become susceptible...

There has been a rise in security breaches over the past few years, prompting an increasing need to mine insights from external discussion and social media platforms to raise alerts of possible attacks that might cater to specific industries. The dark web is one source of information on the internet where users can share information on software vulnerabilities...

­Recently, Deep Neural Networks (DNNs) have been deployed in many safety-critical applications. The security of DNN models can be compromised by adversarial input examples, where the adversary maliciously crafts and adds input noise to fool a DNN model. The perturbation of model parameters (e.g., weight) is another security concern, one that relates...

Current portable and wearable devices use fingerprint analysis for secure authentication. The fingerprint pattern systems analyze only the surface morphology of the fingerprint, making it easy for hackers to spoof and bypass authentication. RF signals can collect tissue information beyond the surface of the finger and can provide increased security...