Related papers: Intentional Forgetting
This paper investigates an important informationflow security property called opacity in partially-observed discrete-event systems. We consider the presence of a passive intruder (eavesdropper) that knows the dynamic model of the system and…
We develop and study new adversarial perturbations that enable an attacker to gain control over decisions in generic Artificial Intelligence (AI) systems including deep learning neural networks. In contrast to adversarial data modification,…
Password users frequently employ passwords that are too simple, or they just reuse passwords for multiple websites. A common complaint is that utilizing secure passwords is too difficult. One possible solution to this problem is to use a…
The Internet Economy has a strong dependency on cyberspace. This raises security risk scenarios due to the increasing number of vulnerabilities and the increased frequency and sophistication of cyber attacks, especially with the advent of…
Memory vulnerabilities are a major threat to many computing systems. To effectively thwart spatial and temporal memory vulnerabilities, full logical memory safety is required. However, current mitigation techniques for memory safety are…
With the advances in information technology (IT) criminals are using cyberspace to commit numerous cyber crimes. Cyber infrastructures are highly vulnerable to intrusions and other threats. Physical devices and human intervention are not…
Despite numerous countermeasures proposed by practitioners and researchers, remote control-flow alteration of programs with memory-safety vulnerabilities continues to be a realistic threat. Guaranteeing that complex software is completely…
The security of passwords is dependent on a thorough understanding of the strategies used by attackers. Unfortunately, real-world adversaries use pragmatic guessing tactics like dictionary attacks, which are difficult to simulate in…
Human memory is not perfect - people constantly memorize new facts and forget old ones. One example is forgetting a password, a common problem raised at IT help desks. We present several protocols that allow a user to automatically recover…
Perimeter cybersecurity, while essential, has proven insufficient against sophisticated, coordinated, and cyber-physical attacks. In contrast, mission-centric cybersecurity emphasizes finding evidence of attack impact on mission success,…
Model explanations provide transparency into a trained machine learning model's blackbox behavior to a model builder. They indicate the influence of different input attributes to its corresponding model prediction. The dependency of…
Despite the deployment of preventive security mechanisms to protect the assets and computing platforms of users, intrusions eventually occur. We propose a novel intrusion survivability approach to withstand ongoing intrusions. Our approach…
Purveyors of malicious network attacks continue to increase the complexity and the sophistication of their techniques, and their ability to evade detection continues to improve as well. Hence, intrusion detection systems must also evolve to…
The ability to learn more and more concepts over time from incrementally arriving data is essential for the development of a life-long learning system. However, deep neural networks often suffer from forgetting previously learned concepts…
Protecting digital identities of human face from various attack vectors is paramount, and face anti-spoofing plays a crucial role in this endeavor. Current approaches primarily focus on detecting spoofing attempts within individual frames…
The vulnerability of cyber-physical systems to cyber attack is well known, and the requirement to build cyber resilience into these systems has been firmly established. The key challenge this paper addresses is that maturing this discipline…
Security risk assessment is essential in establishing the trustworthiness and reliability of modern systems. While various security risk assessment approaches exist, prevalent applications are "pen and paper" implementations that -- even if…
In real-world applications, learning-enabled systems often undergo iterative model development to address challenging or emerging tasks, which involve collecting new data, training a new model and validating the model. This continual model…
Responsible disclosure limitation is an iterative exercise in risk assessment and mitigation. From time to time, as disclosure risks grow and evolve and as data users' needs change, agencies must consider redesigning the disclosure…
The rapid growth of interest in quantum computing has brought about the need to secure these powerful machines against a range of physical attacks. As qubit counts increase and quantum computers achieve higher levels of fidelity, their…