Introducing Privacy-Enhancing Technologies to Consortium Blockchains

Blockchain technology has revolutionized the way data is stored, managed, and shared across various industries. Its decentralized nature and immutability make it highly attractive in use cases that require transparency, integrity, and accountability. However, some applications demand confidentiality, necessitating the development of permissioned...

Scaling Up, Staying Secure: Assessing the Cyber Risks of Distributed Energy Resources in the Smart Grid

Distributed Energy Resources (DER), like solar panels, are projected to take over power generation responsibilities. This will happen during the transition of the current power grid to the Smart Grid. Due to the importance of this power to society, it is crucial that the grid stays stable.<br/><br/>DER devices are similar to IoT devices in scale...

Attacks on Searchable Symmetric Encryption Systems: Revisiting Similar-data and File Injection Attacks

The amount of data individuals create keeps increasing every year to the point that the data cannot be stored on a single device anymore. Cloud storage provides a solution for this problem, but not everybody wants the cloud storage service providers to peek at their data and they thus encrypt their data before storing it on the service provider...

Methodological Considerations in Exploit Prediction Systems

The growing number of software vulnerabilities being disclosed is posing a challenge to many organisations. With limited patching resources and only a fraction of the vulnerabilities posing a real threat, prioritization is key. Current prioritization methods, such as CVSS, are failing and are sometimes no better than random guessing. Exploit...

RPL-based Passive OS Fingerprinting in Low-power and Lossy Wireless Sensor Networks

Since the introduction of networking protocols for Low-power and Lossy Networks (LLN), many implementations have been created in the form of (real-time) Operating Systems (OS), simplifying their usage and making the technology more widely available. The low cost and low complexity of LLNs allow for large-scaled wireless sensor deployments,...

Approximate Gradient Inversion Attack on Federated Learning

Federated learning is a private-by-design distributed learning paradigm where clients train local models on their own data before a central server aggregates their local updates to compute a global model. Depending on the aggregation method used, the local updates are either the gradients or the weights of local learning models. Unfortunately,...

Early-Warning-Driven Approach for Network Protection Against Earthquakes

Natural disasters can significantly disturb communication networks. There are examples of events causing massive connectivity failures in the past, such as the Great East Japan Earthquake. Network protection mechanisms have been developed to cope with the destructive power of natural disasters and mitigate their impact on connections...

Bubblechain: An IoT authentication system

Authentication of domains has been a crucial part of the growth of web browsing, especially for e-commerce and secure browsing. However, the digital space has expanded from web domains to include devices such as smart cars, smart houses, and other IoT devices. The future for these devices is to communicate autonomously with one another, also...

Multi-Functional Privacy-Preserving Data Aggregation: With Malicious User Detection

In practice, many applications like traffic monitoring and smart grids rely on computing functions on privacy-sensitive data. In order to protect privacy-sensitive data and still keep the ability to compute any arbitrary function, multi-functional privacy-preserving data aggregation schemes have been created. These schemes, however, can be...