Federated learning is an emerging paradigm for distributed machine learning that enables clients to collaboratively train models while maintaining data privacy. However, this approach introduces vulnerabilities, notably the risk of backdoor ...

Security Operations Centres (SOCs) are specialised facilities where security analysts leverage advanced technologies to monitor, detect, and respond to cyber incidents. However, the increasing volume of security incidents has overwhelmed security analysts,...

Security Operations Centres (SOCs) play a pivotal role in defending organisations against evolving cyber threats. They function as central hubs for detecting, analysing, and responding promptly to cyber incidents with the primary objective of ensuring the ...

Honeyfiles are a particularly useful type of honeypot—fake files deployed to detect and infer information from malicious behaviour. This paper considers the challenge of naming honeyfiles so they are camouflaged when placed amongst real files in a file ...

Rowhammer has drawn much attention from both academia and industry in the past years as rowhammer exploitation poses severe consequences to system security. Since the first comprehensive study of rowhammer in 2014, a number of rowhammer attacks have been ...

Federated Learning (FL) is a privacy-preserving, collaborative machine learning technique where multiple clients train a shared model on their private datasets without sharing the data. While offering advantages, FL is susceptible to backdoor attacks, ...

The energy industry is undergoing significant transformations as it strives to achieve net-zero emissions and future-proof its infrastructure, where every participant in the power grid has the potential to both consume and produce energy resources. ...

Web users often follow hyperlinks hastily, expecting them to be correctly programmed. However, it is possible those links contain typos or other mistakes. By discovering active but erroneous hyperlinks, a malicious actor can spoof a website or service, ...

The rapid progress in the field of IoT and its wide-ranging applications emphasize the criticality of robust security measures for effectively sharing, storing, and managing sensitive data generated by IoT devices. Regulations such as the ...

• Proposed a novel keyword search scheme using lightweight cryptographic primitives for IoT.
• Enable multi-client data sharing settings, letting IoT owners authorize multiple clients.
• Support a dynamic storage environment permitting ...

Developers and manufacturers provide configurable control parameters for flight control programs to support various environments and missions, along with suggested ranges for these parameters to ensure flight safety. However, this flexible mechanism can ...

Many adversarial attacks target natural language processing systems, most of which succeed through modifying the individual tokens of a document. Despite the apparent uniqueness of each of these attacks, fundamentally they are simply a distinct ...

For businesses looking to outsource their data to remote servers, cloud-based data storage is a popular choice. It is popular due to its flexibility, cost-effectiveness, and widespread availability. However, ensuring the confidentiality of data ...

Forgery of facial images and videos has increased the concern about digital security. It has led to the significant development of detecting forgery data recently. However, the data, especially the videos published on the Internet, are usually compressed ...

The daily deluge of alerts is a sombre reality for Security Operations Centre (SOC) personnel worldwide. Those on the front-lines of cybersecurity face the unenviable task of prioritising threats amongst a flood of URLs found within malicious ...

Training deep neural networks (DNNs) requires large datasets and powerful computing resources, which has led some owners to restrict redistribution without permission. Watermarking techniques that embed confidential data into DNNs have been used to ...

Numerous open-source and commercial malware detectors are available. However, their efficacy is threatened by new adversarial attacks, whereby malware attempts to evade detection, e.g., by performing feature-space manipulation. In this work, we propose ...

Deep neural networks (DNNs) have achieved state-of-the-art performance on face recognition (FR) tasks in the last decade. In real scenarios, the deployment of DNNs requires taking various face accessories into consideration, like glasses, hats, and masks. ...

Authentication and cryptography are critical security functions and, thus, are very often included as part of code. These functions require using credentials, such as passwords, security tokens, and cryptographic keys. However, developers often ...

Federated learning (FL) is a distributed, privacy-preserving learning paradigm where a joint model is trained on private data stored on client devices. Data owners (clients) train models locally and then submit them to an aggregation server for ...

Planned organisational changes are frequent occurrences in large enterprises due to the dynamicity of employees’ roles, evolution of teams, units and divisions as a result of mergers, demergers, and general restructuring. To safeguard system ...