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Nowadays, information and communications technology systems are fundamental assets of our social and economical model, and thus they should be properly protected against the malicious activity of cybercriminals. Defence mechanisms are…
Automatic log file analysis enables early detection of relevant incidents such as system failures. In particular, self-learning anomaly detection techniques capture patterns in log data and subsequently report unexpected log event…
Considering computer systems, security is the major concern with usability. Security policies need to be developed to protect information from unauthorized access. Passwords and secrete codes used between users and information systems for…
Data privacy and anonymisation are critical concerns in today's data-driven society, particularly when handling personal and sensitive user data. Regulatory frameworks worldwide recommend privacy-preserving protocols such as k-anonymisation…
Data privacy is one of the key challenges faced by enterprises today. Anonymization techniques address this problem by sanitizing sensitive data such that individual privacy is preserved while allowing enterprises to maintain and share…
Execution logs are a crucial medium as they record runtime information of software systems. Although extensive logs are helpful to provide valuable details to identify the root cause in postmortem analysis in case of a failure, this may…
Logs are crucial for analyzing large-scale software systems, offering insights into system health, performance, security threats, potential bugs, etc. However, their chaotic nature$\unicode{x2013}$characterized by sheer volume, lack of…
Log data have facilitated various tasks of software development and maintenance, such as testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is typically required to transform log messages into structured…
Secure cloud storage is an issue of paramount importance that both businesses and end-users should take into consideration before moving their data to, potentially, untrusted clouds. Migrating data to the cloud raises multiple privacy…
This paper deals with the problem of analyzing application event logs in relevance to dependability evaluation. We present the significance of application logs as a valuable source of information on operational profiles, anomalies and…
Software and System logs record runtime information about processes executing within a system. These logs have become the most critical and ubiquitous forms of observability data that help developers understand system behavior, monitor…
In industrial and IoT environments, massive amounts of real-time and historical process data are continuously generated and archived. With sensors and devices capturing every operational detail, the volume of time-series data has become a…
To prove that a dataset is sufficiently anonymized, many privacy policies suggest that a re-identification risk assessment be performed, but do not provide a precise methodology for doing so, leaving the industry alone with the problem.…
Logs provide first-hand information for engineers to diagnose failures in large-scale online service systems. Log parsing, which transforms semi-structured raw log messages into structured data, is a prerequisite of automated log analysis…
Kubernetes, an open-source platform for automating the deployment, scaling, and management of containerized applications, is widely used for its efficiency and scalability. However, its complexity and extensive configuration options often…
Accountability regimes typically encourage record-keeping to enable the transparency that supports oversight, investigation, contestation, and redress. However, implementing such record-keeping can introduce considerations, risks, and…
NetFlow data is a popular network log format used by many network analysts and researchers. The advantages of using NetFlow over deep packet inspection are that it is easier to collect and process, and it is less privacy intrusive. Many…
Nowadays, we are increasingly logging on many different Internet sites to access private data like emails or photos remotely stored in the clouds. This makes us all the more concerned with digital identity theft and passwords being stolen…
Machine learning (ML) algorithms are heavily based on the availability of training data, which, depending on the domain, often includes sensitive information about data providers. This raises critical privacy concerns. Anonymization…
In many software applications, logs serve as the only interface between the application and the developer. However, navigating through the logs of long-running applications is often challenging. Logs from previously successful application…