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Intrusion detection systems (IDS) reinforce cyber defense by autonomously monitoring various data sources for traces of attacks. However, IDSs are also infamous for frequently raising false positives and alerts that are difficult to…
Audit logs serve as a critical component in enterprise business systems and are used for auditing, storing, and tracking changes made to the data. However, audit logs are vulnerable to a series of attacks enabling adversaries to tamper data…
Current networks are increasingly growing in size and complexity and so is the amount of monitoring data that they produce. As a result, network monitoring systems have to scale accordingly. As a possible approach, horizontal scalability…
Linux containers are gaining increasing traction in both individual and industrial use, and as these containers get integrated into mission-critical systems, real-time detection of malicious cyber attacks becomes a critical operational…
Achieving high efficiency on AI operators demands precise control over computation and data movement. However, existing scheduling languages are locked into specific compiler ecosystems, preventing fair comparison, reuse, and evaluation…
Nowadays large computers extensively output logs to record the runtime status and it has become crucial to identify any suspicious or malicious activities from the information provided by the realtime logs. Thus, fast log anomaly detection…
While monitoring system behavior to detect anomalies and failures is important, existing methods based on log-analysis can only be as good as the information contained in the logs, and other approaches that look at the OS-level software…
Dataset condensation aims to synthesize compact yet informative datasets that retain the training efficacy of full-scale data, offering substantial gains in efficiency. Recent studies reveal that the condensation process can be vulnerable…
Tools that alert developers about library vulnerabilities depend on accurate, up-to-date vulnerability databases which are maintained by security researchers. These databases record the libraries related to each vulnerability. However, the…
Much of the worlds data is streaming, time-series data, where anomalies give significant information in critical situations. Yet detecting anomalies in streaming data is a difficult task, requiring detectors to process data in real-time,…
This article introduces a novel method for detecting anomalies within log data from control system nodes at the European XFEL accelerator. Effective anomaly detection is crucial for providing operators with a clear understanding of each…
Existing tamper-evident logging systems suffer from high overhead and severe data loss in high-load settings, yet only provide coarse-grained tamper detection. Moreover, installing such systems requires recompiling kernel code. To address…
Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex black boxes. This means that a security analyst will have little to no explanation or clarification on why an IDS model made a particular prediction.…
As the communication industry has connected distant corners of the globe using advances in network technology, intruders or attackers have also increased attacks on networking infrastructure commensurately. System administrators can attempt…
An ambient sensor network is installed in Smart Homes to identify low-level events taking place by residents, which are then analysed to generate a profile of activities of daily living. These profiles are compared to both the resident's…
Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product development, especially for small teams and agile workflows. We present Avenir-UX, a…
Anomaly detection is a crucial and challenging subject that has been studied within diverse research areas. In this work, we explore the task of log anomaly detection (especially computer system logs and user behavior logs) by analyzing…
Code smells signal violations of design principles that degrade the internal quality of evolving software systems. Although many tools detect such anomalies using static metrics, they often ignore the development context in which smells…
Insider threat is one of the most pernicious threat vectors to information and communication technologies (ICT)across the world due to the elevated level of trust and access that an insider is afforded. This type of threat can stem from…
Business Process Management Systems (BPMS) log events and traces of activities during the execution of a process. Anomalies are defined as deviation or departure from the normal or common order. Anomaly detection in business process logs…