Embedded computing systems are very vulnerable to anomalies that can occur during execution of deployed software. Anomalies can be due for example to faults, bugs or deadlocks during executions. These anomalies can have very dangerous consequences on the systems controlled by embedded computing devices. Embedded systems are designed to perform autonomously, i.e. without any human intervention, and thus the possibility to debug an application to manage the anomaly is very difficult if not impossible. Anomaly detection algorithms are the primary means of being aware of anomalous conditions. In this paper we describe a novel approach to detect an anomaly during execution of one or more applications. The algorithm exploits the differences betwe...
The next generation of critical systems, namely complex Critical Infrastructures (LCCIs), require ef...
A number of hardware and software techniques have been proposed to detect dynamic program behaviors ...
The analysis and correct categorisation of software performance anomalies is a major challenge in cu...
Computing systems are vulnerable to anomalies that might occur during execution of deployed software...
Existing techniques used for anomaly detection do not fully utilize the intrinsic properties of embe...
Malware is a serious threat to network-connected embedded systems, as evidenced by the continued and...
Embedded systems suffer from reliability issues such as variations in temperature and voltage, singl...
In this paper, we introduce a novel mechanism that identifies abnormal system-wide behaviors using t...
The inconsistency is a major problem in security of information in computer is two ways: data incons...
Embedded operating systems generate a log of operating system function calls which we refer to as tr...
With billions of networked connected embedded systems, the security historically provided by the iso...
Software performance anomaly detection is a major challenge in complex industrial cyber-physical sys...
Program anomaly detection — modeling normal program executions to detect deviations at runtime as cu...
This paper presents a new machine-learning technique that performs anomaly detection as software is ...
This paper proposes an approach for detecting compromised programs by analysing suitable features fr...
The next generation of critical systems, namely complex Critical Infrastructures (LCCIs), require ef...
A number of hardware and software techniques have been proposed to detect dynamic program behaviors ...
The analysis and correct categorisation of software performance anomalies is a major challenge in cu...
Computing systems are vulnerable to anomalies that might occur during execution of deployed software...
Existing techniques used for anomaly detection do not fully utilize the intrinsic properties of embe...
Malware is a serious threat to network-connected embedded systems, as evidenced by the continued and...
Embedded systems suffer from reliability issues such as variations in temperature and voltage, singl...
In this paper, we introduce a novel mechanism that identifies abnormal system-wide behaviors using t...
The inconsistency is a major problem in security of information in computer is two ways: data incons...
Embedded operating systems generate a log of operating system function calls which we refer to as tr...
With billions of networked connected embedded systems, the security historically provided by the iso...
Software performance anomaly detection is a major challenge in complex industrial cyber-physical sys...
Program anomaly detection — modeling normal program executions to detect deviations at runtime as cu...
This paper presents a new machine-learning technique that performs anomaly detection as software is ...
This paper proposes an approach for detecting compromised programs by analysing suitable features fr...
The next generation of critical systems, namely complex Critical Infrastructures (LCCIs), require ef...
A number of hardware and software techniques have been proposed to detect dynamic program behaviors ...
The analysis and correct categorisation of software performance anomalies is a major challenge in cu...