Trust in IoT: dynamic remote attestation through efficient behavior capture.

<break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break><break></break>The Internet of Things (IoT) is a latest concept of machine-to-machine communication, that also gave birth to several information security problems. Many traditional software solutions fail to address these security issues such as trustworthiness of remote entities. Remote attestation is a technique given by  <italic>Trusted Computing Group</italic> (TCG) to monitor and verify this trustworthiness. In this regard, various remote validation methods have been proposed. However, static techniques cannot provide resistance to recent attacks e.g. the latest <italic>Heartbleed</italic> bug, and the recent high profile <italic>glibc</italic> attack on Linux operating system. In this research, we have designed and implemented a lightweight Linux kernel security module for IoT devices that is  <italic>scalable</italic> enough to monitor multiple applications in the kernel space. The newly built technique can measure and report multiple application’s static and dynamic behavior simultaneously. Verification of behavior of applications is performed via machine learning techniques. The result shows that deviating behavior can be detected successfully by the verifier.<break></break> [ABSTRACT FROM AUTHOR]