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Software Keyloggers are dominant class of malicious applications that surreptitiously logs all the user activity to gather confidential information. Among many other types of keyloggers, API-based keyloggers can pretend as unprivileged program running in a user-space to eavesdrop and record all the keystrokes typed by the user. In a Linux environment, defending against these types of malware means defending the kernel against being compromised and it is still an open and difficult problem. Considering how recent trend of edge computing extends cloud computing and the Internet of Things (IoT) to the edge of the network, a new types of intrusiondetection system (IDS) has been used to mitigate cybersecurity threats in edge computing. Proposed work aims to provide secure environment by constantly checking virtual machines for the presence of keyloggers using cutting edge artificial immune system (AIS) based technology. The algorithms that exist in the field of AIS exploit the immune system’s characteristics of learning and memory to solve diverse problems. We further present our approach by employing an architecture where host OS and a virtual machine (VM) layer actively collaborate to guarantee kernel integrity. This collaborative approach allows us to introspect VM by tracking events (interrupts, system calls, memory writes, network activities, etc.) and to detect anomalies by employing negative selection algorithm (NSA).
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Operating Systems for Resource-adaptive Intelligent Software: Challenges and Opportunities
The past decades witnessed the fast and wide deployment of Internet. The Internet has bred the ubiquitous computing environment that is spanning the cloud, edge, mobile devices, and IoT. Software running over such a ubiquitous computing environment environment is eating the world. A recently emerging trend of Internet-based software systems is “ resource adaptive ,” i.e., software systems should be robust and intelligent enough to the changes of heterogeneous resources, both physical and logical, provided by their running environment. To keep pace of such a trend, we argue that some considerations should be taken into account for the future operating system design and implementation. From the structural perspective, rather than the “monolithic OS” that manages the aggregated resources on the single machine, the OS should be dynamically composed over the distributed resources and flexibly adapt to the resource and environment changes. Meanwhile, the OS should leverage advanced machine/deep learning techniques to derive configurations and policies and automatically learn to tune itself and schedule resources. This article envisions our recent thinking of the new OS abstraction, namely, ServiceOS , for future resource-adaptive intelligent software systems. The idea of ServiceOS is inspired by the delivery model of “ Software-as-a-Service ” that is supported by the Service-Oriented Architecture (SOA). The key principle of ServiceOS is based on resource disaggregation, resource provisioning as a service, and learning-based resource scheduling and allocation. The major goal of this article is not providing an immediately deployable OS. Instead, we aim to summarize the challenges and potentially promising opportunities and try to provide some practical implications for researchers and practitioners.
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- Award ID(s):
- 1633370
- PAR ID:
- 10374173
- Date Published:
- Journal Name:
- ACM Transactions on Internet Technology
- Volume:
- 21
- Issue:
- 2
- ISSN:
- 1533-5399
- Page Range / eLocation ID:
- 1 to 19
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3425866
