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Network-on-chip (NoC) is widely used as an efficient communication architecture in multi-core and many-core System-on-chips (SoCs). However, the shared communication resources in an NoC platform, e.g., channels, buffers, and routers, might be used to conduct attacks compromising the security of NoC-based SoCs. Most of the proposed encryption-based protection methods in the literature require leaving some parts of the packet unencrypted to allow the routers to process/forward packets accordingly. This reveals the source/destination information of the packet to malicious routers, which can be exploited in various attacks. For the first time, we propose the idea of secure, anonymous routing with minimal hardware overhead to encrypt the entire packet while exchanging secure information over the network. We have designed and implemented a new NoC architecture that works with encrypted addresses. The proposed method can manage malicious and benign failures at NoC channels and buffers by bypassing failed components with a situation-driven stochastic path diversification approach. Hardware evaluations show that the proposed security solution combats the security threats at the affordable cost of 1.5% area and 20% power overheads chip-wide.
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Network Anomaly Detection Based on Tensor Decomposition
The problem of detecting anomalies in time series from network measurements has been widely studied and is a topic of fundamental importance. Many anomaly detection methods are based on packet inspection collected at the network core routers, with consequent disadvantages in terms of computational cost and privacy. We propose an alternative method in which packet header inspection is not needed. The method is based on the extraction of a normal subspace obtained by the tensor decomposition technique considering the correlation between different metrics. We propose a new approach for online tensor decomposition where changes in the normal subspace can be tracked efficiently. Another advantage of our proposal is the interpretability of the obtained models. The flexibility of the method is illustrated by applying it to two distinct examples, both using actual data collected on residential routers.
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- Award ID(s):
- 1740895
- PAR ID:
- 10181893
- Date Published:
- Journal Name:
- 18th Mediterranean Communication and Computer Networking Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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