Securing a Wireless Network-on-Chip Against Jamming-Based Denial-of-Service and Eavesdropping Attacks

窃听 干扰 计算机科学 计算机网络 服务拒绝攻击 无线 数据传输 网络数据包 电信 互联网 热力学 物理 万维网
作者
Abhishek Vashist,Andrew Keats,Sai Manoj Pudukotai Dinakarrao,Amlan Ganguly
出处
期刊:IEEE Transactions on Very Large Scale Integration Systems [Institute of Electrical and Electronics Engineers]
卷期号:27 (12): 2781-2791 被引量:31
标识
DOI:10.1109/tvlsi.2019.2928960
摘要

Wireless networks-on-chips (NoCs) (WiNoCs) have emerged as a possible solution to the nonscalable multihop data transmission paths in traditional wired NoC architectures. Using low-power transceivers in NoC switches, novel WiNoC architectures have been shown to achieve higher energy efficiency with improved peak bandwidth and reduced on-chip data transfer latency. However, using wireless interconnects for intrachip data transfer over an unguided medium introduces additional security vulnerabilities in on-chip communication arising from either external attackers or internal hardware Trojans. In this article, we propose a mechanism to make the wireless communication in a WiNoC secure against persistent jamming-based denial-of-service (DoS) attacks and eavesdropping (ED) from both external and internal attackers. Persistent jamming attacks on the on-chip wireless medium will cause interference in data transfer over the duration of the attack resulting in errors in contiguous bits, known as burst errors. Therefore, we use a burst-error correction code to monitor the rate of burst errors received over the wireless medium and deploy a machine-learning (ML) classifier to detect the persistent jamming attack and distinguish it from random burst errors. In the event of a persistent jamming attack, alternate routing strategies are proposed to avoid the DoS attack over the wireless medium, so that a secure data transfer can be sustained even in the presence of persistent jamming. In the event of an external ED attack, we deploy a low-latency and lightweight data scrambling method to secure communication over the wireless channel. In the case of an internal ED, we propose a mechanism to identify the attacker and prevent the attack. We evaluate the proposed techniques on a WiNoC in the presence of DoS and ED attacks from both internal and external attackers. On an average, 99.87% of the attack on DoS detection was achieved with the chosen ML classifier. A bandwidth degradation of <; 3% is experienced in the event of both DoS and ED internal attacks. The wireless interconnects are disabled in the presence of a persistent external jamming DoS attack for security, therefore eliminating the advantages of the wireless interconnections making the performance of the WiNoC comparable with that of a wired NoC. Although scrambling overheads are incurred in the presence of an external ED attack, the overheads are minimized by adopting simple XOR-based encoding and decoding.

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