ACE: Adaptive channel estimation for detecting analog/RF trojans in WLAN transceivers

ACE: Adaptive channel estimation for detecting analog/RF trojans in WLAN transceivers
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ACE:自适应信道估计,用于检测 WLAN 收发器中的模拟/RF 木马

DOI:
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发表时间:
2017
期刊:
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
影响因子:
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通讯作者:
Y. Makris
Y. Makris
中科院分区:
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文献类型:
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作者:
K. S. Subramani;A. Antonopoulos;A. Abotabl;Aria Nosratinia;Y. Makris

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我们提出了一种能够检测无线局域网(WLAN)收发器的模拟/RF电路中的硬件木马(HT)的防御方法。所提出的方法,这是实现在接收机(RX)侧,不能被篡改的攻击者,利用信道估计能力存在于正交频分复用(OFDM)系统。具体而言,它采用自适应方法来鲁棒地将可能的HT活动与信道和设备噪声隔离,从而暴露特洛伊木马的存在。自适应信道估计(ACE)的防御机制进行测试,使用HT,这是实现在印刷电路板(PCB)上,并安装在无线开放接入研究平台(WARP)。通过对功率放大器(PA)进行微小修改而引入的这种HT操纵802.11a/g发射机(TX)的发射功率特性,以便泄漏敏感数据,例如加密密钥。通过在实际信道条件下进行的实验,即在空中和存在干扰的情况下,所提出的防御的有效性已得到验证。
We propose a defense method capable of detecting hardware Trojans (HTs) in the analog/RF circuitry of wireless local area network (WLAN) transceivers. The proposed method, which is implemented on the receiver (RX) side and cannot be tampered with by the attacker, leverages the channel estimation capabilities present in Orthogonal Frequency Division Multiplexing (OFDM) systems. Specifically, it employs an adaptive approach to robustly isolate possible HT activity from channel and device noise, thereby exposing the Trojan's presence. The adaptive channel estimation (ACE) defense mechanism is put to the test using a HT which is implemented on a printed circuit board (PCB) and mounted on the Wireless Open-Access Research Platform (WARP). This HT, which is introduced through minute modifications in the power amplifier (PA), manipulates the transmission power characteristics of an 802.11a/g transmitter (TX) in order to leak sensitive data, such as the encryption key. Effectiveness of the proposed defense has been verified through experiments conducted in actual channel conditions, namely over-the-air and in the presence of interference.
DOI: 10.1109/jproc.2014.2334493
发表时间: 2014-08-01
影响因子: 20.6
作者:
Bhunia, Swarup;Hsiao, Michael S.;Narasimhan, Seetharam
通讯作者: Narasimhan, Seetharam