论文标题
恐慌:侧渠道攻击反向工程的内存计算
SCARE: Side Channel Attack on In-Memory Computing for Reverse Engineering
论文作者
论文摘要
内存计算体系结构为von-Neumann计算所带来的能源效率障碍提供了急需的解决方案,这是由于处理器和内存之间的数据移动。这种内存架构中实现的功能通常是专有的,并且构成了机密的知识产权。我们的研究表明,使用RRAM实施的IMC容易受到侧渠道攻击。与旨在从密码实现中泄漏私钥的常规SCA不同,Scare可以揭示内存中实现的敏感IP。因此,对手无需执行侵入性逆向工程来解锁功能。我们通过将诸如DCIM和魔术等最近的IMC体系结构作为测试用例来证明恐慌。仿真结果表明,基于输入的数量,使其容易受到SCA的影响,并且,或者,或者,或者,或者,或者,或者,或,或者,或者,或者,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或,或者,则产生了不同的功率和计时签名。尽管过程变化可能会因重大重叠而引起的签名,但我们表明对手可以使用统计建模和分析来识别实现功能的结构。恐慌可以通过测试有限数量的模式来找到实现的IP。例如,与A+BC函数的蛮力攻击相比,提出的技术将模式数量减少了64%。此外,分析显示,由于DCIM和魔术的供应电压的对抗性变化,恐惧检测模型的改善。我们还提出了对策,例如冗余输入和文字的扩展。冗余输入可以以25%的面积和20%的功率开销掩盖IP。但是,可以通过更大的努力找到功能。文字的扩展会导致36%的功率开销。但是,它对对手进行了野蛮的搜索,重新努力增加了3.04倍。
In-memory computing architectures provide a much needed solution to energy-efficiency barriers posed by Von-Neumann computing due to the movement of data between the processor and the memory. Functions implemented in such in-memory architectures are often proprietary and constitute confidential Intellectual Property. Our studies indicate that IMCs implemented using RRAM are susceptible to Side Channel Attack. Unlike conventional SCAs that are aimed to leak private keys from cryptographic implementations, SCARE can reveal the sensitive IP implemented within the memory. Therefore, the adversary does not need to perform invasive Reverse Engineering to unlock the functionality. We demonstrate SCARE by taking recent IMC architectures such as DCIM and MAGIC as test cases. Simulation results indicate that AND, OR, and NOR gates (building blocks of complex functions) yield distinct power and timing signatures based on the number of inputs making them vulnerable to SCA. Although process variations can obfuscate the signatures due to significant overlap, we show that the adversary can use statistical modeling and analysis to identify the structure of the implemented function. SCARE can find the implemented IP by testing a limited number of patterns. For example, the proposed technique reduces the number of patterns by 64% compared to a brute force attack for a+bc function. Additionally, analysis shows improvement in SCAREs detection model due to adversarial change in supply voltage for both DCIM and MAGIC. We also propose countermeasures such as redundant inputs and expansion of literals. Redundant inputs can mask the IP with 25% area and 20% power overhead. However, functions can be found by greater RE effort. Expansion of literals incurs 36% power overhead. However, it imposes brute force search by the adversary for which the RE effort increases by 3.04X.