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Abstract
Ambient Intelligence (AmI) requires devices everywhere, dynamic and massively distributed networks of low-cost nodes that, among other data, manage private information or control restricted operations. MSP430, a 16-bit microcontroller, is used in WSN platforms, as the TelosB. Physical access to devices cannot be restricted, so attackers consider them a target of their malicious attacks in order to obtain access to the network. Side-channel analysis (SCA) easily exploits leakages from the execution of encryption algorithms that are dependent on critical data to guess the key value. In this paper we present an evaluation framework that facilitates the analysis of the effects of compiler and backend optimizations on the resistance against statistical SCA. We propose an optimization-based software countermeasure that can be used in current low-cost devices to radically increase resistance against statistical SCA, analyzed with the new framework.
Highlights
The concept of Ambient Intelligence (AmI) provides a vision of the Information Society where the emphasis is on greater user-friendliness, more efficient support services, user-empowerment, and human interaction support.People are surrounded by intelligent intuitive interfaces that are embedded in all kinds of objects and an environment that is capable of recognizing and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way.In [1] authors identified five basic technology requirements for AmI, three of them related to Wireless Sensor Networks: A seamless mobile/fixed communications infrastructure Dynamic and massively distributed device networks Dependability and securityAccording to [2], malicious attacks can even end up ruining businesses based on AmI when the system is put out of operation for some time
We focus our experiments on Correlation Power Analysis (CPA), which can be applied to power consumption traces or to electromagnetic radiation (EMA)
When the partial loop unrolling is of 3 iterations, and when no loop unrolling is applied, in both cases the results obtained are similar
Summary
According to [2], malicious attacks can even end up ruining businesses based on AmI when the system is put out of operation for some time. Malicious attacks can be active or passive. New architectures for nodes in WSN are being presented everyday, using IEEE802.15.4 or Bluetooth [3]. Privacy and security are critical in AmI applications using WSN, as is the case of medical applications [4] where privacy needs a thorough study [5]. An active attack is a deliberate alteration or destruction of data or creation of false data. A passive attack consists of unauthorized monitoring, but not alteration or destruction of data (e.g., wiretapping)
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