A survey of security issues in wireless sensor networks <s> CONSTRAINTS IN WSNS <s> As sensor networks edge closer towards wide-spread deployment, security issues become a central concern. So far, much research has focused on making sensor networks feasible and useful, and has not concentrated on security. We present a suite of security building blocks optimized for resource-constrained environments and wireless communication. SPINS has two secure building blocks: SNEP and μTESLA SNEP provides the following important baseline security primitives: Data confidentiality, two-party data authentication, and data freshness. A particularly hard problem is to provide efficient broadcast authentication, which is an important mechanism for sensor networks. μTESLA is a new protocol which provides authenticated broadcast for severely resource-constrained environments. We implemented the above protocols, and show that they are practical even on minimal hardware: the performance of the protocol suite easily matches the data rate of our network. Additionally, we demonstrate that the suite can be used for building higher level protocols. <s> BIB001 </s> A survey of security issues in wireless sensor networks <s> CONSTRAINTS IN WSNS <s> We consider two of the most important design issues for distributed sensor networks in the battlefield: security for communication in such hostile terrain; and energy efficiency because of the battery's limited capacity and the impracticality of recharging. Communication security is normally provided by encryption, i.e. data are encrypted before transmission and are decrypted first on reception. We exploit the secure sensor network design space for energy efficiency by investigating different microprocessors coupled with various public key algorithms. We propose a power control mechanism for sensors to operate in an energy-efficient fashion using the newly developed dynamical voltage scaling (DVS) technique. In particular we consider multiple voltage processors and insert additional information into the communication channel to guide the selection of proper voltages for data decryption/encryption and processing in order to reduce the total computational energy consumption. We experiment several encryption standards on a broad range of embedded processors and simulate the behavior of the sensor network to show that the sensor's lifetime can be extended substantially. <s> BIB002
Individual sensor nodes in a WSN are inherently resource constrained. They have limited processing capability, storage capacity, and communication bandwidth. Each of these limitations is due in part to the two greatest constraints -limited energy and physical size. Table 1 shows several currently available sensor node platforms. The design of security services in WSNs must consider the hardware constraints of the sensor nodes: • Energy: energy consumption in sensor nodes can be categorized into three parts: -Energy for the sensor transducer -Energy for communication among sensor nodes -Energy for microprocessor computation The study in   found that each bit transmitted in WSNs consumes about as much power as executing 800-1000 instructions. Thus, communication is more costly than computation in WSNs. Any message expansion caused by security mechanisms comes at a significant cost. Further, higher security levels in WSNs usually correspond to more energy consumption for cryptographic functions. Thus, WSNs can be divided into different security levels, depending on energy cost  BIB002 . • Computation: the embedded processors in sensor nodes are generally not as powerful as those in nodes of a wired or ad hoc network. As such, complex cryptographic algorithms cannot be used in WSNs. • Memory: memory in a sensor node usually includes flash memory and RAM. Flash memory is used for storing downloaded application code and RAM is used for storing application programs, sensor data, and intermediate computations. There is usually not enough space to run complicated algorithms after loading OS and application code. In the SmartDust project, for example, TinyOS consumes about 3500 bytes of instruction memory, leaving only 4500 bytes for security and applications   . This makes it impractical to use the majority of current security algorithms BIB001 . With an Intel Mote, the situation is slightly improved, but still far from meeting the requirements of many algorithms. • Transmission range: the communication range of sensor nodes is limited both technically and by the need to conserve energy. The actual range achieved from a given transmission signal strength is dependent on various environmental factors such as weather and terrain.