Differential Cryptanalysis on Block Cipher Skinny with MILP Program

Secure lightweight block ciphers have become an important aspect due to the fact that they are a popular choice for providing security in ubiquitous devices. Two of the most important attacks on block ciphers are differential cryptanalysis [1] and linear cryptanalysis [2]. Calculating the number of active S-boxes is one of the method to examine the security of block ciphers against differential attack. In this paper, we count the minimum number of active S-boxes for several rounds of the lightweight ciphers namely KLEIN, LED and AES. We utilized the method proposed in [9], where calculation of the minimum number of active S-boxes is formulated as a Mixed Integer Linear Programming (MILP) problem. The objective function is to minimize the number of active S-boxes, subject to the constraints imposed by the differential propagation of the cipher. The experimental results are presented in this paper and found to be encouraging.

Mixed integer linear programming (MILP) model was presented by Sun et al. at Asiacrypt 2014 to search for differential characteristics of block ciphers. Based on this model, it is easy to assess block ciphers against differential attack. In this paper, the MILP model is improved to search for differential trails of Midori64 which is a family of lightweight block ciphers provided by Banik et al. at Asiacrypt 2015. We find the best 5-round differential characteristics of Midori64 with MILP-based model, and the probabilities are 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-52</sup> and 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-58</sup> respectively. Based on these distinguishers, we give key recovery attacks on the 11-round reduced Midori64 with data complexities of 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">55.6</sup> and 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">61.2</sup> , and time complexities of 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">109.35</sup> and 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">100.26</sup> .

Resource Management Approach to an Efficient Wireless Sensor Network

Wireless sensor networks consist of a large number of low-cost, low-power, and multifunctional sensor nodes that communicate over short distances through wireless links. Such sensor networks are ideal candidates for a wide range of applications such as monitoring of critical infrastructures, data acquisition in hazardous environments, industry control systems, vehicular networks, and military operations. Wireless sensor networks introduce new security challenges due to their dynamic topology, severe resource constraints, and absence of a trusted infrastructure. The purpose of this special issue is to publish high-quality research papers as well as review articles addressing recent advances of wireless sensor network security. In this special issue, we will explore the topic of security challenges and solutions for the wide application of wireless sensor networks in different areas, such as RFID and smart grid. RFID has been widely used in logistics and internet of things. Smart grid leverages sensor networks to better balance the load of the power grid. Both of them have great impact on the daily life and areweak points of thewhole economy,which attract the attention of terrorists. The feasible attacks and defense solutions are still not clear.The papers in this volume also cover several important foundational security services for wireless sensor networks, such as key management, key distribution, secure cluster formation, secure architecture for multihop communication, intrusion prediction, and secure localization. All these foundational security services are critical bases for application of wireless sensor networks. We hope that the papers in this volume engender further thinking about new security challenges for wireless sensor networks and even further “out-of-the-box” ideas about how to solve new security problems for wireless sensor networks.

Differential cryptanalysis is one of the fundamental cryptanalysis techniques to evaluate the security of the block cipher. In many cases, resistance to differential cryptanalysis is proven through the upper bound of the differential characteristic probability, not the differential probability. Since the attacker uses a differential rather than a differential characteristic, resistance based on a differential characteristic tends to overestimate the security level of the block cipher. Such an overestimation is notably observed in lightweight block ciphers SKINNY, Midori, and CRAFT. In this paper, we examine the gap between the differential characteristics and the differential probability of lightweight block ciphers. We present practical methods for computing differential probability using a multistage graph. Using these methods, we count the exact number of maximum differential characteristics with fixed plaintext/ciphertext difference and activity pattern. By the exact number of maximum differential characteristics, we can calculate the probability that is closer to the real differential probability. In addition, by modifying the method, we compute a more accurate differential probability by considering the characteristics of the lower probability. We find differential distinguishers of 9-round Midori64 with probability 2−61.58, 9-round SKINNY64 with 2−58.67 and 14-round CRAFT with 2−60.32. Furthermore, we find a related-tweakey differential distinguisher of 11-round SKINNY64-64 with 2−55.93 and a related-tweak differential distinguisher of 17-round CRAFT with probability 2−63.37. Finally, we explain why these gaps are notable in Midori64, SKINNY64 and CRAFT by relating the S-box differential distribution table.

Distributed audio sensing with homeostasis-inspired autonomous communication

In order to reduce or avoid the coal mine accidents, this paper proposes the application of wireless sensor networks (WSN) in the coal mine safety intelligent monitoring system, and discusses the principle and advantages of wireless sensor networks. According to the current situation of low level of intellectualization in coal mine safety monitoring system and the existing problems, this paper proposes the designing proposal and the monitoring mechanism of the coal mine safety intelligent monitoring system, discusses the feasibility, the method and the way of the application of the wireless sensor networks in the coal mine safety intelligent monitoring system.

Developing Wireless Sensor Networks (WSN) applications is not an easy task, since it demands different expertise and knowledge. To address this problem, we propose a model-driven approach to build WSN applications. It promotes the separation of concerns between two levels of requirements involved: (i) domain experts, with no knowledge on WSN platforms, contribute to the development of applications, (ii) network experts, with no knowledge on the application domain, program nodes to meet application requirements. Our approach also promotes the reuse of software artifacts: an application model can be reused on different sensor platforms and a platform model can be reused for different WSN applications.

Wireless network of wearable biomedical sensors by human body shows great potential to enhance the biometrics performance significantly. Meanwhile, it poses prominent characteristics and challenges to physicians and engineers for its particular medical application as compared to other application of wireless sensor networks (WSN). Mobility pattern plays an important role in designing the wireless body sensor networks (WBSN) and will also affect the accuracy of modeling WBSN in health care application. Much of the mobility scenarios generated in current work of wireless body sensor networks has used fairly simple models to generate the mobile topological graph, which bear little resemblance to the actual mobility patterns. This paper is the first attempt to investigate the mobility model in WBSN based on the existing mobility models in wireless data networks and ad hoc networks. We first briefly review the existing mobility models in related research areas such as wireless ad hoc network and cellular networks. Further on, we propose a dedicated and more realistic mobility model named BAMM (Body Area Mobility Model) for wireless body sensor networks by concentrating on the unique characteristics of WBSN and finally study the effects of mobility on the performance of WBSN by simulation experiments.

Congestion in Wireless Sensor Network (WSN) occurs when traffic load allocated to any sensor node is beyond its capacity. It is necessary to control the congestion traffic to support traditional quality of service (such as packet loss ratios, packet delay, wasting energy and throughput) especially, multimedia application of Wireless Multimedia Sensor Network (WMSN). Congestion control in WSN has been shown to be very effective with respect to extending lifespan of system. Hence to avoid the congestion in WSN, we proposed an efficient protocol called Priority-based Congestion Control Protocol (PCCP) which prevents an upstream congestion in WSN. The PCCP creates priority table based an importance of each node, and then sends this information to all the nodes within the network. Secondly, the major function of PCCP is to measure congestion level in the network using ratio of packet inter-arrival time along over packet service time. PCCP uses to control upstream congestion along with congestion degree and packet table. PCCP is hop-by-hop upstream congestion control protocol for WSN. PCCP provides work for packet-based computation to optimize congestion control. It can work under both single path & multipath routing. PCCP ensures guarantee of packet loss as well as delay, resulting each node can avoid unfairness and achieve flexible throughput. In this paper, we have proposed that PCCP provides better QoS by controlling network recourse management and network traffic to consuming efficient energy.

The Wireless sensor network has a great applied prospect, so the military, academia and industry pay more and more extensive attention. The first, this article introduces the concept of sensor networks and development background; the second, compared with traditional networks, it summarizes the characteristics of sensor networks. In this basis, the application of the sensor network and the direction of the current study are a given brief introduction and a further discussion.

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

Nowadays, there is a strong demand for increasing the protection of resource-constrained devices such as Radio frequency identification (RFID) systems. Current cryptographic algorithms are sufficient for high-resource desktop computers. RFID systems are commonly used in high-security applications such as access control systems, transaction banking systems, and payment systems. The attacker attempts to mislead RFIDs for unauthorized access to services without payment or to circumvent security mechanisms by detecting a secret password. The biggest challenge in RFID systems is how to ensure successful protection against such infringements. Lightweight cryptography can provide security assurance for protecting RFID systems. This article presents a new ultra-lightweight cryptography algorithm for RFID systems called SLIM. SLIM is a 32-bit block cipher based on the Feistel structure since block ciphers are the most used cryptographic and provide very tight protection for IoT devices. The key challenge in designing a lightweight block cipher is to cope with performance, cost, and security. SLIM, like all symmetric block cipher, uses the same key for encryption and decryption. The proposed algorithm has an excellent performance in both hardware and software environments, with a limited implementation area, an acceptable cost/security for RFID systems, and an energy-efficient behaviour. SLIM has demonstrated high immunity against the most effective linear and differential cryptanalysis attacks and has a sufficient margin of defence against these attacks.

Internet of Things (IOT) is experiencing a super-fast growing phase. Wireless Sensor Networks (WSN), as the “five sense organs” and teleneuron of IOT, is developing fast along. Owing to the application-oriented characteristics of WSN, WSN applications may differ enormously in implementation methods. The WSN developers may have to rewrite the code for each and every application. Along with the increasing demand to WSN applications, WSN developers may have heavier tasks of programming for these applications. Thanks to TinyOS and NesC, an operating system and programming language designed especially for WSN, raises the WSN application's programming to a higher level. Large number of supported sensor hardware plus system provided and user-de-fined libraries eases WSN application programmers' jobs. How-ever, the massive amount of nodes' communication and networking, and security protection slows down the development pace. A unified and empirical WSN application implementation platform is one of the available solutions to the problem. This paper introduces an empirical WSN application implementation platform, which avails the WSN developers build an application with unified code template and network packet generation and processing strategies.

The area of Ambient Intelligence recently seems to be matured enough and widely accepted as one of the basic supporting technologies and approaches for human living environment enhancement. There are many interesting applications of wireless sensor networks coupled with ambient intelligence applications, mainly for the creation of indoor intelligent spaces. However, there are just a few of them aiming at the enhancement of outdoor environments in order to support human activities typical for wide-area spaces in open natural environments. There are also a number of useful applications of wireless sensor networks aiming at environmental monitoring, however, just a few of them, if any, are taking advantage of recent achievements of Ambient Intelligence. In our paper, we intend to go further with the ideas of how the Ambient Intelligence used in a wide manner in connection with wireless sensor networks throughout the open natural environment could be beneficial not only for early warning in case of possible disasters, but also as an important supporting tool for people located in outdoor areas due to various reasons, e.g. hitchhikers, hikers on difficult mountains tracks, or even workers in exacting outdoor workplaces (i.e., a coal mine). An idea of a large-scale Ambient Intelligence system based on a wide area wireless sensor network is presented, where the system should be able to monitor the environment, evaluate the collected data and, if necessary, inform the workers in the environment about possible threats and also give some hints for their rescue, using various communication devices.