The increasing popularity of smart mobile devices enables a widespread use of Location Based Services (LBS). LBSs require real-time processing of frequent updating data (i.e., Streams), and return customized results to mobile users based on their own locations. The mobile environment brings additional design and development considerations to LBS applications, such as real-time awareness, energy efficiency, and privacy preservation. In a recent project, we worked on the Emergency Medical Service as an example LBS application, and developed a Cloud-based LBS prototype, named as Early Alert System (EARS), to deliver real-time emergency vehicle's information to smart mobile devices based on their geo-proximity. EARS leverages Cloud-based stream processing systems to address the real-time stream processing needs, and also develops effective methods to conserve energy consumption and preserve user privacy. EARS is an efficient approach to deliver real-time geo-information from the Cloud to mobile users, and can be easily generalized to other LBS applications in the mobile environment.

ABSTRACT To produce ciphertexts, two modes of encryption are applied—block ciphers, which encrypt a fixed size block of plaintext at a time, and stream ciphers, which encrypt stream data, one or more bits at a time. As one of stream ciphers, the cipher feedback (CFB) mode is implemented by a block cipher via multiple stages, and in each stage, 1 bit or a number of bits of plaintext are encrypted at a time. Throughout this paper, the study will focus upon the error performance of the stream‐based CFB under two sliding‐window protocols, go‐back‐N and selective‐reject, in an error channel in terms of throughput. We model the performance of the CFB in terms of application‐level throughput and derive the number of stages needed to achieve the optimal throughput, under a given error rate in an error channel. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT Network security is an important area in computer science. Although great efforts have already been made regarding security problems, networks are still threatened by all kinds of potential attacks, which may lead to huge damage and loss. Log files are main sources for security analysis. However, log files are not user friendly. It is laborious work to obtain useful information from log files. Compared with log files, visualization systems designed for security purposes provide more perceptive and effective sources for security analysis. Most security visualization systems are based on log files. In this paper, we provide a survey on visualization designs for computer network security. In this survey, we looked into different security visual analytics, and we organized them into five categories. Copyright © 2011 John Wiley & Sons, Ltd.

ABSTRACT With the advancement of computer and information technology, cyber crime is now becoming one of the most significant challenges facing law enforcement organizations. Cyber crimes are generally referred as criminal activities that use computers or networks. An understanding of the characteristics and nature of cyber crimes is important in helping research communities find ways to effectively prevent them. Most existing research focuses more on attacks and attack models, including either actual attacks or imaginary/possible attacks over all layers of networks or computers, but there has been less work carried out on a comprehensive survey of cyber crimes. This paper provides a survey of cyber crimes that have actually occurred. First, cyber crimes in the digital world are compared with crimes in the physical world. Then, cyber crimes are categorized according to the roles of computers or networks. Furthermore, we also notice that some cyber crimes are actually traditionally non‐cyber crimes that are facilitated by computers or networks. It is surprising that there are so many recurrent cyber crimes. More efforts are needed to protect people from cyber crimes. Copyright © 2011 John Wiley & Sons, Ltd.

The multihop routing in wireless sensor networks (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful or even devastating attacks against the routing protocols, including sinkhole attacks, wormhole attacks, and Sybil attacks. The situation is further aggravated by mobile and harsh network conditions. Traditional cryptographic techniques or efforts at developing trust-aware routing protocols do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multihop routing, we have designed and implemented TARF, a robust trust-aware routing framework for dynamic WSNs. Without tight time synchronization or known geographic information, TARF provides trustworthy and energy-efficient route. Most importantly, TARF proves effective against those harmful attacks developed out of identity deception; the resilience of TARF is verified through extensive evaluation with both simulation and empirical experiments on large-scale WSNs under various scenarios including mobile and RF-shielding network conditions. Further, we have implemented a low-overhead TARF module in TinyOS; as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. Based on TARF, we also demonstrated a proof-of-concept mobile target detection application that functions well against an antidetection mechanism.

Abstract In this paper, we use a multiple recursive generator (MRG) to generate sequences of numbers with very long periods, i.e., pseudo‐random sequences. The MRG effectively constructs a block cipher which satisfies important quality requirements such as security, long period, randomness, and efficiency. We compare our approach with another lightweight block cipher based on a linear congruential generator (LCG) and analyze the efficiency in terms of the number of basic operations that are being performed. We also study the effects of using special classes of MRG which hold certain portability and efficiency properties, and analyze their advantages in this context. The proposed cipher is a lightweight cipher, which is very useful for resource limited resources such as sensor nodes in sensor networks, radio frequency identification (RFID) tags, etc. Copyright © 2010 John Wiley & Sons, Ltd.

The rapid development of wireless technology plays extremely important roles in monitoring and control related applications nowadays.This special issue aims at bringing together state-of-the-art contributions of wireless monitoring, control, actuator coordination as well as their co-designs.It is shown in this proposal that there are a number of potential contributors, as well as reviewers, with original research results to this special issue, and the guest editors are capable of managing the special issue.In recent years, the demand for wireless communications in many monitoring and control applications has grown tremendously, such as military, aerospace, industrial, commercial, environmental, and health monitoring, etc.Some new technologies like Zigbee, Wi-Fi, Mobile Robots, and Bluetooth have already made significant contribution to data acquisition.At the same time, there arise some new challenges to guarantee a highly reliable, accurate and fault-tolerant process.It is a critical issue to develop innovative approaches to deal with multi-variable, multi-space problem domains (detection, identification, tracking, data fusion, energy-efficiency, and fault-tolerant framework) as well as practical implementation in wireless monitoring and control application.The purpose of the special issue is to focus on the novel ways by which monitoring, detection, identification, coordination, and control schemes are applied in wireless monitoring and control applications.Specific areas of interest include (but are not limited to):

We present SensorTrust, a trust model to evaluate the trustworthiness of nodes in hierarchical wireless sensor networks, focusing on data integrity.

Anomaly detection has been actively investigated to enhance the security of wireless ad hoc networks. However, it also presents a difficulty on model determination, such as feature selection and algorithm parameter optimization. In this paper, we address the issue of parameter selection for one-class support vector machine (1-SVM) based anomaly detection. We have investigated the performance of existing approaches, and also proposed a skewness-based outlier generation approach for parameter selection in the 1-SVM based anomaly detection model