Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

People tracking by cooperative fusion of RADAR and camera sensors

Accurate 3D tracking of objects from monocular camera poses challenges due to the loss of depth during projection. Although ranging by RADAR has proven effective in highway environments, people tracking remains beyond the capability of single sensor systems. In this paper, we propose a cooperative RADAR-camera fusion method for people tracking on the ground plane. Using average person height, joint detection likelihood is calculated by back-projecting detections from the camera onto the RADAR Range-Azimuth data. Peaks in the joint likelihood, representing candidate targets, are fed into a Particle Filter tracker. Depending on the association outcome, particles are updated using the associated detections (Tracking by Detection), or by sampling the raw likelihood itself (Tracking Before Detection). Utilizing the raw likelihood data has the advantage that lost targets are continuously tracked even if the camera or RADAR signal is below the detection threshold. We show that in single target, uncluttered environments, the proposed method entirely outperforms camera-only tracking. Experiments in a real-world urban environment also confirm that the cooperative fusion tracker produces significantly better estimates, even in difficult and ambiguous situations

The Complementary Brain: From Brain Dynamics To Conscious Experiences

How do our brains so effectively achieve adaptive behavior in a changing world? Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within each stream and parallel interactions between streams create coherent behavioral representations that overcome the complementary deficiencies of each stream and support unitary conscious experiences. This perspective suggests how brain design reflects the organization of the physical world with which brains interact, and suggests an alternative to the computer metaphor suggesting that brains are organized into independent modules. Examples from perception, learning, cognition, and action are described, and theoretical concepts and mechanisms by which complementarity is accomplished are summarized.Defense Advanced Research Projects and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (ITI-97-20333); Office of Naval Research (N00014-95-1-0657

Noise uncertainty effect on multi-channel cognitive radio networks

Achieving high throughput is the most important goal of cognitive radio networks. The main process in cognitive radio is spectrum sensing that targets getting vacant channels. There are many sensing methods like matched filter, feature detection, interference temperature and energy detection which is employed in the proposed system; however, energy detection suffers from noise uncertainty. In this paper a study of throughput under noise fluctuation effect is introduced. The work in this paper proposes multi-channel system; the overall multi-channel throughput is studied under noise fluctuation effect. In addition, the proficiency of the network has been examined under different number of channels and sensing time with noise uncertainty

The Complementary Brain: A Unifying View of Brain Specialization and Modularity

Defense Advanced Research Projects Agency and Office of Naval Research (N00014-95-I-0409); National Science Foundation (ITI-97-20333); Office of Naval Research (N00014-95-I-0657