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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.
2021 IEEE Photovoltaic Specialists Conference (PVSC)
Photovoltaic materials, devices, systems and related science and technology
2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting
The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science
OCEANS 2020 - SINGAPORE
An OCEANS conference is a major forum for scientists, engineers, and end-users throughout the world to present and discuss the latest research results, ideas, developments, and applications in all areas of oceanic science and engineering. Each conference has a specific theme chosen by the conference technical program committee. All papers presented at the conference are subsequently archived in the IEEE Xplore online database. The OCEANS conference comprises a scientific program with oral and poster presentations, and a state of the art exhibition in the field of ocean engineering and marine technology. In addition, each conference can have tutorials, workshops, panel discussions, technical tours, awards ceremonies, receptions, and other professional and social activities.
All fields of satellite, airborne and ground remote sensing.
Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
2011 Carnahan Conference on Security Technology, 2011
The UK Home Office Centre for Applied Science & Technology (CAST)1, in partnership with the Centre for the Protection of National Infrastructure (CPNI), has been developing a suite of standards for the testing of Perimeter Intruder Detection Systems (PIDS). This paper describes the development of the fifth standard in the suite, which is a methodology for the evaluation of a ...
2018 Innovations in Intelligent Systems and Applications (INISTA), 2018
Intrusion detection systems define an important and dynamic research area for cybersecurity. The role of Intrusion Detection System within security architecture is to improve a security level by identification of all malicious and also suspicious events that could be observed in computer or network system. One of the more specific research areas related to intrusion detection is anomaly detection. Anomaly-based ...
2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), 2010
Network intrusion detection systems have become a crucial issue for computer systems security infrastructures. Different methods and algorithms are developed and proposed in recent years to improve intrusion detection systems. The most important issue in current systems is that they are poor at detecting novel anomaly attacks. These kinds of attacks refer to any action that significantly deviates from the ...
2009 International Conference on Networks Security, Wireless Communications and Trusted Computing, 2009
Recent years have seen a growing interest in computational methods based upon natural phenomena with biologically inspired techniques. The use of immune mechanisms in intrusion detection is an appealing concept. This paper reviews and assesses the analogy between the human immune system and intrusion detection systems. We show how immune metaphors can be used efficiently to build intrusion detection systems ...
2010 2nd IEEE International Conference on Information Management and Engineering, 2010
The paper introduces cluster ensemble for intrusion detection systems. Intrusion detection is a hard problem which is studied by many researchers and is a research hot pot. The idea is that we use cluster ensemble to decide which net-event is normal or unnormal. In this paper there are three works presented. First, we state a hard cluster ensemble method. Second, ...
Multiple Sensor Fault Detection and Isolation in Complex Distributed Dynamical Systems
Noise Enhanced Information Systems: Denoising Noisy Signals with Noise
Low Power Image Recognition: The Challenge Continues
Fireside Chat: Key Opinion Leaders on Pre-Symptomatic Illness Detection - IEEE EMBS at NIH, 2019
ASC-2014 SQUIDs 50th Anniversary: 4 of 6 - Keiji Enpuku
A Recurrent Crossbar of Memristive Nanodevices Implements Online Novelty Detection - Christopher Bennett: 2016 International Conference on Rebooting Computing
Fragility of Interconnected Cyber-Physical Systems - Marios M. Polycarpou - WCCI 2016
An FPGA-Quantum Annealer Hybrid System for Wide-Band RF Detection - IEEE Rebooting Computing 2017
Keynote on Machine Learning: Andrea Goldsmith - B5GS 2019
Digital Neuromorphic Design of a Liquid State Machine for Real-Time Processing - Nicholas Soures: 2016 International Conference on Rebooting Computing
Non-Invasive Techniques for Monitoring Chronic Heart Failure - Harry Silber - IEEE EMBS at NIH, 2019
Multi-Function VCO Chip for Materials Sensing and More - Jens Reinstaedt - RFIC Showcase 2018
International Workshop on NFV, SDN, & LPWAN: HPSR 2020 Virtual Conference
IMS 2011-100 Years of Superconductivity (1911-2011) - Existing and Emerging RF Applications of Superconductivity
2011 IEEE Dennis J. Picard Medal for Radar Technologies and Applications - James M. Headrick
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 5 of 7 - SQUID Instrumentation for Early Cancer Diagnostics
Implantable, Insertable and Wearable Micro-optical Devices for Early Detection of Cancer - Plenary Speaker, Christopher Contag - IPC 2018
Analytics for Anomaly detection & Classification | DSBC 2020
Developing Automated Analysis Tools for Space/Time Sidechannel Detection - IEEE SecDev 2016
The UK Home Office Centre for Applied Science & Technology (CAST)1, in partnership with the Centre for the Protection of National Infrastructure (CPNI), has been developing a suite of standards for the testing of Perimeter Intruder Detection Systems (PIDS). This paper describes the development of the fifth standard in the suite, which is a methodology for the evaluation of a category of PIDS known as Wide Area Detection Systems (WADS). WADS are radically different to the PIDS covered by standards to date. Conventional PIDS have an essentially linear detection zone; whereas WADS provide surveillance over an extensive area, rather than along a line. Their range tends to be substantially greater than that of other PIDS; and system functionality is more sophisticated. In practice a WADS may be deployed to protect a large area, including a range of topographical features and obstacles (such as buildings). This complicates meaningful evaluation of products on a comparative basis, and makes setting performance criteria non- trivial compared to conventional PIDS. To address this, it is proposed that performance evaluations are carried out over as clear and benign an area as possible. Within this clear area evaluation, additional performance criteria not usually associated with linear PIDS will be assessed, such as maximum / minimum detection range, detection consistency, plot accuracy and the ability to “mask-out” areas within the detection envelope. In addition, to take account of real-world operational factors, such as undulating terrain, vegetation and man-made obstacles; time-to-alarm; and camera cueing, systems will also be assessed over a cluttered test area. However, relative performance in such an environment will be assessed on an indicative basis only, as it is not practicable to apply pure performance indicators in this case. In summary, it is proposed that rigorous quantitative assessment of performance will be carried out over a clear area of ground. This will be supplemented by indicative comparison of performance over a cluttered test area to demonstrate system behaviour in a more realistic setting, and to enable more sophisticated aspects of functionality to be assessed. This dual- faceted evaluation will support a guidance-led approach to the selection and use of WADS by UK Government and Critical National Infrastructure end users.
Intrusion detection systems define an important and dynamic research area for cybersecurity. The role of Intrusion Detection System within security architecture is to improve a security level by identification of all malicious and also suspicious events that could be observed in computer or network system. One of the more specific research areas related to intrusion detection is anomaly detection. Anomaly-based intrusion detection in networks refers to the problem of finding untypical events in the observed network traffic that do not conform to the expected normal patterns. It is assumed that everything that is untypical/anomalous could be dangerous and related to some security events. To detect anomalies many security systems implements a classification or clustering algorithms. However, recent research proved that machine learning models might misclassify adversarial events, e.g. observations which were created by applying intentionally non-random perturbations to the dataset. Such weakness could increase of false negative rate which implies undetected attacks. This fact can lead to one of the most dangerous vulnerabilities of intrusion detection systems. The goal of the research performed was verification of the anomaly detection systems ability to resist this type of attack. This paper presents the preliminary results of tests taken to investigate existence of attack vector, which can use adversarial examples to conceal a real attack from being detected by intrusion detection systems.
Network intrusion detection systems have become a crucial issue for computer systems security infrastructures. Different methods and algorithms are developed and proposed in recent years to improve intrusion detection systems. The most important issue in current systems is that they are poor at detecting novel anomaly attacks. These kinds of attacks refer to any action that significantly deviates from the normal behaviour which is considered intrusion. This paper proposed a model to improve this problem based on data mining techniques. Apriori algorithm is used to predict novel attacks and generate real-time rules for firewall. Apriori algorithm extracts interesting correlation relationships among large set of data items. This paper illustrates how to use Apriori algorithm in intrusion detection systems to cerate a automatic firewall rules generator to detect novel anomaly attack. Apriori is the best-known algorithm to mine association rules. This is an innovative way to find association rules on large scale.
Recent years have seen a growing interest in computational methods based upon natural phenomena with biologically inspired techniques. The use of immune mechanisms in intrusion detection is an appealing concept. This paper reviews and assesses the analogy between the human immune system and intrusion detection systems. We show how immune metaphors can be used efficiently to build intrusion detection systems to protect computer networks. The paper concludes that the design of a novel intrusion detection systems based on the human immune system is promising for future intrusion detection systems.
The paper introduces cluster ensemble for intrusion detection systems. Intrusion detection is a hard problem which is studied by many researchers and is a research hot pot. The idea is that we use cluster ensemble to decide which net-event is normal or unnormal. In this paper there are three works presented. First, we state a hard cluster ensemble method. Second, the model of cluster ensemble for IDS is illustrated in detail. Third, some UCI datasets and KDD99 dataset are chosen for the experiments, and the results show that cluster ensemble for IDS is better than any single algorithm or model.
Pattern-Matching algorithms are vastly being implemented in the NIDS (Network Intrusion Detection Systems) nowadays in order to keep a check on any malicious activities of any trespasser. With an increase in Network traffic with time, the pattern-matching algorithms should be quick so as to keep a check and keep up with the network speed. Hence, it is very important to choose the right algorithm for our purpose in order to get the work done with ease and in a quick manner. Although there are many pattern-matching algorithms that exist but we decided to take into consideration some majorly popular ones which include: Naive approach, Knuth-MorrisPratt algorithm, RabinKarp Algorithm and also the trie data structure which is still not that popular in this field but we believe can be helpful in the future. The above mentioned algorithms are compared in order to check which of them is most efficient in pattern/Intrusion detection. Pcap files have been used as datasets in order to determine the efficiency of the algorithm by taking into consideration their running times respectively.
With the increasing number of computers being connected to the Internet, security of an information system has never been more urgent. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. This is the reason of an entire area of research, called Intrusion Detection Systems (IDS). Anomaly systems detect intrusions by searching for an abnormal system activity. But the main problem of anomaly detection IDS is that; it is very difficult to build, because of the difficulty in defining what is normal and what is abnormal. Neural network with its ability of learning has become one of the most promising techniques to solve this problem. This paper presents an overview of neural networks and their use in building anomaly intrusion systems.
Security is vital to computer networks. IDSs (intrusion detection systems) are one of the important building blocks of a secure, reliable network and are used widely along with the other security programs and concepts. As the time passes, their importance becomes clearer. Recently, there have been some interesting researches on biological immune systems as a model for intrusion detection. In this article we describe IDS, including an overview of its types, techniques, and explore different IDS designs based on biologically inspired artificial intelligence concept: artificial immune system (AIS), which can be a future direction in IDS designing field. We also discuss some newer topics in this field like danger theory.
Intrusion detection systems constitute a crucial cornerstone in securing computer networks especially after the recent advancements in attacking techniques. IDSes can be categorized according to the nature of detection into two major categories: signature-based and anomaly-based. In this paper we present KBIDS, a kernel-based method for an anomaly-based IDS that tries to cluster the training data to be able to classify the test data correctly. The method depends on the K-Means algorithm that is used for clustering. Our experiments show that the accuracy of detection of KBIDS increases exponentially with the number of clusters. However, the time taken to classify the given test data increase linearly with the number of clusters. It can be derived from the results that 16 clusters are sufficient to achieve an acceptable error rate while keeping the detection delay in bounds.
This work proposes an application ontology who is capable of formally represent the concepts present in the domain of Information Security together with the intrusion detection systems and case-based reasoning. The ontology was evaluated through the development of an IDS capable of detect computers networks attacks and recommend actions to such attacks. The results showed that the developed IDS presented good effectiveness in the detecting attacks, and so it is concluded that the proposed ontology conceptualizes properly the domain concepts and task.
IEEE Draft Standard for Information technology--Telecommunications and information exchange between systems--Local and metropolitan area networks--Specific requirements Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications Amendment: Physical Layer and Management Parameters for Serial 40 Gb/s Ethernet Operation Over Single Mode Fiber
The scope of this project is to add a single-mode fiber Physical Medium Dependent (PMD) option for serial 40 Gb/s operation by specifying additions to, and appropriate modifications of, IEEE Std 802.3-2008 as amended by the IEEE P802.3ba project (and any other approved amendment or corrigendum).