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MulAV: Multilevel and Explainable Detection of Android Malware with Data fusion 18th

MulAV: Multilevel and Explainable Detection of Android Malwa...

引用

18th International conference on algorithms and architectures for Parallel Processing (ICA3PP)

作者： Li, Qun Chen, Zhenxiang Yan, Qiben Wang, Shanshan Ma, Kun Shi, Yuliang Cui, Lizhen Univ Jinan Sch Informat Sci & Engn Jinan 250022 Shandong Peoples R China Shandong Prov Key Lab Network Based Intelligent C Jinan 250022 Shandong Peoples R China Univ Nebraska Lincoln NE USA Shandong Univ Jinan 250101 Shandong Peoples R China

ISBN: (纸本)9783030050634;9783030050627

With the popularization of smartphones, the number of mobile applications has grown substantially. However, many malware are emerging and thus pose a serious threat to the user's mobile phones. Malware detection has become a public concern that requires urgent resolution. In this paper, we propose MulAV, a multilevel and explainable detection method with data fusion. Our method obtain information from multiple levels (the APP source code, network traffic, and geospatial information) and combine it with machine learning method to train a model which can identify mobile malware with high accuracy and few false alarms. Experimental result shows that MulAV outperforms other anti-virus scanners and methods and achieves a detection rate of 97.8% with 0.4% false alarms. Furthermore, for the benefit of users, MulAV displays the explanation for each detection, thus revealing relevant properties of the detected malware.

关键词： Android malware detection Data fusion Multilevel Result explanation

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A multi-mission unattended ground sensor

A multi-mission unattended ground sensor

引用

conference on Unattended Ground sensor Technologies and applications iv

作者： Prado, G Succi, G Fitzgerald, J Clapp, D Gampert, R Martel, PO SenTech Inc Stoneham MA 02180 USA

ISBN: (纸本)0819444936

Technological advances in a number of fields have allowed SenTech to develop a highly capable Unattended Ground sensor (UGS) able to perform a number of critical missions such as ground and air vehicle surveillance, personnel detection and tracking and sniper localization. SenTech employs advanced signal processing techniques to detect, track and identify ground combat vehicles. Processing is done in a highly integrated processing module developed under DARPA's IUGS program. System integration to achieve a three-pound unit with a 15-day field life and long range VHF communications has been developed at SenTech. The first units of these sensors will be delivered in the first quarter of 2002. Extensive testing of the algorithms and software has been conducted over the last few years at a variety of government-sponsored tests and demonstrations. A Gateway unit has been developed which can manage the operation of an eight-sensor field and perform two-dimensional sensor fusion.

关键词： Unattended Ground sensor acoustic seismic detection localization classification

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Real time implementation of image alignment and fusion

Real time implementation of image alignment and fusion

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conference on Multisensor, Multisource Information fusion

作者： Dwyer, D Smith, M Dale, J Heather, J Octec Ltd Western Ctr Bracknell RG12 1RW Berks England

ISBN: (纸本)0819457981

Many modern imaging and surveillance systems contain more than one sensor. For example, most modern airborne imaging pods contain at least visible and infrared sensors. Often these systems have a single display that is only capable of showing data from either camera, and thereby fail to exploit the benefit of having simultaneous multi-spectral data available to the user. It can be advantageous to capture all spectral features within each image and to display a fused result rather than single band imagery. This paper discusses the key processes necessary for an image fusion system and then describes how they were implemented in a real-time, rugged hardware system. The problems of temporal and spatial misalignment of the sensors and the process of electronic image warping must be solved before the image data is fused. The techniques used to align the two inputs to the fusion system are described and a summary is given of our research into automatic alignment techniques. The benefits of different image fusion schemes are discussed and those that were implemented are described. The paper concludes with a summary of the real-time implementation of image alignment and image fusion by Octec and Waterfall Solutions and the problems that have been encountered and overcome.

关键词： image alignment image fusion real time image processing

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A mathematical framework for the optimization of rejection and ROC thresholds in the fusion of correlated sensor data

A mathematical framework for the optimization of rejection a...

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conference on Multisensor, Multisource Information fusion

作者： Laine, TI Bauer, KW USAF Inst Technol Dept Operat Sci Wright Patterson AFB OH 45433 USA

ISBN: (纸本)0819453579

In pattern recognition applications, significant costs can be associated with various decision options and a minimum acceptable level of confidence is often required. Combat target identification is one example where the incorrect labeling of Targets and Non-targets incurs substantial costs: yet, these costs may be difficult to quantify. One way to increase decision confidence is through fusion of data from multiple sources or from multiple looks through time. Numerous methods have been published to determine optimal rules for the fusion of decision labels or to determine the Bayes' optimal decision if prior and posterior probabilities along with decision costs can be accurately estimated. This paper introduces a mathematical framework to optimize multiple decision thresholds subject to a decision maker's preferences. when a continuous measure of class membership is available. Decision variables may include rejection thresholds to specify non-declaration regions and ROC thresholds to explore viable trite positive and false positive Target classification rates, where the feasible space can be partially visualized by a 3D ROC surface. This methodology yields an optimal class declaration rule subject to decision maker preferences without using explicit costs associated with each type of decision. Some properties of this optimization framework are shown for Gaussian distributions representing Target and Non-target classes with various prior probabilities and correlation levels between simulated multiple sensor looks.

关键词： combat identification (CID) fusion receiver operating characteristic (ROC). 3-D ROC surface automatic taraet recosinition (ATR) performance rejection

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Whose Data are Reliable: sensor Declared Data Reliability 19

Whose Data are Reliable: Sensor Declared Data Reliability

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19th International conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Shafin, Sakib Shahriar Karmakar, Gour Mareels, iven Balasubramanian, Venki Kolluri, Ramachandra Rao Federat Univ Australia Ctr Smart Analyt CSA Ballarat Vic 3350 Australia Federat Univ Australia Inst Innovat Sci & Sustainabil Ballarat Vic 3350 Australia IBM Australia Pty Ltd IBM Consulting St Leonards Australia

ISBN: (纸本)9798350336672

sensor data is susceptible to faults, noise, and malicious attacks, posing a significant operational and security threat. Therefore, ensuring reliability of sensor data is critical for real-time monitoring systems. Prior research on sensor data reliability relies on edge or upper-layer devices for data fusion from multiple sensors, employing architectures with major overheads and latency due to transmission and storage demands. An alternative approach is to have the sensor estimate and declare its own reliability. While some methods involve sensors computing data confidence and including it in payloads, limitations arise in the absence of neighboring sensor data, and communication overheads are incurred. To address this problem, this paper proposes an innovative approach to enhance the reliability of sensor data using an intelligent self-declaration process. Proposed reliability estimation is evaluate with three lightweight estimation algorithms, namely, Kalman Filter, Holt-Winters Method, and Mahalanobis Distance using sensor's historical data. The reliability level is then added to the three reserved bits of a TCP packet header which results in zero additional overhead. Experiments conducted using real-world sensor data (from water quality monitoring systems) obtained from our IoT lab demonstrate the effectiveness of our proposal and the potential for application in real-world sensor-based applications.

关键词： Reliability

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Neural methods based on modified reputation rules for detection and identification of intrusion attacks in wireless ad hoc sensor networks

Neural methods based on modified reputation rules for detect...

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conference on Evolutionary and Bio-Inspired Computation - Theory and applications iv

作者： Hortos, William S. ACERT Orlando FL 32819 USA

ISBN: (纸本)9780819481689

Determining methods to secure the process of data fusion against attacks by compromised nodes in wireless sensor networks (WSNs) and to quantify the uncertainty that may exist in the aggregation results is a critical issue in mitigating the effects of intrusion attacks. Published research has introduced the concept of the trustworthiness (reputation) of a single sensor node. Reputation is evaluated using an information-theoretic concept, the Kullback-Leibler (KL) distance. Reputation is added to the set of security features. In data aggregation, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As aggregate information is disseminated along routes to the sink node(s), its corresponding opinion is propagated and regulated by Josang's belief model. By applying subjective logic on the opinion to manage trust propagation, the uncertainty inherent in aggregation results can be quantified for use in decision making. The concepts of reputation and opinion are modified to allow their application to a class of dynamic WSNs. Using reputation as a factor in determining interim aggregate information is equivalent to implementation of a reputation-based security filter at each processing stage of data fusion, thereby improving the intrusion detection and identification results based on unsupervised techniques. In particular, the reputation-based version of the probabilistic neural network (PNN) learns the signature of normal network traffic with the random probability weights normally used in the PNN replaced by the trust-based quantified reputations of sensor data or subsequent aggregation results generated by the sequential implementation of a version of Josang's belief model. A two-stage, intrusion detection and identification algorithm is implemented to overcome the problems of large sensor data loads and resource restrictions in WSNs. Performance of the two-stage algorithm is assessed in simulations of WSN sce

关键词： Cross-layer features intrusion detection and identification Josang's belief model Kullback-Leibler (KL) distance mobile software agents recurrent neural networks reputation quantification unsupervised learning algorithms wireless ad hoc sensor networks

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An Updatable Key Management Scheme for Underwater Wireless sensor Networks 23rd

An Updatable Key Management Scheme for Underwater Wireless S...

引用

23rd International conference on algorithms and architectures for Parallel Processing (ICA3PP)

作者： Guan, Zhiyun Wu, Junhua Li, Guangshun Wang, Tielin Qufu Normal Univ Sch Comp Sci Rizhao 276826 Peoples R China

ISBN: (纸本)9789819708581;9789819708598

In recent years, underwater wireless sensor networks (UWSNs) have emerged as promising network model for various marine exploration, detection, and protection applications. The problems of frequent node movement and high battery energy consumption have led to the design of terrestrial wireless sensor networks (TWSNs) that are not applicable to underwater. There is an urgent need to develop new and efficient security mechanisms. On the other hand, nodes drift with the current. It is extremely challenging to balance the energy constraints while ensuring secure and private data transfer between moving nodes. In this paper, we propose an updatable key management scheme for UWSNs. A group mobility model suitable for underwater is used in a network model based on a hierarchical structure. We process the communication through a symmetric polynomial-based key pre-distribution scheme. In addition, we design a dynamic key update scheme based on reverse hash chains to extend the network security survival time. The obtained results show that our approach saves storage and communication overhead while providing highly secure connectivity and good resistance to node capture.

关键词： Underwater wireless sensor networks (UWSNs) Key management Security Symmetric polynomials

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An Overview of Factors Influencing the Mass Adoption of Self-Driving Vehicles 9

An Overview of Factors Influencing the Mass Adoption of Self...

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IEEE 9th International conference on Power Electronics Systems and applications (PESA)

作者： Li, Zilin Cheng, Ka Wai Eric Chan, Kevin K. W. Hong Kong Polytech Univ Dept Elect Engn Power Elect Res Ctr Hong Kong Peoples R China

ISBN: (纸本)9781665486682

A self-driving vehicle used to be found in science fiction but would promisingly and gradually become a reality in our daily life in the foreseeable future. Self-driving or autonomous vehicles can bring about disruptive changes to the current transportation system, commuting ways, the concept of vehicle ownership, risk management, legal liability, regulations, urban planning, etc. A highly/fully self-driving vehicle is one of the most complex man-made systems and involves various aspects of modern society. Nevertheless, the public seems to lack a clear enough understanding of self-driving vehicles. To further the development of self-driving technologies, it is necessary to develop a comprehensive understanding of multifaceted factors that could hinder the mass adoption of self-driving vehicles. Therefore, this paper intends to present an overview of some technical factors that could influence the advancement of self-driving vehicles. First, this paper reviews state-of-the-art architectures of a self-driving vehicle. Various sensor technologies are followed with a discussion of their limitations. As two essential software subsystems for realizing a self-driving vehicle, the perception and decision-making systems are presented with an overview of their major tasks and challenges. This paper is concluded with a summary of the technical challenges, being a helpful resource for engineers, the public, policy-makers, and social researchers.

关键词： autonomous vehicles architectures camera Lidar overview Radar self-driving car sensor technologies sensor fusion algorithms

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Adaptive resource allocation architecture applied to line tracking

Adaptive resource allocation architecture applied to line tr...

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sensor fusion: architectures, algorithms, and applications iv

作者： Owen, Mark W. Pace, Donald W. SPAWAR Systems Cent San Diego United States

Current line tracker approaches only address resources in the form of memory and processing time requirements. These architecture approaches limit the amount of complex algorithmic processing a line tracker may perform to provide the correct solution. Past approaches include single-hypothesis Kalman filter-based tracking and a-b tracking. Both approaches assume a real time recursive data processing requirement, and are fairly memory intensive. These architectures are not expandable. Recent research has demonstrated the benefits of a multiple hypothesis, multiple model sonar line tracking solution, achieved at significant computational cost. We have developed an adaptive architecture that trades computational resources for algorithm complexity based on environmental conditions. A Fuzzy Logic Rule-Based approach is applied to adaptively assign algorithmic resources to meet system requirements. The resources allocated by the Fuzzy Logic algorithm include (a) the number of hypotheses permitted (yielding multi-hypothesis and single-hypothesis modes), (b) the number of signal models to use (yielding an interacting multiple model capability), (c) a new track likelihood for hypothesis generation, (d) track attribute evaluator activation (for signal to noise ratio, frequency bandwidth, and others), and (e) adaptive cluster threshold control. Algorithm allocation is driven by a comparison of current throughput rates to a desired real time rate. The Fuzzy Logic Controlled (FLC) line tracker, a single hypothesis line tracker, and a multiple hypothesis line tracker are compared on real sonar data. System resource usage results demonstrate the utility of the FLC line tracker.

关键词： sensor data fusion

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Investigation of target tracking performance for unattended ground sensor networks employing Distributed Cluster Management

Investigation of target tracking performance for unattended ...

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conference on Multisensor, Multisource Information fusion

作者： Stelzig, Chad A. Essawy, Magdi A. Minor, Sharon Gen Dynam Adv Informat Syst 8800 Queen Ave S Bloomington MN 55431 USA US Army CECOM Ctr Night Vis & Electroopt Ft Belvoir VA 22060 USA

ISBN: (纸本)0819462985

Interest in the distribution of processing in unattended ground sensing (UGS) networks has resulted in new technologies and system designs targeted at reduction of communication bandwidth and resource consumption through managed sensor interactions. A successful management algorithm should not only address the conservation of resources, but also attempt to optimize the information gained through each sensor interaction so as to not significantly deteriorate target tracking performance. This paper investigates the effects of Distributed Cluster Management (DCM) on tracking performance when operating in a deployed UGS cluster. Originally designed to reduce communications bandwidth and allow for sensor field scalability, the DCM has also been shown to simplify the target tracking problem through reduction of redundant information. It is this redundant information that in some circumstances results in secondary false tracks due to multiple intersections and increased uncertainty during track initiation periods. A combination of field test data playback and Monte Carlo simulations are used to analyze and compare the performance of a distributed UGS cluster to that of an unmanaged centralized cluster.

关键词： unattended ground sensors Distributed Cluster Management target tracking

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