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Investigation of Android Malware Using Deep Learning Approach

Intelligent Automation & Soft computing 2023年第2期35卷 2413-2429页

作者： V.Joseph Raymond R.Jeberson Retna Raj Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119TamilnaduIndia School of Computing SRM Institute of Science and TechnologyChennai603203TamilnaduIndia

In recent days the usage of android smartphones has increased exten-sively by *** are several applications in different categories bank-ing/ﬁnance,social engineering,education,sports andﬁtness,and many more *** android stack is more vulnerable compared to other mobile plat-forms like IOS,Windows,or Blackberry because of the open-source *** the Existing system,malware is written using vulnerable system calls to bypass signature detection important drawback is might not work with zero-day exploits and stealth *** attackers target the victim with various attacks like adware,backdoor,spyware,ransomware,and zero-day exploits and create threat hunts on the day-to-day *** the existing approach,there are various tradi-tional machine learning classiﬁers for building a decision support system with limitations such as low detection rate and less feature *** important contents taken for building model from android applications like Intent Filter,Per-mission Signature,API Calls,and System commands are taken from the manifestﬁ*** function parameters of various machine and deep learning classiﬁers like Nave Bayes,k-Nearest Neighbors(k-NN),Support Vector Machine(SVM),Ada Boost,and Multi-Layer Perceptron(MLP)are done for effective *** our pro-posed work,we have used an unsupervised learning multilayer perceptron with multiple target labels and built a model with a better accuracy rate compared to logistic regression,and rank the best features for detection of applications and clas-sify as malicious or benign can be used as threat model by online antivirus scanners.

关键词： Android application permissions multilayer perception relief scoring

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Ultra-low power MoS2 optoelectronic synapse with wavelength sensitivity for color target recognition

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science China(Information sciences) 2025年第4期68卷 187-196页

作者： Bo WEI Yabo CHEN Xiaotong HAN Yan KANG Bujia LIANG Cheng LI Xiaokuo YANG Liang FANG Yuanxi PENG Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology Fundamentals Department Air Force Engineering University College of Advanced Interdisciplinary Studies National University of Defense Technology Institute of Quantum Information Science and Technology College of ScienceNational University of Defense Technology College of Computer National University of Defense Technology

Optoelectronic synapses that integrate visual perception and pre-processing hold significant potential for neuromorphic vision systems（NVSs）. However, due to a lack of wavelength sensitivity, existing NVS mainly focuses on gray-scale image processing, making it challenging to recognize color images. Additionally, the high power consumption of optoelectronic synapses, compared to the 10 fJ energy consumption of biological synapses, limits their broader application. To address these challenges, an energy-efficient NVS capable of color target recognition in a noisy environment was developed,utilizing a MoS2optoelectronic synapse with wavelength sensitivity. Benefiting from the distinct photon capture capabilities of 450, 535, and 650 nm light, the optoelectronic synapse exhibits wavelength-dependent synaptic plasticity, including excitatory postsynaptic current（EPSC）, paired-pulse facilitation（PPF）, and long-term plasticity（LTP）. These properties can effectively mimic the visual memory and color discrimination functions of the human vision system. Results demonstrate that the NVS, based on MoS2optoelectronic synapses, can eliminate the color noise at the sensor level, increasing color image recognition accuracy from 50% to 90%. Importantly, the optoelectronic synapse operates at a low voltage spike of0.0005 V, consuming only 0.075 fJ per spike, surpassing the energy efficiency of both existing optoelectronic and biological synapses. This ultra-low power, color-sensitive device eliminates the need for color filters and offers great promise for future deployment in filter-free NVS.

关键词： optoelectronic synapse neuromorphic vision system color recognition 2D materials image pre-processing

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Fully Distributed Nash Equilibrium Seeking for High-Order Players With Actuator Limitations

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1434-1444页

作者： Maojiao Ye Qing-Long Han Lei Ding Shengyuan Xu the School of Automation Nanjing University of Science and TechnologyNanjing 210094China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the Institute of Advanced Technology Nanjing University of Posts and TelecommunicationsNanjing 210023China

This paper explores the problem of distributed Nash equilibrium seeking in games, where players have limited knowledge on other players' actions. In particular, the involved players are considered to be high-order integrators with their control inputs constrained within a pre-specified region. A linear transformation for players' dynamics is firstly utilized to facilitate the design of bounded control inputs incorporating multiple saturation functions. By introducing consensus protocols with adaptive and time-varying gains, the unknown actions for players are distributively estimated. Then, a fully distributed Nash equilibrium seeking strategy is exploited, showcasing its remarkable properties: (1) ensuring the boundedness of control inputs;(2) avoiding any global information/parameters;and (3) allowing the graph to be directed. Based on Lyapunov stability analysis, it is theoretically proved that the proposed distributed control strategy can lead all the players' actions to the Nash equilibrium. Finally, an illustrative example is given to validate effectiveness of the proposed method.

关键词： Actuator limitation directed networks games Nash equilibrium

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Characterization of Exact One-Query Quantum Algorithms for Partial Boolean Functions

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Journal of computer science & technology 2023年第6期38卷 1423-1430页

作者：叶泽坤李绿周 Institute of Quantum Computing and Computer Theory School of Computer Science and EngineeringSun Yat-sen UniversityGuangzhou 510006China Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen UniversityGuangzhou 510006China

The query model(or black-box model)has attracted much attention from the communities of both classical and quantum ***,quantum advantages are revealed by presenting a quantum algorithm that has a better query complexity than its classical *** the history of quantum algorithms,the Deutsch algorithm and the Deutsch-Jozsa algorithm play a fundamental role and both are exact one-query quantum *** leads us to con-sider the problem:what functions can be computed by exact one-query quantum algorithms?This problem has been ad-dressed in the literature for total Boolean functions and symmetric partial Boolean functions,but is still open for general partial Boolean ***,in this paper,we continue to characterize the computational power of exact one-query quantum algorithms for general partial Boolean ***,we present several necessary and sufficient conditions for a partial Boolean function to be computed by exact one-query quantum ***,inspired by these conditions,we discover some new representative functions that can be computed by exact one-query quantum algorithms but have an essential difference from the already known ***,it is worth pointing out that before our work,the known func-tions that can be computed by exact one-query quantum algorithms are all symmetric functions and the quantum algo-rithm used is essentially the Deutsch-Jozsa algorithm,whereas the functions discovered in this paper are generally asym-metric and new algorithms to compute these functions are ***,this expands the class of functions that can be computed by exact one-query quantum algorithms.

关键词： quantum computing quantum query complexity quantum algorithm

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Blockchain Security Using Q-Pragmatic-Sensitive Feature Analysis to Preserve Privacy 3

Blockchain Security Using Q-Pragmatic-Sensitive Feature Anal...

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3rd IEEE International Conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Punithavathi, S. Jeyalaksshmi, S. Vels Institute Of Science Technology & Advanced Studies Department Of Computer Science Chennai India School Of Computing Science Vels Institute Of Science Technology & Advanced Studies Department Of Information Technology Chennai India

ISBN: (纸本)9798350318609

Healthcare data contains large amounts of personal information and is privacy sensitive. The healthcare sector needs privacy protection to keep private and sensitive information safe from unauthorized access. Security problems are raised by fundamental sharing difficulties involving personal information setting to securely forecast sensitive medical data using blockchain technology to address this issue. To solve the problem issue, propose a quasi-sensitive identification of blockchain security using tried-and-true partition fold padding encryption (PFPE) to improve the security of healthcare transactions. The Q-Pragmatic-Sensitive Feature Analysis (QPSFA) determines the terms related to sensitive privacy features. Finally, the Provable Fold Padding Encryption, and the authentication procedure is completed by using an Access Verification-based role to verify it. To ensure that, in a blockchain, the private data are cleansed and placed into data blocks. This suggests that the proposed system outperforms high accuracy up to 90%, as well security up to 94 % high insecurity compared to previous approaches regarding sensitivity and specificity rate performance and prediction accuracy. © 2024 IEEE.

关键词： Blockchain

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Digital twin empowered cooperative trajectory planning of platoon vehicles for collision avoidance with unexpected obstacles

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Digital Communications and Networks 2024年第6期10卷 1666-1676页

作者： Hao Du Supeng Leng Jianhua He Kai Xiong Longyu Zhou School of Information&Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China School of Computer Science and Electronic Engineering University of EssexColchester CO43SQUnited Kingdom Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110China

Road obstacles that unexpectedly appear due to vehicle breakdowns and accidents are major causes of fatal road *** Autonomous Vehicles(CAVs)can be used to avoid collisions to ensure road safety through cooperative sensing and ***,the collision avoidance performance of CAVs with unexpected obstacles has not been studied in the existing *** this paper,we first design a platoon-based collision avoidance framework for *** this framework,we deploy a Digital Twin(DT)system at the head vehicle in a platoon to reduce communication overhead and decision-making delay based on a proposed trajectory planning *** addition,a DT-assistant system is deployed on the assistant vehicle to monitor vehicles out of the sensing range of the head vehicle for the maintenance of the DT *** this case,the transmission frequency of kinetic states of platoon members can be reduced to ensure low-overhead ***,we design a variable resource reservation interval that can ensure DT synchronization between DT and the assistant system with high *** further improve road safety,an urgency level-based trajectory planning algorithm is proposed to avoid unexpected obstacles considering different levels of emergency *** results show that our DT system-based scheme can achieve significant performance gains in unexpected obstacle *** to the existing schemes,it can reduce collisions by 95%and is faster by about 10%passing by the unexpected obstacle.

关键词： Platoon driving Cooperative trajectory planning Digital twin Obstacle avoidance

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Secure Block Chain-Based Healthcare Sensitive Data Prediction Using Pragmatic Quasi-Identifiers in a Decentralized Cloud Environment

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SN computer science 2024年第1期5卷 41页

作者： Punithavathi, S. Jeyalaksshmi, S. Department of Computer Science Vels Institute of Science Technology and Advanced Studies Chennai India Hindustan College of Arts and Science Chennai India Department of Information Technology School of Computing Science Vels Institute of Science Technology and Advanced Studies Chennai India

Security is essential for all facts, information sharing around the internet and maintaining personalized information. In recent days, the healthcare industry needs privacy-preserving to keep personalized data from others containing sensitive information. Due to increasing security breaches, fundamental sharing problems with personalized details shared on the internet lead to security problems. To resolve this problem, we propose a Secure Blockchain-based Healthcare-sensitive data prediction using a Pragmatic quasi identifier in a decentralized cloud environment. Pragmatic quasi-sensitivity Identification (PQSI) based Privacy-preserving for securing personalized records Using Hyper Recurrent feature classification for improved cloud security. Initially, the sensitivity fitness value of the feature is estimated through Intensive feature success rate (IFSR) and clustered by marginal subset features. By marginalizing the sensitivity threshold frequency rate, the components are extracted by pragmatic quasi-sensitive identifier and classified using Hyper recurrent Neural classification (HRNC) to find the sensitive and non-sensitive records based on frequency fitness weight to split and store perception as individually in the private cloud. Further, to improve the security level Elliptic Curve Cryptography (ECC) based master node authentication technique is used in the blockchain concept. Peer end Block chain principle is applied to secure the sensitive data. To ensure the sensitive records are sanitized into data blocks to assure in a blockchain environment. This proposed system produces higher prediction accuracy than other methods and achieves higher sensitivity and specificity rate performance. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing ECC Hyper recurrent feature classification Privacy preservation Security Sensitive data analysis

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Numerical Simulation Study of Oil-Water Emulsion Separation in an Ultrasonic Field:Effect of Coupling between Acoustic and Flow Field Parameters

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China Petroleum Processing & Petrochemical technology 2024年第1期26卷 116-125页

作者： Wang Heping Lin Yinchao Li Yanggui Zhang Xiaohang Wu Yi Key Laboratory of Engineering Mathematics and Advanced Computing of Nanchang Institute of Technology School of SciencesNanchang Institute of TechnologyNanchang 330099People’s Republic of China Dongguan Key Laboratory of Kunpeng Computing School of Computer ScienceGuangdong University of Science&TechnologyDongguan 523083China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016China

In this study,the separation and coalescence of oil-in-water emulsions are explored in an ultrasonic field using the lattice Boltzmann *** simulating the propagation of ultrasonic waves,this study focuses on examining the effects of acoustic wave frequency,the ratio of oil to water components,and the aspect ratio of the boundary on the emulsification and separation processes of oil-water *** following conclusions are drawn.①Frequency affects the speed of oil droplet separation,leading to an increase in droplet size over *** droplets are found near the source,while smaller droplets are distributed throughout the wave web.②As the boundary aspect ratio increases,the emulsification efficiency of the droplets weakens,and the system takes longer to stabilize.③Emulsions with a higher component of oil can better resist acoustic waves.④At the same acoustic frequency,longer wavelength ultrasonic fields promote the formation of uniformly distributed,smaller oil droplets,which is beneficial to the storage of *** numerical simulation results offer insights for optimizing conditions for oil-in-water separation and serve as a numerical reference for the study of oil-in-water emulsion separation in ultrasonic environments.

关键词： lattice Boltzmann method phase separation ultrasound field

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SMART DRIVING LICENSING SYSTEM AND AUTHORIZATION OF AUTONOMOUS VEHICLE INTEGRATING WIRELESS SENSOR NETWORKS AND IoT

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Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2024年第9期83卷 69-85页

作者： Santhakumar, D. Sudhan, M.B. Prasanna, R. Manikandan, S.P. Prathaban, Banu Priya Kanna, Rajesh R. Saravanan, G. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai Ramapuram India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sree Sastha Institute of Engineering and Technology Chennai India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sri Sairam Institute of Technology Tamil Nadu Chennai India

The advent of autonomous vehicles has revolutionized the automotive industry, offering promising advancements in safety, efficiency, and mobility. To integrate these autonomous vehicles into our society seamlessly, it is imperative to establish a robust licensing system that ensures the safe operation of automated vehicles on public roads. This article presents an effective smart Driving Licensing System (SDLS), a digital framework designed to regulate the existing licensing system and authorize licensing for autonomous vehicles. Through a comprehensive assessment process, the system assesses the drivers and the autonomous vehicle’s ability to navigate various road conditions, respond to dynamic environments, and prioritize safety for passengers and other road users. SDLS integrates high-level security through facial and fingerprint verification for identity verification to preserve licensing data. Hacking and unauthorized access to autonomous vehicles is prevented by robust cybersecurity protocols. The key benefits of SDLS include automated data collection, integration of wireless sensor networks (WSN) and Internet of Things (IoT), smart application processing, real-time license checks, cybersecurity measures, automated testing, and digital certification. The proposed system offers a comprehensive approach to safely integrating autonomous vehicles into our transportation ecosystem. The autonomous vehicles are integrated with antennas at rooftops or into bumpers, depending upon the vehicle design which can be connected with the SDLS for signal communication. Furthermore, the SDLS establishes a framework for continuous monitoring and updates, enabling ongoing assessments to keep pace with evolving technology and safety standards. © 2024 by Begell House, Inc.

关键词： Autonomous vehicles

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Reinforcement Learning-Based Cooperative Target Tracking Control of Unmanned Surface Vehicles Under Data Falsification Attacks

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Liu, Zhao-Qing Ge, Xiaohua Han, Qing-Long Wang, Yu-Long Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne VIC Australia School of Mechatronic Engineering and Automation Shanghai University Shanghai China

This paper deals with the problem of cooperative target tracking control for multiple networked unmanned surface vehicles under data falsification attacks. First, a data falsification attack model is constructed to account for unknown falsified control commands. Next, a networked cooperative target tracking model is developed by integrating the concurrent impacts of data falsification attacks and network-induced delays. Then, a reinforcement learning-based compensation mechanism, consisting of an actor neural network and an adaptive critic function, is developed to offset the adverse effects caused by the unknown dynamics and external disturbances. Meanwhile, to cope with data falsification attacks and reduce the neural network approximation errors, a secure control input is subtly developed. Based on the developed compensation mechanism and secure control input, a dynamic control law is constructed to regulate the action of involved unmanned surface vehicles. Furthermore, a resilient cooperative target tracking control scheme is proposed to achieve the expected cooperative target tracking control objectives. At last, two case studies are provided to validate the efficacy of the designed resilient cooperative target tracking control scheme. IEEE

关键词： Reinforcement learning

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