LEADER 02356nam 2200325z- 450 001 9910557104503321 005 20231214133652.0 035 $a(CKB)5400000000041002 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68858 035 $a(EXLCZ)995400000000041002 100 $a20202105d2020 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSymmetry-Adapted Machine Learning for Information Security 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2020 215 $a1 electronic resource (202 p.) 311 $a3-03936-642-4 311 $a3-03936-643-2 330 $aSymmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis. 606 $aHistory of engineering & technology$2bicssc 615 7$aHistory of engineering & technology 700 $aPark$b James$4edt$0521811 702 $aPark$b James$4oth 906 $aBOOK 912 $a9910557104503321 996 $aSymmetry-Adapted Machine Learning for Information Security$93023792 997 $aUNINA