Memory analysis is one of the key techniques in computer live forensics. Especially,the analysis of a Mac OS X operating system's memory image file plays an important role in identifying the running status of an a...Memory analysis is one of the key techniques in computer live forensics. Especially,the analysis of a Mac OS X operating system's memory image file plays an important role in identifying the running status of an apple computer. However,how to analyze the image file without using extra"mach-kernel"file is one of the unsolved difficulties. In this paper,we firstly compare several approaches for physical memory acquisition and analyze the effects of each approach on physical memory. Then,we discuss the traditional methods for the physical memory file analysis of Mac OS X. A novel physical memory image file analysis approach without using extra"mach-kernel"file is proposed base on the discussion. We verify the performance of the new approach on Mac OS X 10. 8. 2. The experimental results show that the proposed approach is simpler and more practical than previous ones.展开更多
Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer...Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer security community.This paper seeks to provide a dedicated review of the very recent research works on using Deep Learning techniques to solve computer security challenges.In particular,the review covers eight computer security problems being solved by applications of Deep Learning:security-oriented program analysis,defending return-oriented programming(ROP)attacks,achieving control-flow integrity(CFI),defending network attacks,malware classification,system-event-based anomaly detection,memory forensics,and fuzzing for software security.展开更多
Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer...Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer security community.This paper seeks to provide a dedicated review of the very recent research works on using Deep Learning techniques to solve computer security challenges.In particular,the review covers eight computer security problems being solved by applications of Deep Learning:security-oriented program analysis,defending return-oriented programming(ROP)attacks,achieving control-flow integrity(CFI),defending network attacks,malware classification,system-event-based anomaly detection,memory forensics,and fuzzing for software security.展开更多
基金Sponsored by the National Natural Science Foundation of China (Grant No.61303199)Natural Science Foundation of Shandong Province (Grant No.ZR2013FQ001 and ZR2011FQ030)+1 种基金Outstanding Research Award Fund for Young Scientists of Shandong Province (Grant No.BS2013DX010)Academy of Sciences Youth Fund Project of Shandong Province (Grant No.2013QN007)
文摘Memory analysis is one of the key techniques in computer live forensics. Especially,the analysis of a Mac OS X operating system's memory image file plays an important role in identifying the running status of an apple computer. However,how to analyze the image file without using extra"mach-kernel"file is one of the unsolved difficulties. In this paper,we firstly compare several approaches for physical memory acquisition and analyze the effects of each approach on physical memory. Then,we discuss the traditional methods for the physical memory file analysis of Mac OS X. A novel physical memory image file analysis approach without using extra"mach-kernel"file is proposed base on the discussion. We verify the performance of the new approach on Mac OS X 10. 8. 2. The experimental results show that the proposed approach is simpler and more practical than previous ones.
基金This work was supported by ARO W911NF-13-1-0421(MURI),NSF CNS-1814679,and ARO W911NF-15-1-0576.
文摘Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer security community.This paper seeks to provide a dedicated review of the very recent research works on using Deep Learning techniques to solve computer security challenges.In particular,the review covers eight computer security problems being solved by applications of Deep Learning:security-oriented program analysis,defending return-oriented programming(ROP)attacks,achieving control-flow integrity(CFI),defending network attacks,malware classification,system-event-based anomaly detection,memory forensics,and fuzzing for software security.
基金supported by ARO W911NF-13-1-0421(MURI),NSF CNS-1814679,and ARO W911NF-15-1-0576.
文摘Although using machine learning techniques to solve computer security challenges is not a new idea,the rapidly emerging Deep Learning technology has recently triggered a substantial amount of interests in the computer security community.This paper seeks to provide a dedicated review of the very recent research works on using Deep Learning techniques to solve computer security challenges.In particular,the review covers eight computer security problems being solved by applications of Deep Learning:security-oriented program analysis,defending return-oriented programming(ROP)attacks,achieving control-flow integrity(CFI),defending network attacks,malware classification,system-event-based anomaly detection,memory forensics,and fuzzing for software security.
