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Host-based intrusion detection system with system calls: Review and future trends
In a contemporary data center, Linux applications often generate a large quantity of real-time
system call traces, which are not suitable for traditional host-based intrusion detection …
system call traces, which are not suitable for traditional host-based intrusion detection …
Droidcat: Effective android malware detection and categorization via app-level profiling
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …
Deep learning for effective Android malware detection using API call graph embeddings
High penetration of Android applications along with their malicious variants requires efficient
and effective malware detection methods to build mobile platform security. API call …
and effective malware detection methods to build mobile platform security. API call …
SEDMDroid: An enhanced stacking ensemble framework for Android malware detection
The popularity of the Android platform in smartphones and other Internet-of-Things devices
has resulted in the explosive of malware attacks against it. Malware presents a serious …
has resulted in the explosive of malware attacks against it. Malware presents a serious …
An enhanced stacked LSTM method with no random initialization for malware threat hunting in safety and time-critical systems
Malware detection is an increasingly important operational focus in cyber security,
particularly, given the fast pace of such threats (eg, new malware variants introduced every …
particularly, given the fast pace of such threats (eg, new malware variants introduced every …
An improved two-hidden-layer extreme learning machine for malware hunting
Detecting unknown malware and their variants remains both an operational challenge and a
research challenge. In recent years, there have been attempts to design machine learning …
research challenge. In recent years, there have been attempts to design machine learning …
Malware visualization for fine-grained classification
J Fu, J Xue, Y Wang, Z Liu, C Shan - IEEE Access, 2018 - ieeexplore.ieee.org
Due to the rapid rise of automated tools, the number of malware variants has increased
dramatically, which poses a tremendous threat to the security of the Internet. Recently, some …
dramatically, which poses a tremendous threat to the security of the Internet. Recently, some …
A feature-hybrid malware variants detection using CNN based opcode embedding and BPNN based API embedding
Being able to detect malware variants is a critical problem due to the potential damages and
the fast paces of new malware variations. According to surveys from McAfee and Symantec …
the fast paces of new malware variations. According to surveys from McAfee and Symantec …
Optimizing symbolic execution for malware behavior classification
Increasingly software correctness, reliability, and security is being analyzed using tools that
combine various formal and heuristic approaches. Often such analysis becomes expensive …
combine various formal and heuristic approaches. Often such analysis becomes expensive …
DroidHook: a novel API-hook based Android malware dynamic analysis sandbox
With the popularity of Android devices, mobile apps are prevalent in our daily life, making
them a target for attackers to steal private data and push advertisements. Dynamic analysis …
them a target for attackers to steal private data and push advertisements. Dynamic analysis …