Open Access
ARTICLE
Ji Qian1, Fang Liu2,*, Donghui Li3, Xin Jin4, Feng Li4
Journal of Cyber Security, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jcs.2020.011169
Abstract Anomaly detection using KPI (Key Performance Indicator) is critical
for Internet-based services to maintain high service availability. However, given
the velocity, volume, and diversified nature of monitoring data, it is difficult to
obtain enough labelled data to build an accurate anomaly detection model for
using supervised machine leaning methods. In this paper, we propose an
automatic and generic transfer learning strategy: Detecting anomalies on a new
KPI by using pretrained model on existing selected labelled KPI. Our approach,
called KADT (KPI Anomaly Detection based on Transfer Learning), integrates
KPI clustering and model pretrained techniques. KPI clustering is used to obtain… More >
Open Access
ARTICLE
Huanrong Tang, Yaojing Sun, Jianquan Ouyang*
Journal of Cyber Security, Vol.2, No.4, pp. 167-182, 2020, DOI:10.32604/jcs.2020.011341
Abstract With the rapid development of blockchain technology, more and more
people are paying attention to the consensus mechanism of blockchain. Practical
Byzantine Fault Tolerance (PBFT), as the first efficient consensus algorithm
solving the Byzantine Generals Problem, plays an important role. But PBFT also
has its problems. First, it runs in a completely closed environment, and any node
can't join or exit without rebooting the system. Second, the communication
complexity in the network is as high as O(n2), which makes the algorithm only
applicable to small-scale networks. For these problems, this paper proposes an
Optimized consensus algorithm, Excellent Practical Byzantine Fault… More >
Open Access
ARTICLE
Enlu Li1, Zhangjie Fu1,2,3,*, Siyu Chen1, Junfu Chen1
Journal of Cyber Security, Vol.2, No.4, pp. 183-190, 2020, DOI:10.32604/jcs.2020.015010
Abstract With the development of natural language processing, deep learning,
and other technologies, text steganography is rapidly developing. However,
adversarial attack methods have emerged that gives text steganography the ability
to actively spoof steganalysis. If terrorists use the text steganography method to
spread terrorist messages, it will greatly disturb social stability. Steganalysis
methods, especially those for resisting adversarial attacks, need to be further
improved. In this paper, we propose a two-stage highly robust model for text
steganalysis. The proposed method analyzes and extracts anomalous features at
both intra-sentential and inter-sentential levels. In the first phase, every sentence
is first transformed into… More >
Open Access
ARTICLE
Yu Xue, Sow Alpha Amadou*, Yan Zhao
Journal of Cyber Security, Vol.2, No.4, pp. 191-196, 2020, DOI:10.32604/jcs.2020.014045
Abstract Attracted numerous analysts’ consideration, classification is one of the
primary issues in Machine learning. Numerous evolutionary algorithms (EAs)
were utilized to improve their global search ability. In the previous years, many
scientists have attempted to tackle this issue, yet regardless of the endeavors,
there are still a few inadequacies. Based on solving the classification problem,
this paper introduces a new optimization classification model, which can be
applied to the majority of evolutionary computing (EC) techniques. Firework
algorithm (FWA) is one of the EC methods, Although the Firework algorithm
(FWA) is a proficient algorithm for solving complex optimization issue. The
proficient… More >
Open Access
REVIEW
Xingwang Ju*
Journal of Cyber Security, Vol.2, No.4, pp. 197-207, 2020, DOI:10.32604/jcs.2020.014310
Abstract Due to the power of editing tools, new types of fake faces are being
created and synthesized, which has attracted great attention on social media. It is
reasonable to acknowledge that one human cannot distinguish whether the face is
manipulated from the real faces. Therefore, the detection of face manipulation
becomes a critical issue in digital media forensics. This paper provides an
overview of recent deep learning detection models for face manipulation. Some
public dataset used for face manipulation detection is introduced. On this basis,
the challenges for the research and the potential future directions are analyzed
and discussed. More >
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