Detecting SYN flooding attacks based on traffic prediction

Wang, Shangguang; Sun, Qibo; Zou, Hua; Yang, Fangchun

doi:10.1002/sec.428

Cited by 11 publications

(7 citation statements)

References 27 publications

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“…There is network communication in our proposed scheme, so the attacker may attack core DEX management system by SYN flooding attacks. This problem is out of our discussion in this paper, but we can develop additional security mechanism such as detection of SYN flooding .…”

Section: Discussionmentioning

confidence: 99%

Server‐based code obfuscation scheme for APK tamper detection

Piao

Jung

2014

Security Comm Networks

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It is easy to decompile Android applications (or apps) owing to the structural characteristics of the app building process, but this ease makes them quite vulnerable to forgery or modification attacks. In particular, users may suffer direct financial loss if this vulnerability is exploited in security-critical private and business applications, such as online banking. One of the solutions to these problems is a code obfuscation technique. In this regard, DexGuard, which is based on ProGuard, which is integrated into the Android software development kit build system, has recently been introduced. Although DexGuard protects Android applications more effectively, an attacker is still able to analyze the hex code of a Dalvix Executable file. To resolve this weakness, we begin by analyzing the DexGuard tool from both a static and dynamic point of view. Our analysis reveals that DexGuard has some weaknesses. In this paper, we propose an obfuscation technique based on a client/server model with one-time secret key delivery using short message service or network protocol. The main concept is to store the core execute class file through obfuscation on the server, so when a program needs to execute core routines, it must request these routines from the server. In this way, we can protect Android apps from reverse engineering.

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Section: Discussionmentioning

confidence: 99%

Server‐based code obfuscation scheme for APK tamper detection

Piao

Jung

2014

Security Comm Networks

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“…This optimization is mainly reflected in the process of sample selection. According to formula (7) to formula (10) in the manuscript, each fog node/MEC host has an optimal external weight in the network environment which is more suitable for the training.…”

Section: Numerical Simulationmentioning

confidence: 99%

“…IDS is an important security barrier that can quickly detect intrusion and security risks in the network [9,10]. The detection algorithm is one of the most important parts in IDS.…”

Section: Introductionmentioning

confidence: 99%

Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC

Zhou

Xing

et al. 2018

Wireless Communications and Mobile Computing

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Fog computing, as a new paradigm, has many characteristics that are different from cloud computing. Due to the resources being limited, fog nodes/MEC hosts are vulnerable to cyberattacks. Lightweight intrusion detection system (IDS) is a key technique to solve the problem. Because extreme learning machine (ELM) has the characteristics of fast training speed and good generalization ability, we present a new lightweight IDS called sample selected extreme learning machine (SS-ELM). The reason why we propose "sample selected extreme learning machine" is that fog nodes/MEC hosts do not have the ability to store extremely large amounts of training data sets. Accordingly, they are stored, computed, and sampled by the cloud servers. Then, the selected sample is given to the fog nodes/MEC hosts for training. This design can bring down the training time and increase the detection accuracy. Experimental simulation verifies that SS-ELM performs well in intrusion detection in terms of accuracy, training time, and the receiver operating characteristic (ROC) value.

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“…In this case, it is possible to verify the users by using ( , ) secret sharing method. Wang et al [5] deployed a private wireless sensor network to monitor the whole vehicle network. The vehicle-mounted communication mode and the position of communication event are available.…”

Section: Introductionmentioning

confidence: 99%

RESH: A Secure Authentication Algorithm Based on Regeneration Encoding Self-Healing Technology in WSN

et al. 2016

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In the real application environment of wireless sensor networks (WSNs), the uncertain factor of data storage makes the authentication information be easily forged and destroyed by illegal attackers. As a result, it is hard for secure managers to conduct forensics on transmitted information in WSN. This work considers the regeneration encoding self-healing and secret sharing techniques and proposes an effective scheme to authenticate data in WSN. The data is encoded by regeneration codes and then distributed to other redundant nodes in the form of fragments. When the network is attacked, the scheme has the ability against tampering attack or collusion attack. Furthermore, the damaged fragments can be restored as well. Parts of fragments, encoded by regeneration code, are required for secure authentication of the original distributed data. Experimental results show that the proposed scheme reduces hardware communication overhead by five percent in comparison. Additionally, the performance of local recovery achieves ninety percent.

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Detecting SYN flooding attacks based on traffic prediction

Cited by 11 publications

References 27 publications

Server‐based code obfuscation scheme for APK tamper detection

Server‐based code obfuscation scheme for APK tamper detection

Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC

RESH: A Secure Authentication Algorithm Based on Regeneration Encoding Self-Healing Technology in WSN

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