A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> ELECTRONICS (Total: 207 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Journal Cover
Security and Communication Networks
Journal Prestige (SJR): 0.285
Citation Impact (citeScore): 1
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1939-0114 - ISSN (Online) 1939-0122
Published by Hindawi Homepage  [340 journals]
  • HMMED: A Multimodal Model with Separate Head and Payload Processing for
           Malicious Encrypted Traffic Detection

    • Free pre-print version: Loading...

      Abstract: Malicious encrypted traffic detection is a critical component of network security management. Previous detection methods can be categorized into two classes as follows: one is to use the feature engineering method to construct traffic features for classification and the other is to use the end-to-end method that directly inputs the original traffic to obtain traffic features for classification. Both of the abovementioned two methods have the problem that the obtained features cannot fully characterize the traffic. To this end, this paper proposes a hierarchical multimodal deep learning model (HMMED) for malicious encrypted traffic detection. This model adopts the abovementioned two feature generation methods to learn the features of payload and header, respectively, then fuses the features to get the final traffic features, and finally inputs the final traffic features into the softmax classifier for classification. In addition, since traditional deep learning is highly dependent on the training set size and data distribution, resulting in a model that is not very generalizable and difficult to adapt to unseen encrypted traffic, the model proposed in this paper uses a large amount of unlabeled encrypted traffic in the pretraining layer to pretrain a submodel used to obtain a generic packet payload representation. The test results on the USTC-TFC2016 dataset show that the proposed model can effectively solve the problem of insufficient feature extraction of traditional detection methods and improve the ACC of malicious encrypted traffic detection.
      PubDate: Thu, 30 May 2024 13:50:00 +000
       
  • A Robust Coverless Image Steganography Algorithm Based on Image Retrieval
           with SURF Features

    • Free pre-print version: Loading...

      Abstract: With the advancement of image steganography, coverless image steganography has gained widespread attention due to its ability to hide information without modifying the carrier of images. However, existing coverless image steganography methods often require both communicating parties to transmit an amount of additional information including image blocks’ locations or a large number of parameters, which will raise a serious suspicion. In light of this issue, we propose a robust coverless image steganography algorithm based on Speeded-Up Robust Features (SURF). Firstly, the proposed method allows both communicating parties to independently create multiple coverless image datasets (CIDs) using random seeds. Then, a mapping rule is designed for creating one-to-one correspondence between hash sequences and images in CIDs. Finally, the secret information will be carried by the images whose hash sequences are equal to the secret segments. At the receiver side, the robust SURF of images is utilized to retrieve the secret information. Experimental results demonstrate that the proposed algorithm outperforms other methods in terms of capacity, robustness, and security. Furthermore, it is worth noting that the proposed method eliminates the need to transmit a large amount of additional information, which is a significant security issue in existing coverless image steganography algorithms.
      PubDate: Sat, 18 May 2024 08:20:00 +000
       
  • Effective and Efficient Android Malware Detection and Category
           Classification Using the Enhanced KronoDroid Dataset

    • Free pre-print version: Loading...

      Abstract: Android is the most widely used mobile operating system and responsible for handling a wide variety of data from simple messages to sensitive banking details. The explosive increase in malware targeting this platform has made it imperative to adopt machine learning approaches for effective malware detection and classification. Since its release in 2008, the Android platform has changed substantially and there has also been a significant increase in the number, complexity, and evolution of malware that target this platform. This rapid evolution quickly renders existing malware datasets out of date and has a degrading impact on machine learning-based detection models. Many studies have been carried out to explore the effectiveness of various machine learning models for Android malware detection. Majority of these studies use datasets that have compiled using static or dynamic analysis of malware but the use of hybrid analysis approaches has not been addressed completely. Likewise, the impact of malware evolution has not been fully investigated. Although some of the models have achieved exceptional results, their performance deteriorated for evolving malware and they were also not effective against antidynamic malware. In this paper, we address both these limitations by creating an enhanced subset of the KronoDroid dataset and using it to develop a supervised machine learning model capable of detecting evolving and antidynamic malware. The original KronoDroid dataset contains malware samples from 2008 to 2020, making it effective for the detection of evolving malware and handling concept drift. Also, the dynamic features are collected by executing the malware on a real device, making it effective for handling antidynamic malware. We create an enhanced subset of this dataset by adding malware category labels with the help of multiple online repositories. Then, we train multiple supervised machine learning models and use the ExtraTree classifier to select the top 50 features. Our results show that the random forest (RF) model has the highest accuracy of 98.03% for malware detection and 87.56% for malware category classification (for 15 malware categories).
      PubDate: Mon, 08 Apr 2024 13:20:00 +000
       
  • Securing the Transmission While Enhancing the Reliability of Communication
           Using Network Coding in Block-Wise Transfer of CoAP

    • Free pre-print version: Loading...

      Abstract: The practical employment of network coding (NC) has shown major improvements when it comes to the transmission reliability of sender data and bandwidth utilization. Moreover, network coding has been employed recently to secure the transmission of data and prevent unauthorized recovery of sender packets. In this paper, we employ network coding (NC) in a practical way in networks with constrained resources with the goal of improving the reliability and security of data transfer. More specifically, we apply NC on the recent options of block-wise transfer (BWT) of the constrained application protocol (CoAP). The goal is to enhance the reliability of CoAP when used to transfer larger data blocks using BWT. Also, we employ an innovative homomorphic encryption approach to secure the BWT of CoAP.
      PubDate: Thu, 28 Mar 2024 10:35:00 +000
       
  • Exploring the Security Vulnerability in Frequency-Hiding Order-Preserving
           Encryption

    • Free pre-print version: Loading...

      Abstract: Frequency-hiding order-preserving encryption (FH-OPE) has emerged as an important tool in data security, particularly in cloud computing, because of its unique ability to preserve the order of plaintexts in their corresponding ciphertexts and enable efficient range queries on encrypted data. Despite its strong security model, indistinguishability under frequency analyzing ordered chosen plaintext attack (IND-FA-OCPA), our research identifies a vulnerability in its design, particularly the impact of range queries. In our research, we quantify the frequency of data exposure resulting from these range queries and present potential inference attacks on the FH-OPE scheme. Our findings are substantiated through experiments on real-world datasets, with the goal of measuring the frequency of data exposure resulting from range queries on FH-OPE encrypted databases. These results quantify the level of risk in practical applications of FH-OPE and reveal the potential for additional inference attacks and the urgency of addressing these threats. Consequently, our research highlights the need for a more comprehensive security model that considers the potential risks associated with range queries and underscores the importance of developing new range-query methods that prevent exposing these vulnerabilities.
      PubDate: Thu, 29 Feb 2024 14:05:00 +000
       
  • Toward a Real-Time TCP SYN Flood DDoS Mitigation Using Adaptive
           Neuro-Fuzzy Classifier and SDN Assistance in Fog Computing

    • Free pre-print version: Loading...

      Abstract: The growth of the Internet of Things (IoT) has recently impacted our daily lives in many ways. As a result, a massive volume of data are generated and need to be processed in a short period of time. Therefore, a combination of computing models such as cloud computing is necessary. The main disadvantage of the cloud platform is its high latency due to the centralized mainframe. Fortunately, a distributed paradigm known as fog computing has emerged to overcome this problem, offering cloud services with low latency and high-access bandwidth to support many IoT application scenarios. However, attacks against fog servers can take many forms, such as distributed denial of service (DDoS) attacks that severely affect the reliability and availability of fog services. To address these challenges, we propose mitigation of fog computing-based SYN Flood DDoS attacks using an adaptive neuro-fuzzy inference system (ANFIS) and software defined networking (SDN) assistance (FASA). The simulation results show that the FASA system outperforms other algorithms in terms of accuracy, precision, recall, and F1-score. This shows how crucial our system is for detecting and mitigating TCP-SYN floods and DDoS attacks.
      PubDate: Fri, 23 Feb 2024 09:50:00 +000
       
  • Retracted: A Review of Motion Vector-Based Video Steganography

    • Free pre-print version: Loading...

      PubDate: Wed, 24 Jan 2024 07:05:00 +000
       
  • Retracted: Efficient and Energy-Saving Computation Offloading Mechanism
           with Energy Harvesting for IoT

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:26 +000
       
  • Retracted: A New Method for Inverter Diagnosis of Electric Locomotive
           Using Adversarial Neural Networks

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:25 +000
       
  • Retracted: Research on Tourism Route Recommendation Strategy Based on
           Convolutional Neural Network and Collaborative Filtering Algorithm

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:23 +000
       
  • Retracted: Blockchain-Based Intelligent Interconnection System
           Optimization Decision

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:21 +000
       
  • Retracted: Deep Reinforcement Learning-Based Algorithm for VNF-SC
           Deployment

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:20 +000
       
  • Retracted: Analysis of Dynamic Influence Mechanism of Network Public
           Opinion Based on Simulation Feature Extraction

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:18 +000
       
  • Retracted: Discussion on Innovative Methods of Higher Teacher Education
           and Training Based on New Artificial Intelligence

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:16 +000
       
  • Retracted: Analysis of Economic Relationship Using the Concept of Complex
           Pythagorean Fuzzy Information

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:14 +000
       
  • Retracted: Secure Two-Party Computation Based on Fast Cut-and-Choose
           Bilateral Oblivious Transfer

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:12 +000
       
  • Retracted: Construction and Simulation of the Enterprise Financial Risk
           Diagnosis Model by Using Dropout and BN to Improve LSTM

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:11 +000
       
  • Retracted: On the Modeling of RTT Time Series for Network Anomaly
           Detection

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:09 +000
       
  • Retracted: A Secure and Efficient Multi-Object Grasping Detection Approach
           for Robotic Arms

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:07 +000
       
  • Retracted: Paper-Cutting Pattern Design Based on Image Restoration
           Technology

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:06 +000
       
  • Retracted: SCR-CC: A Novel Sensing Clustering Routing Algorithm Based on
           Collaborative Computing in Heterogeneous Sensor Networks

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:04 +000
       
  • Retracted: A Robust and Privacy-Preserving Anonymous User Authentication
           Scheme for Public Cloud Server

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:02 +000
       
  • Retracted: Internet of Things-Based Home Education Interactive System and
           Parent-Teacher Relationship Cultivation

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:08:01 +000
       
  • Retracted: Analysis of Painting Elements of Tea Culture and Art Works
           Based on Image Perception

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:59 +000
       
  • Retracted: HS-MOEA/D: An Oriented Algorithm for Delay and Reliability
           VNF-SC Deployment

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:57 +000
       
  • Retracted: A Novel Hierarchical Key Assignment Scheme for Data Access
           Control in IoT

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:56 +000
       
  • Retracted: Development Trend of Digital Physical Education Teaching by
           Integrating Intelligent Sensor Technology

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:54 +000
       
  • Retracted: Evaluation Method of Enterprise Management Effectiveness Based
           on Improved Analytic Hierarchy Process

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:53 +000
       
  • Retracted: Simulation of Film and Television Transmission Path Based on
           Ant Colony Optimization Algorithm

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:51 +000
       
  • Retracted: Security and Makespan Trade-Off Strategy in Fog-Enabled IoT
           Networks

    • Free pre-print version: Loading...

      PubDate: Tue, 09 Jan 2024 07:07:49 +000
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.221.66.130
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-
JournalTOCs
 
 

 A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> ELECTRONICS (Total: 207 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Similar Journals
HOME > Browse the 73 Subjects covered by JournalTOCs  
SubjectTotal Journals
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 44.221.66.130
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-