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  Subjects -> ELECTRONICS (Total: 187 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 7)
Advances in Electronics     Open Access   (Followers: 90)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Power Electronics     Open Access   (Followers: 38)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 337)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 26)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 14)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 30)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 20)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 38)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 13)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 1)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 295)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access  
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 117)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 97)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 100)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 55)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 207)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 99)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 80)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 49)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 72)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 71)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 58)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 42)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 26)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 78)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access  
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 55)
IET Smart Grid     Open Access  
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 70)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 11)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 3)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 11)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 32)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 175)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 29)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Learning Technologies, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Magnetics Letters, IEEE     Hybrid Journal   (Followers: 7)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 41)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 9)
Optical Communications and Networking, IEEE/OSA Journal of     Full-text available via subscription   (Followers: 15)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Pulse     Full-text available via subscription   (Followers: 5)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 9)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 5)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 56)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Services Computing, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Software Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 78)
Solid State Electronics Letters     Open Access  
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Transactions on Electrical and Electronic Materials     Hybrid Journal  
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Ural Radio Engineering Journal     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)
Wireless Power Transfer     Full-text available via subscription   (Followers: 4)
Women in Engineering Magazine, IEEE     Full-text available via subscription   (Followers: 11)
Електротехніка і Електромеханіка     Open Access  

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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  [338 journals]
  • All-in-One Framework for Detection, Unpacking, and Verification for
           Malware Analysis
    • Abstract: Packing is the most common analysis avoidance technique for hiding malware. Also, packing can make it harder for the security researcher to identify the behaviour of malware and increase the analysis time. In order to analyze the packed malware, we need to perform unpacking first to release the packing. In this paper, we focus on unpacking and its related technologies to analyze the packed malware. Through extensive analysis on previous unpacking studies, we pay attention to four important drawbacks: no phase integration, no detection combination, no real-restoration, and no unpacking verification. To resolve these four drawbacks, in this paper, we present an all-in-one structure of the unpacking system that performs packing detection, unpacking (i.e., restoration), and verification phases in an integrated framework. For this, we first greatly increase the packing detection accuracy in the detection phase by combining four existing and new packing detection techniques. We then improve the unpacking phase by using the state-of-the-art static and dynamic unpacking techniques. We also present a verification algorithm evaluating the accuracy of unpacking results. Experimental results show that the proposed all-in-one unpacking system performs all of the three phases well in an integrated framework. In particular, the proposed hybrid detection method is superior to the existing methods, and the system performs unpacking very well up to 100% of restoration accuracy for most of the files except for a few packers.
      PubDate: Sun, 13 Oct 2019 00:05:03 +000
       
  • An Active Controller Selection Scheme for Minimizing Packet-In Processing
           Latency in SDN
    • Abstract: In software-defined network, the use of distributed controllers to control forwarding devices has been proposed to solve the issues of scalability and load balance. However, the forwarding devices are statically assigned to the controllers in these distributed systems, which can overload some controllers while others are underutilized. In this paper, we propose an architecture named ASLB (active controller selection load balance), which proactively selects appropriate controllers for load balancing and minimize packet processing delays. We also present a novel active controller selection algorithm (ACS) for ASLB that efficiently schedules traffic from the switch to the controller and designs an intermediate coordinator for actively selecting a controller to serve a request. We built a system and evaluated it on a physical platform. The results show that ASLB is much better than the static allocation scheme in terms of minimizing latency, bandwidth utilization, and throughput.
      PubDate: Sun, 13 Oct 2019 00:05:02 +000
       
  • Smart Detection: An Online Approach for DoS/DDoS Attack Detection Using
           Machine Learning
    • Abstract: Users and Internet service providers (ISPs) are constantly affected by denial-of-service (DoS) attacks. This cyber threat continues to grow even with the development of new protection technologies. Developing mechanisms to detect this threat is a current challenge in network security. This article presents a machine learning- (ML-) based DoS detection system. The proposed approach makes inferences based on signatures previously extracted from samples of network traffic. The experiments were performed using four modern benchmark datasets. The results show an online detection rate (DR) of attacks above 96%, with high precision (PREC) and low false alarm rate (FAR) using a sampling rate (SR) of 20% of network traffic.
      PubDate: Sun, 13 Oct 2019 00:05:00 +000
       
  • Outsourcing Hierarchical Threshold Secret Sharing Scheme Based on
           Reputation
    • Abstract: Secret sharing is a basic tool in modern communication, which protects privacy and provides information security. Among the secret sharing schemes, fairness is a vital and desirable property. To achieve fairness, the existing secret sharing schemes either require a trusted third party or the execution of a multiround protocol, which are impractical. Moreover, the classic scheme requires expensive computing in the secret verification phase. In this work, we provide an outsourcing hierarchical threshold secret sharing (HTSS) protocol based on reputation. In the scheme, participants from different levels can fairly reconstruct the secret, and the protocol only needs to run for one round. A cloud service provider (CSP) uses powerful computing resources to help participants complete homomorphic encryption and complex verification operations, and the CSP cannot be aware of any valuable information. The participants can obtain the secret with a small number of operations. To avoid collusion, we suppose that participants have their own reputation value, and they are punished or rewarded according to their behavior. The reputation value of a participant who deviates from the protocol will decrease; therefore, the participant will choose a cooperative strategy to obtain better payoffs. Lastly, our scheme is proved to be secure, and experiments indicate that our scheme is feasible and efficient.
      PubDate: Thu, 10 Oct 2019 12:05:00 +000
       
  • Multidivisible Online/Offline Cryptography and Its Application to
           Signcryptions
    • Abstract: We introduce a general concept of multidivisible online/offline (MDO) cryptography, which covers the previous works including online/offline cryptographic schemes, divisible online/offline signatures, incrementally executable signcryptions, and multidivisible online/offline encryptions. We then present the notion of multidivisible online/offline signcryptions (MDOSCs) as novel application of MDO cryptography. We define several security notions for MDOSCs and show implications and separations between these security notions. We also present a generic construction of MDOSC that achieves the strongest security notions with regard to confidentiality and unforgeability. Using MDOSC schemes, the computationally restricted and/or bandwidth-restricted devices can transmit messages in both confidential and authenticated way with low computational overhead and/or low-bandwidth network.
      PubDate: Tue, 08 Oct 2019 10:05:00 +000
       
  • Automated Dataset Generation System for Collaborative Research of Cyber
           Threat Analysis
    • Abstract: The objectives of cyberattacks are becoming sophisticated, and attackers are concealing their identity by masquerading as other attackers. Cyber threat intelligence (CTI) is gaining attention as a way to collect meaningful knowledge to better understand the intention of an attacker and eventually predict future attacks. A systemic threat analysis based on data acquired from actual cyber incidents is a useful approach to generating intelligence for such an objective. Developing an analysis technique requires a high-volume and fine-quality data. However, researchers can become discouraged by inaccessibility to data because organizations rarely release their data to the research community. Owing to a data inaccessibility issue, academic research tends to be biased toward techniques that develop steps of the CTI process other than analysis and production. In this paper, we propose an automated dataset generation system called CTIMiner. The system collects threat data from publicly available security reports and malware repositories. The data are stored in a structured format. We released the source codes and dataset to the public, including approximately 640,000 records from 612 security reports published from January 2008 to June 2019. In addition, we present a statistical feature of the dataset and techniques that can be developed using it. Moreover, we demonstrate an application example of the dataset that analyzes the correlation and characteristics of an incident. We believe our dataset will promote collaborative research on threat analysis for the generation of CTI.
      PubDate: Mon, 30 Sep 2019 10:05:02 +000
       
  • LTE Phone Number Catcher: A Practical Attack against Mobile Privacy
    • Abstract: Phone number is a unique identity code of a mobile subscriber, which plays a more important role in the mobile social network life than another identification number IMSI. Unlike the IMSI, a mobile device never transmits its own phone number to the network side in the radio. However, the mobile network may send a user’s phone number to another mobile terminal when this user initiating a call or SMS service. Based on the above facts, with the help of an IMSI catcher and 2G man-in-the-middle attack, this paper implemented a practicable and effective phone number catcher prototype targeting at LTE mobile phones. We caught the LTE user’s phone number within a few seconds after the device camped on our rogue station. This paper intends to verify that mobile privacy is also quite vulnerable even in LTE networks as long as the legacy GSM still exists. Moreover, we demonstrated that anyone with basic programming skills and the knowledge of GSM/LTE specifications can easily build a phone number catcher using SDR tools and commercial off-the-shelf devices. Hence, we hope the operators worldwide can completely disable the GSM mobile networks in the areas covered by 3G and 4G networks as soon as possible to reduce the possibility of attacks on higher-generation cellular networks. Several potential countermeasures are also discussed to temporarily or permanently defend the attack.
      PubDate: Mon, 30 Sep 2019 09:05:00 +000
       
  • An Object Proxy-Based Dynamic Layer Replacement to Protect IoMT
           Applications
    • Abstract: The Internet of medical things (IoMT) has become a promising paradigm, where the invaluable additional data can be collected by the ordinary medical devices when connecting to the Internet. The deep understanding of symptoms and trends can be provided to patients to manage their lives and treatments. However, due to the diversity of medical devices in IoMT, the codes of healthcare applications may be manipulated and tangled by malicious devices. In addition, the linguistic structures for layer activation in languages cause controls of layer activation to be part of program’s business logic, which hinders the dynamic replacement of layers. Therefore, to solve the above critical problems in IoMT, in this paper, a new approach is firstly proposed to support the dynamic replacement of layer in IoMT applications by incorporating object proxy into virtual machine (VM). Secondly, the heap and address are used to model the object and object evolution to guarantee the feasibility of the approach. After that, we analyze the influences of field access and method invocation and evaluate the risk and safety of the application when these constraints are satisfied. Finally, we conduct the evaluations by extending Java VM to validate the effectiveness of the proposal.
      PubDate: Mon, 30 Sep 2019 07:05:00 +000
       
  • Industrial Anomaly Detection and Attack Classification Method Based on
           Convolutional Neural Network
    • Abstract: The massive use of information technology has brought certain security risks to the industrial production process. In recent years, cyber-physical attacks against industrial control systems have occurred frequently. Anomaly detection technology is an essential technical means to ensure the safety of industrial control systems. Considering the shortcomings of traditional methods and to facilitate the timely analysis and location of anomalies, this study proposes a solution based on the deep learning method for industrial traffic anomaly detection and attack classification. We use a convolutional neural network deep learning representation model as the detection model. The original one-dimensional data are mapped using the feature mapping method to make them suitable for model processing. The deep learning method can automatically extract critical features and achieve accurate attack classification. We performed a model evaluation using real network attack data from a supervisory control and data acquisition (SCADA) system. The experimental results showed that the proposed method met the anomaly detection and attack classification needs of a SCADA system. The proposed method also promotes the application of deep learning methods in industrial anomaly detection.
      PubDate: Sun, 29 Sep 2019 00:05:00 +000
       
  • Privacy Protection of Social Networks Based on Classified Attribute
           Encryption
    • Abstract: With the rapid development of social networks, privacy has also attracted attention. Based on this problem, a privacy protection scheme for social networks based on classified attribute encryption (PPSSN) is proposed for the data owner and attribute management server to manage user permissions; the approach reduces data owner overhead and also avoids use of a property management server to limit access user collusion attacks. To balance the privacy and security of data publication, this scheme classifies users and designs access control for different users and different privileges. In addition, this paper also introduces a good friend data cache mechanism to improve and optimize the original scheme to reduce the cost of decryption. The efficiency and system overhead of the proposed scheme are compared and analyzed based on experiments. The experiments show that the proposed scheme improves query efficiency, reduces system cost, and enhances privacy security.
      PubDate: Thu, 26 Sep 2019 09:05:00 +000
       
  • Power Grid Estimation Using Electric Network Frequency Signals
    • Abstract: The electric network frequency (ENF) has a statistical uniqueness according to time and location. The ENF signal is always slightly fluctuating for the load balance of the power grid around the fundamental frequency. The ENF signals can be obtained from the power line using a frequency disturbance recorder (FDR). The ENF signal can also be extracted from video files or audio files because the ENF signal is also saved due to the influence of the electromagnetic field when video files or audio files are recorded. In this paper, we propose a method to find power grid from ENF signals collected from various time and area. We analyzed ENF signals from the distribution level of the power system and online uploaded video files. Moreover, a hybrid feature extraction approach, which employs several features, is proposed to infer the location of the signal belongs regardless of the time that the signal was collected. Employing our suggested feature extraction methods, the signal which extracted from the power line can be classified 95.21% and 99.07% correctly when ENF signals have 480 and 1920 data points, respectively. In the case of ENF signals extracted from multimedia, the accuracy varies greatly according to the recorded environment such as network status and microphone quality. When constructing a feature vector from 120 data points of ENF signals, we could identify the power grid had an average of 94.17% accuracy from multimedia.
      PubDate: Tue, 24 Sep 2019 10:05:00 +000
       
  • Sensitivity of Importance Metrics for Critical Digital Services Graph to
           Service Operators’ Self-Assessment Errors
    • Abstract: Interdependency of critical digital services can be modeled in the form of a graph with exactly known structure but with edge weights subject to estimation errors. We use standard and custom centrality indexes to measure each service vulnerability. Vulnerability of all nodes in the graph gets aggregated in a number of ways into a single network vulnerability index for services whose operation is critical for the state. This study compares sensitivity of various centralities combined with various aggregation methods to errors in edge weights reported by service operators. We find that many of those combinations are quite robust and can be used interchangeably to reflect various perceptions of network vulnerability. We use graphs of source files’ dependencies for a number of open-source projects, as a good analogy for real critical services graph, which will remain confidential.
      PubDate: Mon, 23 Sep 2019 08:05:00 +000
       
  • Detection of Free-Form Copy-Move Forgery on Digital Images
    • Abstract: Nowadays, production and distribution of digital images has become part of our life. Since digital images, which are important carriers of information, are considered as the concrete proofs of facts in many fields and they can be used as evidence in the courts of law, development of techniques to ensure image authenticity is an active research topic. Copy-move forgery is one of the most common manipulation techniques that are implemented on the digital images, and various techniques have been developed for detection of these kinds of forgeries. JPEG format, which presents the ability of making high rate compression without causing remarkable changes in the meaning of the image, is the most commonly used format on digital images. In this study, the topic of detecting free-form copy-move forgeries on digital images is covered. It has been observed that the developed technique is able to detect the professional forgeries in which the copied region is selected in free-form and which are almost impossible to be detected by human eye, with high success rate, and it is able to give successful results even if the image is exposed to postprocesses such as JPEG compression and Gaussian filtering, which make the detection of forgery harder.
      PubDate: Sun, 22 Sep 2019 00:05:04 +000
       
  • Automatic Identification of Honeypot Server Using Machine Learning
           Techniques
    • Abstract: Traditional security strategies are powerless when facing novel attacks in the complex network environment, such as advanced persistent threat (APT). Compared with traditional security detection strategies, the honeypot system, especially on the Internet of things research area, is intended to be attacked and automatically monitor potential attacks by analyzing network packages or log files. The researcher can extract exactly threat actor tactics, techniques, and procedures from these data and then generate more effective defense strategies. But for normal security researchers, it is an urgent topic how to improve the honeypot mechanism which could not be recognized by attackers, and silently capture their behaviors. So, they need awesome intelligent techniques to automatically check remotely whether the server runs honeypot service or not. As the rapid progress in honeypot detection using machine learning technologies, the paper proposed a new automatic identification model based on random forest algorithm with three group features: application-layer feature, network-layer feature, and other system-layer feature. The experiment datasets are collected from public known platforms and designed to prove the effectiveness of the proposed model. The experiment results showed that the presented model achieved a high area under curve (AUC) value with 0.93 (area under the receiver operating characteristic curve), which is better than other machine learning algorithms.
      PubDate: Sun, 22 Sep 2019 00:05:02 +000
       
  • A Malware and Variant Detection Method Using Function Call Graph
           Isomorphism
    • Abstract: The huge influx of malware variants are generated using packing and obfuscating techniques. Current antivirus software use byte signature to identify known malware, and this method is easy to be deceived and generally ineffective for identifying malware variants. Antivirus experts use hash signature to verify if captured sample is one of the malware databases, and this method cannot recognize malware variants whose hash signatures have changed completely. Function call graph is a high-level abstraction representation of a program and more stable and resilient than byte or hash signature. In this paper, function call graph is used as signature of a program, and two kinds of graph isomorphism algorithms are employed to identify known malware and its variants. Four experiments are designed to evaluate the performance of the proposed method. Experimental results indicate that the proposed method is effective and efficient for identifying known malware and a portion of their variants. The proposed method can also be used to index and locate a large-scale malware database and group malware to the corresponding family.
      PubDate: Sun, 22 Sep 2019 00:05:01 +000
       
  • Generative Reversible Data Hiding by Image-to-Image Translation via GANs
    • Abstract: The traditional reversible data hiding technique is based on cover image modification which inevitably leaves some traces of rewriting that can be more easily analyzed and attacked by the warder. Inspired by the cover synthesis steganography-based generative adversarial networks, in this paper, a novel generative reversible data hiding (GRDH) scheme by image translation is proposed. First, an image generator is used to obtain a realistic image, which is used as an input to the image-to-image translation model with CycleGAN. After image translation, a stego image with different semantic information will be obtained. The secret message and the original input image can be recovered separately by a well-trained message extractor and the inverse transform of the image translation. The experimental results have verified the effectiveness of the scheme.
      PubDate: Wed, 11 Sep 2019 10:05:01 +000
       
  • Evaluating the Impact of Name Resolution Dependence on the DNS
    • Abstract: In the process of resolving domain names to IP addresses, there exist complex dependence relationships between domains and name servers. This paper studies the impact of the resolution dependence on the DNS through constructing a domain name resolution network based on large-scale actual data. The core nodes of the resolution network are mined from different perspectives by means of four methods. Then, both core attacks and random attacks on the network are simulated for further vulnerability analysis. The experimental results show that when the top 1% of the core nodes in the network are attacked, 46.19% of the domain names become unresolved, and the load of the residual network increases by nearly 195%, while only 0.01% of domain names fail to be resolved and the load increases with 18% in the same attack scale of the random mode. For these key nodes, we need to take effective security measures to prevent them from being attacked. The simulation experiment also proves that the resolution network is a scale-free network, which exhibits robustness against random failure and vulnerability against intentional attacks. These findings provide new references for the configuration of the DNS.
      PubDate: Mon, 09 Sep 2019 13:30:00 +000
       
  • A Data-Driven Approach to Cyber Risk Assessment
    • Abstract: Cyber risk assessment requires defined and objective methodologies; otherwise, its results cannot be considered reliable. The lack of quantitative data can be dangerous: if the assessment is entirely qualitative, subjectivity will loom large in the process. Too much subjectivity in the risk assessment process can weaken the credibility of the assessment results and compromise risk management programs. On the other hand, obtaining a sufficiently large amount of quantitative data allowing reliable extrapolations and previsions is often hard or even unfeasible. In this paper, we propose and study a quantitative methodology to assess a potential annualized economic loss risk of a company. In particular, our approach only relies on aggregated empirical data, which can be obtained from several sources. We also describe how the method can be applied to real companies, in order to customize the initial data and obtain reliable and specific risk assessments.
      PubDate: Mon, 09 Sep 2019 09:05:01 +000
       
  • Big Data Analytics for Cyber Security
    • PubDate: Sun, 08 Sep 2019 00:05:00 +000
       
  • A Novel Trust Model Based on Node Recovery Technique for WSN
    • Abstract: With the rapid development of sensor technology and wireless network technology, wireless sensor network (WSN) has been widely applied in many resource-constrained environments and application scenarios. As there are a large number of sensor nodes in WSN, node failures are inevitable and have a significant impact on task execution. In this paper, considering the vulnerability, unreliability, and dynamic characteristics of sensor nodes, node failures are classified into two categories including unrecoverable failures and recoverable failures. Then, the traditional description of the interaction results is extended to the trinomial distribution. According to the Bayesian cognitive model, the global trust degree is aggregated by both direct and indirect interaction records, and a novel trust model based on node recovery technique for WSNs is proposed to reduce the probability of failure for task execution. Simulation results show that compared with existing trust models, our proposed TMBNRT (trust model based on node recovery technique) algorithm can effectively meet the security and the reliability requirements of WSN.
      PubDate: Tue, 03 Sep 2019 08:05:00 +000
       
  • Social Security and Privacy for Social IoT Polymorphic Value Set: A
           Solution to Inference Attacks on Social Networks
    • Abstract: Social Internet of Things (SIoT) integrates social network schemes into Internet of Things (IoT), which provides opportunities for IoT objects to form social communities. Existing social network models have been adopted by SIoT paradigm. The wide distribution of IoT objects and openness of social networks, however, make it more challenging to preserve privacy of IoT users. In this paper, we present a novel framework that preserves privacy against inference attacks on social network data through ranked retrieval models. We propose PVS, a privacy-preserving framework that involves the design of polymorphic value sets and ranking functions. PVS enables polymorphism of private attributes by allowing them to respond to different queries in different ways. We begin this work by identifying two classes of adversaries, authenticity-ignorant adversary, and authenticity-knowledgeable adversary, based on their knowledge of the distribution of private attributes. Next, we define the measurement functions of utility loss and propose PVSV and PVST that preserve privacy against authenticity-ignorant and authenticity-knowledgeable adversaries, respectively. We take into account the utility loss of query results in the design of PVSV and PVST. Finally, we show that PVSV and PVST meet the privacy guarantee with acceptable utility loss in extensive experiments over real-world datasets.
      PubDate: Wed, 28 Aug 2019 08:05:00 +000
       
  • Group Signatures with Message-Dependent Opening: Formal Definitions and
           Constructions
    • Abstract: This paper introduces a new capability for group signatures called message-dependent opening. It is intended to weaken the high trust placed on the opener; i.e., no anonymity against the opener is provided by an ordinary group signature scheme. In a group signature scheme with message-dependent opening (GS-MDO), in addition to the opener, we set up an admitter that is not able to extract any user’s identity but admits the opener to open signatures by specifying messages where signatures on the specified messages will be opened by the opener. The opener cannot extract the signer’s identity from any signature whose corresponding message is not specified by the admitter. This paper presents formal definitions of GS-MDO and proposes a generic construction of it from identity-based encryption and adaptive non-interactive zero-knowledge proofs. Moreover, we propose two specific constructions, one in the standard model and one in the random oracle model. Our scheme in the standard model is an instantiation of our generic construction but the message-dependent opening property is bounded. In contrast, our scheme in the random oracle model is not a direct instantiation of our generic construction but is optimized to increase efficiency and achieves the unbounded message-dependent opening property. Furthermore, we also demonstrate that GS-MDO implies identity-based encryption, thus implying that identity-based encryption is essential for designing GS-MDO schemes.
      PubDate: Mon, 26 Aug 2019 11:05:01 +000
       
  • A Neighbor Prototype Selection Method Based on CCHPSO for Intrusion
           Detection
    • Abstract: Nearest neighbor (NN) models play an important role in the intrusion detection system (IDS). However, with the advent of the era of big data, the NN model has the disadvantages of low efficiency, noise sensitivity, and high storage requirement. This paper presents a neighbor prototype selection method based on CCHPSO for intrusion detection. In the model, the prototype selection and feature weight adjustment are performed simultaneously and k-nearest neighbor (KNN) is used as the basic classifier. To deal with large-scale optimization problems, a cooperative coevolving algorithm based on hybrid standard particle swarm and binary particle swarm optimization, which employs the divide-and-conquer strategy, is proposed in this paper. Meanwhile, a fitness function based on the accuracy and data reduction rate is defined in the CCHPSO to obtain a set of appropriate prototypes and feature weights. The KDD99 and NSL datasets are used to assess the effectiveness of the method. The empirical results indicate that the data reduction rate of the proposed method is very high, ranging from 82.32% to 92.01%. Compared with all the data used, the proposed method can not only achieve comparable accuracy performance but also save a lot of storage and computing resources.
      PubDate: Tue, 20 Aug 2019 14:05:01 +000
       
  • A Secure and Efficient ECC-Based Anonymous Authentication Protocol
    • Abstract: Nowadays, remote user authentication protocol plays a great role in ensuring the security of data transmission and protecting the privacy of users for various network services. In this study, we discover two recently introduced anonymous authentication schemes are not as secure as they claimed, by demonstrating they suffer from offline password guessing attack, desynchronization attack, session key disclosure attack, failure to achieve user anonymity, or forward secrecy. Besides, we reveal two environment-specific authentication schemes have weaknesses like impersonation attack. To eliminate the security vulnerabilities of existing schemes, we propose an improved authentication scheme based on elliptic curve cryptosystem. We use BAN logic and heuristic analysis to prove our scheme provides perfect security attributes and is resistant to known attacks. In addition, the security and performance comparison show that our scheme is superior with better security and low computation and communication cost.
      PubDate: Tue, 20 Aug 2019 13:05:02 +000
       
  • Dynamics on Hybrid Complex Network: Botnet Modeling and Analysis of
           Medical IoT
    • Abstract: With the rapid development of Internet of things technology, the application of intelligent devices in the medical industry has become ubiquitous. Connected devices have revolutionized clinicians and patient care but also made modern hospitals vulnerable to cyber attacks. Among the security risks, botnets are of particular concern, which can be used to control thousands of devices for remote data theft and equipment destruction. In this paper, we propose a non-Markovian spread dynamics model to understand the effects of botnet propagation, which can characterize the hybrid contagion situation in reality. Based on the Susceptible-Adopted-Recovered model, we introduce nonredundant memory spread mechanism for global propagation, as a tuner to adjust spreading rate difference. For describing the proposed model, we extend a heterogeneous edge-based compartmental theory. Through extensive numerical simulations, we reveal that the growth pattern of the final adoption size versus the information transmission probability is discontinuous and how the final adoption size is affected by hybrid ratio α, global scope control factor ϵ, accumulated received information threshold T, and other parameters on ER network. Furthermore, we give the theory and simulation result on BA network and also compare the two hybrid methods—single infection in one time slice and double infections in one time slice—to evaluate the influence on final adoption size. We found in SIOT hybrid contagion scenario the final adoption size shows the phenomenon of a decline followed by an increase versus different hybrid ratio, and it is both verified in theory and numerical simulation. Through validation by thousands of experiments, our developed theory agrees well with the numerical simulations.
      PubDate: Sun, 18 Aug 2019 08:05:00 +000
       
  • Improved Malware Detection Model with Apriori Association Rule and
           Particle Swarm Optimization
    • Abstract: The incessant destruction and harmful tendency of malware on mobile devices has made malware detection an indispensable continuous field of research. Different matching/mismatching approaches have been adopted in the detection of malware which includes anomaly detection technique, misuse detection, or hybrid detection technique. In order to improve the detection rate of malicious application on the Android platform, a novel knowledge-based database discovery model that improves apriori association rule mining of a priori algorithm with Particle Swarm Optimization (PSO) is proposed. Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. In this method, the candidate detectors generated by particle swarm optimization form rules using apriori association rule. These rule models are used together with extraction algorithm to classify and detect malicious android application. Using a number of rule detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. The results of the experiments show that the proposed a priori association rule with Particle Swarm Optimization model has remarkable improvement over the existing contemporary detection models.
      PubDate: Thu, 08 Aug 2019 12:05:02 +000
       
  • Comprehensive Risk Identification Model for SCADA Systems
    • Abstract: The world is experiencing exponential growth in the use of SCADA systems in many industrial fields. The increased and considerable growth in information and communication technology has been forcing SCADA organizations to shift their SCADA systems from proprietary technology and protocol-based systems into internet-based ones. This paradigm shift has also increased the risks that target SCADA systems. To protect such systems, a risk management process is needed to identify all the risks. This study presents a detailed investigation on twenty-one scientific articles, guidelines, and databases related to SCADA risk identification parameters and provides a comparative study among them. The study next proposes a comprehensive risk identification model for SCADA systems. This model was built based on the risk identification parameters of ISO 31000 risk management principles and guidelines. The model states all risk identification parameters, identifies the relationships between those parameters, and uses a hierarchical-based method to draw complete risk scenarios. In addition, the proposed model defines the interdependency risk map among all risks stated in the model. This risk map can be used in understanding the evolution of the risks through time in SCADA systems. The proposed model is then transformed into a benchmark database containing 19,163 complete risk scenarios that can affect SCADA systems. Finally, a case study is presented to demonstrate one of the usages of the proposed model and its benchmark database. This case study provides 306 possible attack scenarios that Hacktivist can use to affect SCADA systems.
      PubDate: Tue, 06 Aug 2019 07:05:00 +000
       
  • Detecting Shilling Attacks with Automatic Features from Multiple Views
    • Abstract: Due to the openness of the recommender systems, the attackers are likely to inject a large number of fake profiles to bias the prediction of such systems. The traditional detection methods mainly rely on the artificial features, which are often extracted from one kind of user-generated information. In these methods, fine-grained interactions between users and items cannot be captured comprehensively, leading to the degradation of detection accuracy under various types of attacks. In this paper, we propose an ensemble detection method based on the automatic features extracted from multiple views. Firstly, to collaboratively discover the shilling profiles, the users’ behaviors are analyzed from multiple views including ratings, item popularity, and user-user graph. Secondly, based on the data preprocessed from multiple views, the stacked denoising autoencoders are used to automatically extract user features with different corruption rates. Moreover, the features extracted from multiple views are effectively combined based on principal component analysis. Finally, according to the features extracted with different corruption rates, the weak classifiers are generated and then integrated to detect attacks. The experimental results on the MovieLens, Netflix, and Amazon datasets indicate that the proposed method can effectively detect various attacks.
      PubDate: Mon, 05 Aug 2019 09:05:00 +000
       
  • Linear Secret Sharing Scheme with Reduced Number of Polynomials
    • Abstract: Threshold secret sharing is concerned with the splitting of a secret into shares and distributing them to some persons without revealing its information. Any ≤ persons possessing the shares have the ability to reconstruct the secret, but any persons less than cannot do the reconstruction. Linear secret sharing scheme is an important branch of secret sharing. The purpose of this paper is to propose a new polynomial based linear (,) secret sharing scheme, which is based on Shamir’s secret sharing scheme and ElGamal cryptosystem. Firstly, we withdraw some required properties of secret sharing scheme after reviewing the related schemes and ElGamal cryptosystem. The designed scheme provides the properties of security for the secret, recoverability of the secret, privacy of the secret, and cheating detection of the forged shares. It has half computation overhead than the previous linear scheme.
      PubDate: Sun, 04 Aug 2019 13:05:01 +000
       
  • Application-Level Unsupervised Outlier-Based Intrusion Detection and
           Prevention
    • Abstract: As cyber threats are permanently jeopardizing individuals privacy and organizations’ security, there have been several efforts to empower software applications with built-in immunity. In this paper, we present our approach to immune applications through application-level, unsupervised, outlier-based intrusion detection and prevention. Our framework allows tracking application domain objects all along the processing lifecycle. It also leverages the application business context and learns from production data, without creating any training burden on the application owner. Moreover, as our framework uses runtime application instrumentation, it incurs no additional cost on the application provider. We build a fine-grained and rich-feature application behavioral model that gets down to the method level and its invocation context. We define features to be independent from the variable structure of method invocation parameters and returned values, while preserving security-relevant information. We implemented our framework in a Java environment and evaluated it on a widely-used, enterprise-grade, and open-source ERP. We tested several unsupervised outlier detection algorithms and distance functions. Our framework achieved the best results in terms of effectiveness using the Local Outlier Factor algorithm and the Clark distance, while the average instrumentation overhead per intercepted call remains acceptable.
      PubDate: Sun, 28 Jul 2019 12:05:00 +000
       
 
 
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