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Xu, Hui, Zhou, Yangfan, Lyu, Michael.  2016.  N-version Obfuscation. Proceedings of the 2Nd ACM International Workshop on Cyber-Physical System Security. :22–33.

Although existing for decades, software tampering attack is still a main threat to systems, such as Android, and cyber physical systems. Many approaches have been proposed to thwart specific procedures of tampering, e.g., obfuscation and self-checksumming. However, none of them can achieve theoretically tamper-proof without the protection of hardware circuit. Rather than proposing new tricks against tampering attacks, we focus on impeding the replication of software tampering via program diversification, and thus pose a scalability barrier against the attacks. Our idea, namely N-version obfuscation (NVO), is to automatically generate and deliver same featured, but functionally nonequivalent software copies to different machines or users. In this paper, we investigate such an idea on Android platform. We carefully design a candidate NVO solution for networked apps, which leverages a Message Authentication Code (MAC) mechanism to generate the functionally nonequivalent diversities. Our evaluation result shows that the time required for breaking such a software system increases linearly with respect to the number of software versions. In this way, attackers would suffer great scalability issues, considering that an app can have millions of users. With minimal NVO costs, effective tamper-resistant security can therefore be established.

Han, K., Zhang, W., Liu, C..  2020.  Numerical Study of Acoustic Propagation Characteristics in the Multi-scale Seafloor Random Media. 2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP). :135–138.
There is some uncertainty as to the applicability or accuracy of current theories for wave propagation in sediments. Numerical modelling of acoustic data has long been recognized to be a powerful method of understanding of complicated wave propagation and interaction. In this paper, we used the coupled two-dimensional PSM-BEM program to simulate the process of acoustic wave propagation in the seafloor with distributed multi-scale random media. The effects of fluid flow between the pores and the grains with multi-scale distribution were considered. The results show that the coupled PSM-BEM program can be directly applied to both high and low frequency seafloor acoustics. A given porous frame with the pore space saturated with fluid can greatly increase the magnitude of acoustic anisotropy. acoustic wave velocity dispersion and attenuation are significant over a frequency range which spans at least two orders of magnitude.
Huang, Hsiang-Hung, Toprasertpong, Kasidit, Delamarre, Amaury, Watanabe, Kentaroh, Sugiyama, Masakazu, Nakano, Yoshiaki.  2019.  Numerical Demonstration of Trade-off between Carrier Confinement Effect and Carrier Transport for Multiple-Quantum-Well Based High-Efficiency InGaP Solar Cells. 2019 Compound Semiconductor Week (CSW). :1-2.

To promote InGaP solar cell efficiency toward the theoretical limit, one promising approach is to incorporate multiple quantum wells (MQWs) into the InGaP host and improve its open-circuit voltage by facilitating radiative carrier recombination owing to carrier confinement. In this research, we demonstrate numerically that a strain-balanced (SB) In1-xGaxP/In1-yGayP MQW enhances confined carrier density while degrades the effective carrier mobility. However, a smart design of the MQW structure is possible by considering quantitatively the trade-off between carrier confinement effect and carrier transport, and MQW can be advantageous over the InGaP bulk material for boosting photovoltaic efficiency.

Schulz, Lukas, Schulz, Dirk.  2018.  Numerical Analysis of the Transient Behavior of the Non-Equilibrium Quantum Liouville Equation. IEEE Transactions on Nanotechnology. 17:1197—1205.

The numerical analysis of transient quantum effects in heterostructure devices with conventional numerical methods tends to pose problems. To overcome these limitations, a novel numerical scheme for the transient non-equilibrium solution of the quantum Liouville equation utilizing a finite volume discretization technique is proposed. Additionally, the solution with regard to the stationary regime, which can serve as a reference solution, is inherently included within the discretization scheme for the transient regime. Resulting in a highly oscillating interference pattern of the statistical density matrix as well in the stationary as in the transient regime, the reflecting nature of the conventional boundary conditions can be an additional source of error. Avoiding these non-physical reflections, the concept of a complex absorbing potential used for the Schrödinger equation is utilized to redefine the drift operator in order to render open boundary conditions for quantum transport equations. Furthermore, the method allows the application of the commonly used concept of inflow boundary conditions.

Cui, Liqun, Dong, Mianxiong, Ota, Kaoru, Wu, Jun, Li, Jianhua, Wu, Yang.  2019.  NSTN: Name-Based Smart Tracking for Network Status in Information-Centric Internet of Things. ICC 2019 - 2019 IEEE International Conference on Communications (ICC). :1–6.
Internet of Things(IoT) is an important part of the new generation of information technology and an important stage of development in the era of informatization. As a next generation network, Information Centric Network (ICN) has been introduced into the IoT, leading to the content independence of IC-IoT. To manage the changing network conditions and diagnose the cause of anomalies within it, network operators must obtain and analyze network status information from monitoring tools. However, traditional network supervision method will not be applicable to IC-IoT centered on content rather than IP. Moreover, the surge in information volume will also bring about insufficient information distribution, and the data location in the traditional management information base is fixed and cannot be added or deleted. To overcome these problems, we propose a name-based smart tracking system to store network state information in the IC-IoT. Firstly, we design a new structure of management information base that records various network state information and changes its naming format. Secondly, we use a tracking method to obtain the required network status information. When the manager issues a status request, each data block has a defined data tracking table to record past requests, the location of the status data required can be located according to it. Thirdly, we put forward an adaptive network data location replacement strategy based on the importance of stored data blocks, so that the information with higher importance will be closer to the management center for more efficient acquisition. Simulation results indicate the feasibility of the proposed scheme.
Hwang, T..  2017.  NSF GENI cloud enabled architecture for distributed scientific computing. 2017 IEEE Aerospace Conference. :1–8.

GENI (Global Environment for Network Innovations) is a National Science Foundation (NSF) funded program which provides a virtual laboratory for networking and distributed systems research and education. It is well suited for exploring networks at a scale, thereby promoting innovations in network science, security, services and applications. GENI allows researchers obtain compute resources from locations around the United States, connect compute resources using 100G Internet2 L2 service, install custom software or even custom operating systems on these compute resources, control how network switches in their experiment handle traffic flows, and run their own L3 and above protocols. GENI architecture incorporates cloud federation. With the federation, cloud resources can be federated and/or community of clouds can be formed. The heart of federation is user identity and an ability to “advertise” cloud resources into community including compute, storage, and networking. GENI administrators can carve out what resources are available to the community and hence a portion of GENI resources are reserved for internal consumption. GENI architecture also provides “stitching” of compute and storage resources researchers request. This provides L2 network domain over Internet2's 100G network. And researchers can run their Software Defined Networking (SDN) controllers on the provisioned L2 network domain for a complete control of networking traffic. This capability is useful for large science data transfer (bypassing security devices for high throughput). Renaissance Computing Institute (RENCI), a research institute in the state of North Carolina, has developed ORCA (Open Resource Control Architecture), a GENI control framework. ORCA is a distributed resource orchestration system to serve science experiments. ORCA provides compute resources as virtual machines and as well as baremetals. ORCA based GENI ra- k was designed to serve both High Throughput Computing (HTC) and High Performance Computing (HPC) type of computes. Although, GENI is primarily used in various universities and research entities today, GENI architecture can be leveraged in the commercial, aerospace and government settings. This paper will go over the architecture of GENI and discuss the GENI architecture for scientific computing experiments.

Karmaker Santu, Shubhra Kanti, Bindschadler, Vincent, Zhai, ChengXiang, Gunter, Carl A..  2018.  NRF: A Naive Re-Identification Framework. Proceedings of the 2018 Workshop on Privacy in the Electronic Society. :121-132.

The promise of big data relies on the release and aggregation of data sets. When these data sets contain sensitive information about individuals, it has been scalable and convenient to protect the privacy of these individuals by de-identification. However, studies show that the combination of de-identified data sets with other data sets risks re-identification of some records. Some studies have shown how to measure this risk in specific contexts where certain types of public data sets (such as voter roles) are assumed to be available to attackers. To the extent that it can be accomplished, such analyses enable the threat of compromises to be balanced against the benefits of sharing data. For example, a study that might save lives by enabling medical research may be enabled in light of a sufficiently low probability of compromise from sharing de-identified data. In this paper, we introduce a general probabilistic re-identification framework that can be instantiated in specific contexts to estimate the probability of compromises based on explicit assumptions. We further propose a baseline of such assumptions that enable a first-cut estimate of risk for practical case studies. We refer to the framework with these assumptions as the Naive Re-identification Framework (NRF). As a case study, we show how we can apply NRF to analyze and quantify the risk of re-identification arising from releasing de-identified medical data in the context of publicly-available social media data. The results of this case study show that NRF can be used to obtain meaningful quantification of the re-identification risk, compare the risk of different social media, and assess risks of combinations of various demographic attributes and medical conditions that individuals may voluntarily disclose on social media.

Hall-Andersen, Mathias, Wong, David, Sullivan, Nick, Chator, Alishah.  2018.  nQUIC: Noise-Based QUIC Packet Protection. Proceedings of the Workshop on the Evolution, Performance, and Interoperability of QUIC. :22–28.
We present nQUIC, a variant of QUIC-TLS that uses the Noise protocol framework for its key exchange and basis of its packet protector with no semantic transport changes. nQUIC is designed for deployment in systems and for applications that assert trust in raw public keys rather than PKI-based certificate chains. It uses a fixed key exchange algorithm, compromising agility for implementation and verification ease. nQUIC provides mandatory server and optional client authentication, resistance to Key Compromise Impersonation attacks, and forward and future secrecy of traffic key derivation, which makes it favorable to QUIC-TLS for long-lived QUIC connections in comparable applications. We developed two interoperable prototype implementations written in Go and Rust. Experimental results show that nQUIC finishes its handshake in a comparable amount of time as QUIC-TLS.
Razi, Afsaneh, Hua, Kien A., Majidi, Akbar.  2017.  NQ-GPLS: N-Queen Inspired Gateway Placement and Learning Automata-Based Gateway Selection in Wireless Mesh Network. Proceedings of the 15th ACM International Symposium on Mobility Management and Wireless Access. :41–44.

This paper discusses two issues with multi-channel multi-radio Wireless Mesh Networks (WMN): gateway placement and gateway selection. To address these issues, a method will be proposed that places gateways at strategic locations to avoid congestion and adaptively learns to select a more efficient gateway for each wireless router by using learning automata. This method, called the N-queen Inspired Gateway Placement and Learning Automata-based Selection (NQ-GPLS), considers multiple metrics such as loss ratio, throughput, load at the gateways and delay. Simulation results from NS-2 simulator demonstrate that NQ-GPLS can significantly improve the overall network performance compared to a standard WMN.

Martin, H., Entrena, L., Dupuis, S., Natale, G. Di.  2018.  A Novel Use of Approximate Circuits to Thwart Hardware Trojan Insertion and Provide Obfuscation. 2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS). :41-42.

Hardware Trojans have become in the last decade a major threat in the Integrated Circuit industry. Many techniques have been proposed in the literature aiming at detecting such malicious modifications in fabricated ICs. For the most critical circuits, prevention methods are also of interest. The goal of such methods is to prevent the insertion of a Hardware Trojan thanks to ad-hoc design rules. In this paper, we present a novel prevention technique based on approximation. An approximate logic circuit is a circuit that performs a possibly different but closely related logic function, so that it can be used for error detection or error masking where it overlaps with the original circuit. We will show how this technique can successfully detect the presence of Hardware Trojans, with a solution that has a smaller impact than triplication.

Athanasiou, G., Fengou, M.-A., Beis, A., Lymberopoulos, D..  2014.  A novel trust evaluation method for Ubiquitous Healthcare based on cloud computational theory. Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. :4503-4506.

The notion of trust is considered to be the cornerstone on patient-psychiatrist relationship. Thus, a trustfully background is fundamental requirement for provision of effective Ubiquitous Healthcare (UH) service. In this paper, the issue of Trust Evaluation of UH Providers when register UH environment is addressed. For that purpose a novel trust evaluation method is proposed, based on cloud theory, exploiting User Profile attributes. This theory mimics human thinking, regarding trust evaluation and captures fuzziness and randomness of this uncertain reasoning. Two case studies are investigated through simulation in MATLAB software, in order to verify the effectiveness of this novel method.

Li, T., Wu, L., Zhang, X., Wu, X., Zhou, J., Wang, X..  2017.  A novel transition effect ring oscillator based true random number generator for a security SoC. 2017 International Conference on Electron Devices and Solid-State Circuits (EDSSC). :1–2.

The transition effect ring oscillator (TERO) based true random number generator (TRNG) was proposed by Varchola and Drutarovsky in 2010. There were several stochastic models for this advanced TRNG based on ring oscillator. This paper proposed an improved TERO based TRNG and implements both on Altera Cyclone series FPGA platform and on a 0.13um CMOS ASIC process. FPGA experimental results show that this balanced TERO TRNG is in good performance as the experimental data results past the national institute of standards and technology (NIST) test in 1M bit/s. The TRNG is feasible for a security SoC.

Jilnaraj, A. R., Geetharanjin, P. R., Lethakumary, B..  2019.  A Novel Technique for Biometric Data Protection in Remote Authentication System. 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). 1:681—686.
Remote authentication via biometric features has received much attention recently, hence the security of biometric data is of great importance. Here a crypto-steganography method applied for the protection of biometric data is implemented. It include semantic segmentation, chaotic encryption, data hiding and fingerprint recognition to avoid the risk of spoofing attacks. Semantically segmented image of the person to be authenticated is used as the cover image and chaotic encrypted fingerprint image is used as secret image here. Chaotic encrypted fingerprint image is embedded into the cover image using Integer Wavelet Transform (IWT). Extracted fingerprint image is then compared with the fingerprints in database to authenticate the person. Qualified Significant Wavelet Trees (QSWT`s) of the cover image act as the target coefficients to insert the secret image. IWT provide both invisibility and resistance against the lossy transmissions. Experimental result shows that the semantic segmentation reduces the bandwidth efficiently. In addition, chaotic encryption and IWT based data hiding increases the security of the transmitted biometric data.
Shamieh, F., Alharbi, R..  2018.  Novel Sybil Defense Scheme for Peer–to–peer Applications. 2018 21st Saudi Computer Society National Computer Conference (NCC). :1–8.

The importance of peer-to-peer (P2P) network overlays produced enormous interest in the research community due to their robustness, scalability, and increase of data availability. P2P networks are overlays of logically connected hosts and other nodes including servers. P2P networks allow users to share their files without the need for any centralized servers. Since P2P networks are largely constructed of end-hosts, they are susceptible to abuse and malicious activity, such as sybil attacks. Impostors perform sybil attacks by assigning nodes multiple addresses, as opposed to a single address, with the goal of degrading network quality. Sybil nodes will spread malicious data and provide bogus responses to requests. To prevent sybil attacks from occurring, a novel defense mechanism is proposed. In the proposed scheme, the DHT key-space is divided and treated in a similar manner to radio frequency allocation incensing. An overlay of trusted nodes is used to detect and handle sybil nodes with the aid of source-destination pairs reporting on each other. The simulation results show that the proposed scheme detects sybil nodes in large sized networks with thousands of interactions.

Ayaida, Marwane, Messai, Nadhir, Wilhelm, Geoffrey, Najeh, Sameh.  2019.  A Novel Sybil Attack Detection Mechanism for C-ITS. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :913–918.

Cooperative Intelligent Transport Systems (C-ITS) are expected to play an important role in our lives. They will improve the traffic safety and bring about a revolution on the driving experience. However, these benefits are counterbalanced by possible attacks that threaten not only the vehicle's security, but also passengers' lives. One of the most common attacks is the Sybil attack, which is even more dangerous than others because it could be the starting point of many other attacks in C-ITS. This paper proposes a distributed approach allowing the detection of Sybil attacks by using the traffic flow theory. The key idea here is that each vehicle will monitor its neighbourhood in order to detect an eventual Sybil attack. This is achieved by a comparison between the real accurate speed of the vehicle and the one estimated using the V2V communications with vehicles in the vicinity. The estimated speed is derived by using the traffic flow fundamental diagram of the road's portion where the vehicles are moving. This detection algorithm is validated through some extensive simulations conducted using the well-known NS3 network simulator with SUMO traffic simulator.

Dabas, N., Singh, R. P., Kher, G., Chaudhary, V..  2017.  A novel SVD and online sequential extreme learning machine based watermark method for copyright protection. 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–5.

For the increasing use of internet, it is equally important to protect the intellectual property. And for the protection of copyright, a blind digital watermark algorithm with SVD and OSELM in the IWT domain has been proposed. During the embedding process, SVD has been applied to the coefficient blocks to get the singular values in the IWT domain. Singular values are modulated to embed the watermark in the host image. Online sequential extreme learning machine is trained to learn the relationship between the original coefficient and the corresponding watermarked version. During the extraction process, this trained OSELM is used to extract the embedded watermark logo blindly as no original host image is required during this process. The watermarked image is altered using various attacks like blurring, noise, sharpening, rotation and cropping. The experimental results show that the proposed watermarking scheme is robust against various attacks. The extracted watermark has very much similarity with the original watermark and works good to prove the ownership.

Zhu, Mengeheng, Shi, Hong.  2018.  A Novel Support Vector Machine Algorithm for Missing Data. Proceedings of the 2Nd International Conference on Innovation in Artificial Intelligence. :48–53.
Missing data problem often occurs in data analysis. The most common way to solve this problem is imputation. But imputation methods are only suitable for dealing with a low proportion of missing data, when assuming that missing data satisfies MCAR (Missing Completely at Random) or MAR (Missing at Random). In this paper, considering the reasons for missing data, we propose a novel support vector machine method using a new kernel function to solve the problem with a relatively large proportion of missing data. This method makes full use of observed data to reduce the error caused by filling a large number of missing values. We validate our method on 4 data sets from UCI Repository of Machine Learning. The accuracy, F-score, Kappa statistics and recall are used to evaluate the performance. Experimental results show that our method achieve significant improvement in terms of classification results compared with common imputation methods, even when the proportion of missing data is high.
Rezaei, Aref, Farzinvash, Leili, Farzamnia, Ali.  2019.  A Novel Steganography Algorithm using Edge Detection and MPC Algorithm. 2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC). :49—54.

With the rapid development of the Internet, preserving the security of confidential data has become a challenging issue. An effective method to this end is to apply steganography techniques. In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. The proposed edge detection scheme partitions the given image, namely cover image, into blocks. Next, it identifies the edge blocks based on the variance of their corner pixels. Embedding the confidential data in sharp edges causes less distortion in comparison to the smooth areas. To diminish the imposed distortion by data embedding in edge blocks, we employ LSB and MPC algorithms. In the proposed scheme, the blocks are split into some groups firstly. Next, a full tree is constructed per group using the LSBs of its pixels. This tree is converted into another full tree in some rounds. The resultant tree is used to modify the considered LSBs. After the accomplishment of the data embedding process, the final image, which is called stego image, is derived. According to the experimental results, the proposed algorithm improves PSNR with at least 5.4 compared to the previous schemes.

Mukhandi, M., Portugal, D., Pereira, S., Couceiro, M. S..  2019.  A novel solution for securing robot communications based on the MQTT protocol and ROS. 2019 IEEE/SICE International Symposium on System Integration (SII). :608—613.

With the growing use of the Robot Operating System (ROS), it can be argued that it has become a de-facto framework for developing robotic solutions. ROS is used to build robotic applications for industrial automation, home automation, medical and even automatic robotic surveillance. However, whenever ROS is utilized, security is one of the main concerns that needs to be addressed in order to ensure a secure network communication of robots. Cyber-attacks may hinder evolution and adaptation of most ROS-enabled robotic systems for real-world use over the Internet. Thus, it is important to address and prevent security threats associated with the use of ROS-enabled applications. In this paper, we propose a novel approach for securing ROS-enabled robotic system by integrating ROS with the Message Queuing Telemetry Transport (MQTT) protocol. We manage to secure robots' network communications by providing authentication and data encryption, therefore preventing man-in-the-middle and hijacking attacks. We also perform real-world experiments to assess how the performance of a ROS-enabled robotic surveillance system is affected by the proposed approach.

L. Rivière, J. Bringer, T. H. Le, H. Chabanne.  2015.  "A novel simulation approach for fault injection resistance evaluation on smart cards". 2015 IEEE Eighth International Conference on Software Testing, Verification and Validation Workshops (ICSTW). :1-8.

Physical perturbations are performed against embedded systems that can contain valuable data. Such devices and in particular smart cards are targeted because potential attackers hold them. The embedded system security must hold against intentional hardware failures that can result in software errors. In a malicious purpose, an attacker could exploit such errors to find out secret data or disrupt a transaction. Simulation techniques help to point out fault injection vulnerabilities and come at an early stage in the development process. This paper proposes a generic fault injection simulation tool that has the particularity to embed the injection mechanism into the smart card source code. By its embedded nature, the Embedded Fault Simulator (EFS) allows us to perform fault injection simulations and side-channel analyses simultaneously. It makes it possible to achieve combined attacks, multiple fault attacks and to perform backward analyses. We appraise our approach on real, modern and complex smart card systems under data and control flow fault models. We illustrate the EFS capacities by performing a practical combined attack on an Advanced Encryption Standard (AES) implementation.

Dong, Jiqun, Qiao, Xiuquan.  2016.  A novel service provisioning mechanism in content-centric networking. :319–326.

Content-Centric Networking (CCN) has emerged as a clean-slate future Internet architecture to address the challenges faced by traditional IP network, such as mobility, scalable content distribution and security. As a novel networking paradigm, CCN is built on named data, not host address and decouples the content from location. By the in-network caching, consumer can fetch the interested content from the closest routers.

Ben Dhief, Yosra, Djemaiel, Yacine, Rekhis, Slim, Boudriga, Noureddine.  2016.  A Novel Sensor Cloud Based SCADA Infrastructure for Monitoring and Attack Prevention. Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media. :45–49.

The infrastructures of Supervisory Control and Data Acquisition (SCADA) systems have evolved through time in order to provide more efficient supervision services. Despite the changes made on SCADA architectures, several enhancements are still required to address the need for: a) large scale supervision using a high number of sensors, b) reduction of the reaction time when a malicious activity is detected; and c) the assurance of a high interoperability between SCADA systems in order to prevent the propagation of incidents. In this context, we propose a novel sensor cloud based SCADA infrastructure to monitor large scale and inter-dependant critical infrastructures, making an effective use of sensor clouds to increase the supervision coverage and the processing time. It ensures also the interoperability between interdependent SCADAs by offering a set of services to SCADA, which are created through the use of templates and are associated to set of virtual sensors. A simulation is conducted to demonstrate the effectiveness of the proposed architecture.

Yuan, Yali, Kaklamanos, Georgios, Hogrefe, Dieter.  2016.  A Novel Semi-Supervised Adaboost Technique for Network Anomaly Detection. Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems. :111–114.

With the developing of Internet, network intrusion has become more and more common. Quickly identifying and preventing network attacks is getting increasingly more important and difficult. Machine learning techniques have already proven to be robust methods in detecting malicious activities and network threats. Ensemble-based and semi-supervised learning methods are some of the areas that receive most attention in machine learning today. However relatively little attention has been given in combining these methods. To overcome such limitations, this paper proposes a novel network anomaly detection method by using a combination of a tri-training approach with Adaboost algorithms. The bootstrap samples of tri-training are replaced by three different Adaboost algorithms to create the diversity. We run 30 iteration for every simulation to obtain the average results. Simulations indicate that our proposed semi-supervised Adaboost algorithm is reproducible and consistent over a different number of runs. It outperforms other state-of-the-art learning algorithms, even with a small part of labeled data in the training phase. Specifically, it has a very short execution time and a good balance between the detection rate as well as the false-alarm rate.

Monge, Marco Antonio Sotelo, Vidal, Jorge Maestre, Villalba, Luis Javier García.  2018.  A Novel Self-Organizing Network Solution Towards Crypto-ransomware Mitigation. Proceedings of the 13th International Conference on Availability, Reliability and Security. :48:1–48:10.
In the last decade, crypto-ransomware evolved from a family of malicious software with scarce repercussion in the research community, to a sophisticated and highly effective intrusion method positioned in the spotlight of the main organizations for cyberdefense. Its modus operandi is characterized by fetching the assets to be blocked, their encryption, and triggering an extortion process that leads the victim to pay for the key that allows their recovery. This paper reviews the evolution of crypto-ransomware focusing on the implication of the different advances in communication technologies that empowered its popularization. In addition, a novel defensive approach based on the Self-Organizing Network paradigm and the emergent communication technologies (e.g. Software-Defined Networking, Network Function Virtualization, Cloud Computing, etc.) is proposed. They enhance the orchestration of smart defensive deployments that adapt to the status of the monitoring environment and facilitate the adoption of previously defined risk management policies. In this way it is possible to efficiently coordinate the efforts of sensors and actuators distributed throughout the protected environment without supervision by human operators, resulting in greater protection with increased viability
Makhoul, Rawad, Maynard, Xavier, Perichon, Pierre, Frey, David, Jeannin, Pierre-Olivier, Lembeye, Yves.  2018.  A Novel Self Oscillating Class Phi2 Inverter Topology. 2018 2nd European Conference on Electrical Engineering and Computer Science (EECS). :7—10.

The class φ2 is a single transistor, fast transient inverter topology often associated with power conversion at very high frequency (VHF: 30MHz-300MHz). At VHF, gate drivers available on the market fail to provide the adequate transistor switching signal. Hence, there is a need for new power topologies that do no make use of gate drivers but are still suitable for power conversion at VHF. In This paper, we introduce a new class φ;2 topology that incorporates an oscillator, which takes the drain signal through a feedback circuit in order to force the transistor switching. A design methodology is provided and a 1MHz 20V input prototype is built in order to validate the topology behaviour.