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2020-01-13
Lipps, Christoph, Krummacker, Dennis, Schotten, Hans Dieter.  2019.  Securing Industrial Wireless Networks: Enhancing SDN with PhySec. 2019 Conference on Next Generation Computing Applications (NextComp). :1–7.
The requirements regarding network management defined by the continuously rising amount of interconnected devices in the industrial landscape turns it into an increasingly complex task. Associated by the fusion of technologies up to Cyber-Physical Production Systems (CPPS) and the Industrial Internet of Things (IIoT) with its multitude of communicating sensors and actuators new demands arise. In particular, the driving forces of this development, mobility and flexibility, are affecting today's networks. However, it is precisely these wireless solutions, as enabler for this advancement, that create new attack vectors and cyber-security threats. Furthermore, many cryptographic procedures, intended to secure the networks, require additional overhead, which is limiting the transmission bandwidth and speed as well. For this reason, new and efficient solutions must be developed and applied, in order to secure the existing, as well as the future, industrial communication networks. This work proposes a conceptual approach, consisting of a combination of Software-Defined Networking (SDN) and Physical Layer Security (PhySec) to satisfy the network security requirements. Use cases are explained that demonstrate the appropriateness of the approach and it is shown that this is a easy to use and resource efficient, but nevertheless sound and secure approach.
2019-12-18
Chugunkov, Ilya V., Fedorov, Leonid O., Achmiz, Bela Sh., Sayfullina, Zarina R..  2018.  Development of the Algorithm for Protection against DDoS-Attacks of Type Pulse Wave. 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). :292-294.

Protection from DDoS-attacks is one of the most urgent problems in the world of network technologies. And while protect systems has algorithms for detection and preventing DDoS attacks, there are still some unresolved problems. This article is devoted to the DDoS-attack called Pulse Wave. Providing a brief introduction to the world of network technologies and DDoS-attacks, in particular, aims at the algorithm for protecting against DDoS-attack Pulse Wave. The main goal of this article is the implementation of traffic classifier that adds rules for infected computers to put them into a separate queue with limited bandwidth. This approach reduces their load on the service and, thus, firewall neutralises the attack.

2019-11-19
Wang, Bo, Wang, Xunting.  2018.  Vulnerability Assessment Method for Cyber Physical Power System Considering Node Heterogeneity. 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). :1109-1113.
In order to make up for the shortcomings of traditional evaluation methods neglecting node difference, a vulnerability assessment method considering node heterogeneity for cyber physical power system (CPPS) is proposed. Based on the entropy of the power flow and complex network theory, we establish heterogeneity evaluation index system for CPPS, which considers the survivability of island survivability and short-term operation of the communication network. For mustration, hierarchical CPPS model and distributed CPPS model are established respectively based on partitioning characteristic and different relationships of power grid and communication network. Simulation results show that distributed system is more robust than hierarchical system of different weighting factor whether under random attack or deliberate attack and a hierarchical system is more sensitive to the weighting factor. The proposed method has a better recognition effect on the equilibrium of the network structure and can assess the vulnerability of CPPS more accurately.
2019-10-22
Khelf, Roumaissa, Ghoualmi-Zine, Nacira.  2018.  IPsec/Firewall Security Policy Analysis: A Survey. 2018 International Conference on Signal, Image, Vision and their Applications (SIVA). :1–7.
As the technology reliance increases, computer networks are getting bigger and larger and so are threats and attacks. Therefore Network security becomes a major concern during this last decade. Network Security requires a combination of hardware devices and software applications. Namely, Firewalls and IPsec gateways are two technologies that provide network security protection and repose on security policies which are maintained to ensure traffic control and network safety. Nevertheless, security policy misconfigurations and inconsistency between the policy's rules produce errors and conflicts, which are often very hard to detect and consequently cause security holes and compromise the entire system functionality. In This paper, we review the related approaches which have been proposed for security policy management along with surveying the literature for conflicts detection and resolution techniques. This work highlights the advantages and limitations of the proposed solutions for security policy verification in IPsec and Firewalls and gives an overall comparison and classification of the existing approaches.
2019-09-09
Zhou, X., Lu, Y., Wang, Y., Yan, X..  2018.  Overview on Moving Target Network Defense. 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC). :821–827.
Moving Target Defense (MTD) is a research hotspot in the field of network security. Moving Target Network Defense (MTND) is the implementation of MTD at network level. Numerous related works have been proposed in the field of MTND. In this paper, we focus on the scope and area of MTND, systematically present the recent representative progress from four aspects, including IP address and port mutation, route mutation, fingerprint mutation and multiple mutation, and put forward the future development directions. Several new perspectives and elucidations on MTND are rendered.
2019-08-26
Zhang, Y., Ya\u gan, O..  2018.  Modeling and Analysis of Cascading Failures in Interdependent Cyber-Physical Systems. 2018 IEEE Conference on Decision and Control (CDC). :4731-4738.

Integrated cyber-physical systems (CPSs), such as the smart grid, are becoming the underpinning technology for major industries. A major concern regarding such systems are the seemingly unexpected large scale failures, which are often attributed to a small initial shock getting escalated due to intricate dependencies within and across the individual counterparts of the system. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as cascading failures. Our framework consists of two networks that have inherently different characteristics governing their intra-dependency: i) a cyber-network where a node is deemed to be functional as long as it belongs to the largest connected (i.e., giant) component; and ii) a physical network where nodes are given an initial flow and a capacity, and failure of a node results with redistribution of its flow to the remaining nodes, upon which further failures might take place due to overloading. Furthermore, it is assumed that these two networks are inter-dependent. For simplicity, we consider a one-to-one interdependency model where every node in the cyber-network is dependent upon and supports a single node in the physical network, and vice versa. We provide a thorough analysis of the dynamics of cascading failures in this interdependent system initiated with a random attack. The system robustness is quantified as the surviving fraction of nodes at the end of cascading failures, and is derived in terms of all network parameters involved. Analytic results are supported through an extensive numerical study. Among other things, these results demonstrate the ability of our model to capture the unexpected nature of large-scale failures, and provide insights on improving system robustness.

2019-06-10
Ponmaniraj, S., Rashmi, R., Anand, M. V..  2018.  IDS Based Network Security Architecture with TCP/IP Parameters Using Machine Learning. 2018 International Conference on Computing, Power and Communication Technologies (GUCON). :111-114.

This computer era leads human to interact with computers and networks but there is no such solution to get rid of security problems. Securities threats misleads internet, we are sometimes losing our hope and reliability with many server based access. Even though many more crypto algorithms are coming for integrity and authentic data in computer access still there is a non reliable threat penetrates inconsistent vulnerabilities in networks. These vulnerable sites are taking control over the user's computer and doing harmful actions without user's privileges. Though Firewalls and protocols may support our browsers via setting certain rules, still our system couldn't support for data reliability and confidentiality. Since these problems are based on network access, lets we consider TCP/IP parameters as a dataset for analysis. By doing preprocess of TCP/IP packets we can build sovereign model on data set and clump cluster. Further the data set gets classified into regular traffic pattern and anonymous pattern using KNN classification algorithm. Based on obtained pattern for normal and threats data sets, security devices and system will set rules and guidelines to learn by it to take needed stroke. This paper analysis the computer to learn security actions from the given data sets which already exist in the previous happens.

2019-05-09
Lu, G., Feng, D..  2018.  Network Security Situation Awareness for Industrial Control System Under Integrity Attacks. 2018 21st International Conference on Information Fusion (FUSION). :1808-1815.

Due to the wide implementation of communication networks, industrial control systems are vulnerable to malicious attacks, which could cause potentially devastating results. Adversaries launch integrity attacks by injecting false data into systems to create fake events or cover up the plan of damaging the systems. In addition, the complexity and nonlinearity of control systems make it more difficult to detect attacks and defense it. Therefore, a novel security situation awareness framework based on particle filtering, which has good ability in estimating state for nonlinear systems, is proposed to provide an accuracy understanding of system situation. First, a system state estimation based on particle filtering is presented to estimate nodes state. Then, a voting scheme is introduced into hazard situation detection to identify the malicious nodes and a local estimator is constructed to estimate the actual system state by removing the identified malicious nodes. Finally, based on the estimated actual state, the actual measurements of the compromised nodes are predicted by using the situation prediction algorithm. At the end of this paper, a simulation of a continuous stirred tank is conducted to verify the efficiency of the proposed framework and algorithms.

2019-05-01
Naik, N., Shang, C., Shen, Q., Jenkins, P..  2018.  Vigilant Dynamic Honeypot Assisted by Dynamic Fuzzy Rule Interpolation. 2018 IEEE Symposium Series on Computational Intelligence (SSCI). :1731–1738.

Dynamic Fuzzy Rule Interpolation (D-FRI) offers a dynamic rule base for fuzzy systems which is especially useful for systems with changing requirements and limited prior knowledge. This suggests a possible application of D-FRI in the area of network security due to the volatility of the traffic. A honeypot is a valuable tool in the field of network security for baiting attackers and collecting their information. However, typically designed with fewer resources they are not considered as a primary security tool for use in network security. Consequently, such honeypots can be vulnerable to many security attacks. One such attack is a spoofing attack which can cause severe damage to the honeypot, making it inefficient. This paper presents a vigilant dynamic honeypot based on the D-FRI approach for use in predicting and alerting of spoofing attacks on the honeypot. First, it proposes a technique for spoofing attack identification based on the analysis of simulated attack data. Then, the paper employs the identification technique to develop a D-FRI based vigilant dynamic honeypot, allowing the honeypot to predict and alert that a spoofing attack is taking place in the absence of matching rules. The resulting system is capable of learning and maintaining a dynamic rule base for more accurate identification of potential spoofing attacks with respect to the changing traffic conditions of the network.

Rayavel, P., Rathnavel, P., Bharathi, M., Kumar, T. Siva.  2018.  Dynamic Traffic Control System Using Edge Detection Algorithm. 2018 International Conference on Soft-Computing and Network Security (ICSNS). :1-5.

As the traffic congestion increases on the transport network, Payable on the road to slower speeds, longer falter times, as a consequence bigger vehicular queuing, it's necessary to introduce smart way to reduce traffic. We are already edging closer to ``smart city-smart travel''. Today, a large number of smart phone applications and connected sat-naves will help get you to your destination in the quickest and easiest manner possible due to real-time data and communication from a host of sources. In present situation, traffic lights are used in each phase. The other way is to use electronic sensors and magnetic coils that detect the congestion frequency and monitor traffic, but found to be more expensive. Hence we propose a traffic control system using image processing techniques like edge detection. The vehicles will be detected using images instead of sensors. The cameras are installed alongside of the road and it will capture image sequence for every 40 seconds. The digital image processing techniques will be applied to analyse and process the image and according to that the traffic signal lights will be controlled.

2019-04-05
Dong, X., Hu, J., Cui, Y..  2018.  Overview of Botnet Detection Based on Machine Learning. 2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE). :476-479.

With the rapid development of the information industry, the applications of Internet of things, cloud computing and artificial intelligence have greatly affected people's life, and the network equipment has increased with a blowout type. At the same time, more complex network environment has also led to a more serious network security problem. The traditional security solution becomes inefficient in the new situation. Therefore, it is an important task for the security industry to seek technical progress and improve the protection detection and protection ability of the security industry. Botnets have been one of the most important issues in many network security problems, especially in the last one or two years, and China has become one of the most endangered countries by botnets, thus the huge impact of botnets in the world has caused its detection problems to reset people's attention. This paper, based on the topic of botnet detection, focuses on the latest research achievements of botnet detection based on machine learning technology. Firstly, it expounds the application process of machine learning technology in the research of network space security, introduces the structure characteristics of botnet, and then introduces the machine learning in botnet detection. The security features of these solutions and the commonly used machine learning algorithms are emphatically analyzed and summarized. Finally, it summarizes the existing problems in the existing solutions, and the future development direction and challenges of machine learning technology in the research of network space security.

2019-03-28
Ambassa, P. L., Kayem, A. V. D. M., Wolthusen, S. D., Meinel, C..  2018.  Privacy Risks in Resource Constrained Smart Micro-Grids. 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA). :527-532.

In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can offer a cost-effective power management and supply alternative to national power grid connections. RCSMG architectures handle communications over distributed lossy networks to minimize operation costs. However, the unreliable nature of lossy networks makes privacy an important consideration. Existing anonymisation works on data perturbation work mainly by distortion with additive noise. Apply these solutions to RCSMGs is problematic, because deliberate noise additions must be distinguishable both from system and adversarial generated noise. In this paper, we present a brief survey of privacy risks in RCSMGs centered on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.

2019-03-18
Albarakati, A., Moussa, B., Debbabi, M., Youssef, A., Agba, B. L., Kassouf, M..  2018.  OpenStack-Based Evaluation Framework for Smart Grid Cyber Security. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1–6.

The rapid evolution of the power grid into a smart one calls for innovative and compelling means to experiment with the upcoming expansions, and analyze their behavioral response under normal circumstances and when targeted by attacks. Such analysis is fundamental to setting up solid foundations for the smart grid. Smart grid Hardware-In-the-Loop (HIL) co-simulation environments serve as a key approach to answer questions on the systems components, functionality, security concerns along with analysis of the system outcome and expected behavior. In this paper, we introduce a HIL co-simulation framework capable of simulating the smart grid actions and responses to attacks targeting its power and communication components. Our testbed is equipped with a real-time power grid simulator, and an associated OpenStack-based communication network. Through the utilized communication network, we can emulate a multitude of attacks targeting the power system, and evaluating the grid response to those attacks. Moreover, we present different illustrative cyber attacks use cases, and analyze the smart grid behavior in the presence of those attacks.

2019-02-22
Yu, R., Xue, G., Kilari, V. T., Zhang, X..  2018.  Deploying Robust Security in Internet of Things. 2018 IEEE Conference on Communications and Network Security (CNS). :1-9.

Popularization of the Internet-of-Things (IoT) has brought widespread concerns on IoT security, especially in face of several recent security incidents related to IoT devices. Due to the resource-constrained nature of many IoT devices, security offloading has been proposed to provide good-enough security for IoT with minimum overhead on the devices. In this paper, we investigate the inevitable risk associated with security offloading: the unprotected and unmonitored transmission from IoT devices to the offloaded security mechanisms. An important challenge in modeling the security risk is the dynamic nature of IoT due to demand fluctuations and infrastructure instability. We propose a stochastic model to capture both the expected and worst-case security risks of an IoT system. We then propose a framework to efficiently address the optimal robust deployment of security mechanisms in IoT. We use results from extensive simulations to demonstrate the superb performance and efficiency of our approach compared to several other algorithms.

2019-02-08
Zou, Z., Wang, D., Yang, H., Hou, Y., Yang, Y., Xu, W..  2018.  Research on Risk Assessment Technology of Industrial Control System Based on Attack Graph. 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :2420-2423.

In order to evaluate the network security risks and implement effective defenses in industrial control system, a risk assessment method for industrial control systems based on attack graphs is proposed. Use the concept of network security elements to translate network attacks into network state migration problems and build an industrial control network attack graph model. In view of the current subjective evaluation of expert experience, the atomic attack probability assignment method and the CVSS evaluation system were introduced to evaluate the security status of the industrial control system. Finally, taking the centralized control system of the thermal power plant as the experimental background, the case analysis is performed. The experimental results show that the method can comprehensively analyze the potential safety hazards in the industrial control system and provide basis for the safety management personnel to take effective defense measures.

Yi, F., Cai, H. Y., Xin, F. Z..  2018.  A Logic-Based Attack Graph for Analyzing Network Security Risk Against Potential Attack. 2018 IEEE International Conference on Networking, Architecture and Storage (NAS). :1-4.
In this paper, we present LAPA, a framework for automatically analyzing network security risk and generating attack graph for potential attack. The key novelty in our work is that we represent the properties of networks and zero day vulnerabilities, and use logical reasoning algorithm to generate potential attack path to determine if the attacker can exploit these vulnerabilities. In order to demonstrate the efficacy, we have implemented the LAPA framework and compared with three previous network vulnerability analysis methods. Our analysis results have a low rate of false negatives and less cost of processing time due to the worst case assumption and logical property specification and reasoning. We have also conducted a detailed study of the efficiency for generation attack graph with different value of attack path number, attack path depth and network size, which affect the processing time mostly. We estimate that LAPA can produce high quality results for a large portion of networks.
Aufa, F. J., Endroyono, Affandi, A..  2018.  Security System Analysis in Combination Method: RSA Encryption and Digital Signature Algorithm. 2018 4th International Conference on Science and Technology (ICST). :1-5.

Public key cryptography or asymmetric keys are widely used in the implementation of data security on information and communication systems. The RSA algorithm (Rivest, Shamir, and Adleman) is one of the most popular and widely used public key cryptography because of its less complexity. RSA has two main functions namely the process of encryption and decryption process. Digital Signature Algorithm (DSA) is a digital signature algorithm that serves as the standard of Digital Signature Standard (DSS). DSA is also included in the public key cryptography system. DSA has two main functions of creating digital signatures and checking the validity of digital signatures. In this paper, the authors compare the computational times of RSA and DSA with some bits and choose which bits are better used. Then combine both RSA and DSA algorithms to improve data security. From the simulation results, the authors chose RSA 1024 for the encryption process and added digital signatures using DSA 512, so the messages sent are not only encrypted but also have digital signatures for the data authentication process.

2018-12-10
Farooq, M. J., Zhu, Q..  2018.  On the Secure and Reconfigurable Multi-Layer Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT). IEEE Transactions on Wireless Communications. 17:2618–2632.

The Internet of things (IoT) is revolutionizing the management and control of automated systems leading to a paradigm shift in areas, such as smart homes, smart cities, health care, and transportation. The IoT technology is also envisioned to play an important role in improving the effectiveness of military operations in battlefields. The interconnection of combat equipment and other battlefield resources for coordinated automated decisions is referred to as the Internet of battlefield things (IoBT). IoBT networks are significantly different from traditional IoT networks due to battlefield specific challenges, such as the absence of communication infrastructure, heterogeneity of devices, and susceptibility to cyber-physical attacks. The combat efficiency and coordinated decision-making in war scenarios depends highly on real-time data collection, which in turn relies on the connectivity of the network and information dissemination in the presence of adversaries. This paper aims to build the theoretical foundations of designing secure and reconfigurable IoBT networks. Leveraging the theories of stochastic geometry and mathematical epidemiology, we develop an integrated framework to quantify the information dissemination among heterogeneous network devices. Consequently, a tractable optimization problem is formulated that can assist commanders in cost effectively planning the network and reconfiguring it according to the changing mission requirements.

2018-06-11
Chen, C. W., Chang, S. Y., Hu, Y. C., Chen, Y. W..  2017.  Protecting vehicular networks privacy in the presence of a single adversarial authority. 2017 IEEE Conference on Communications and Network Security (CNS). :1–9.

In vehicular networks, each message is signed by the generating node to ensure accountability for the contents of that message. For privacy reasons, each vehicle uses a collection of certificates, which for accountability reasons are linked at a central authority. One such design is the Security Credential Management System (SCMS) [1], which is the leading credential management system in the US. The SCMS is composed of multiple components, each of which has a different task for key management, which are logically separated. The SCMS is designed to ensure privacy against a single insider compromise, or against outside adversaries. In this paper, we demonstrate that the current SCMS design fails to achieve its design goal, showing that a compromised authority can gain substantial information about certificate linkages. We propose a solution that accommodates threshold-based detection, but uses relabeling and noise to limit the information that can be learned from a single insider adversary. We also analyze our solution using techniques from differential privacy and validate it using traffic-simulator based experiments. Our results show that our proposed solution prevents privacy information leakage against the compromised authority in collusion with outsider attackers.

2018-05-30
Tavasoli, M., Alishahi, S., Zabihi, M., Khorashadizadeh, H., Mohajerzadeh, A. H..  2017.  An Efficient NSKDP Authentication Method to Secure Smart Grid. 2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE). :276–280.

Since the Information Networks are added to the current electricity networks, the security and privacy of individuals is challenged. This combination of technologies creates vulnerabilities in the context of smart grid power which disrupt the consumer energy supply. Methods based on encryption are against the countermeasures attacks that have targeted the integrity and confidentiality factors. Although the cryptography strategies are used in Smart Grid, key management which is different in size from tens to millions of keys (for meters), is considered as the critical processes. The Key mismanagement causes to reveal the secret keys for attacker, a symmetric key distribution method is recently suggested by [7] which is based on a symmetric key distribution, this strategy is very suitable for smart electric meters. The problem with this method is its vulnerability to impersonating respondents attack. The proposed approach to solve this problem is to send the both side identifiers in encrypted form based on hash functions and a random value, the proposed solution is appropriate for devices such as meters that have very little computing power.

Li, F., Chen, J., Shu, F., Zhang, J., Qing, S., Guo, W..  2017.  Research of Security Risk in Electric Power Information Network. 2017 6th International Conference on Computer Science and Network Technology (ICCSNT). :361–365.

The factors that threaten electric power information network are analyzed. Aiming at the weakness of being unable to provide numerical value of risk, this paper presents the evaluation index system, the evaluation model and method of network security based on multilevel fuzzy comprehensive judgment. The steps and method of security evaluation by the synthesis evaluation model are provided. The results show that this method is effective to evaluate the risk of electric power information network.

2018-05-24
Ding, P., Wang, Y., Yan, G., Li, W..  2017.  DoS Attacks in Electrical Cyber-Physical Systems: A Case Study Using TrueTime Simulation Tool. 2017 Chinese Automation Congress (CAC). :6392–6396.

Recent years, the issue of cyber security has become ever more prevalent in the analysis and design of electrical cyber-physical systems (ECPSs). In this paper, we present the TrueTime Network Library for modeling the framework of ECPSs and focuses on the vulnerability analysis of ECPSs under DoS attacks. Model predictive control algorithm is used to control the ECPS under disturbance or attacks. The performance of decentralized and distributed control strategies are compared on the simulation platform. It has been proved that DoS attacks happen at dada collecting sensors or control instructions actuators will influence the system differently.

Huang, P., Wang, Y., Yan, G..  2017.  Vulnerability Analysis of Electrical Cyber Physical Systems Using a Simulation Platform. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. :489–494.

This paper considers a framework of electrical cyber-physical systems (ECPSs) in which each bus and branch in a power grid is equipped with a controller and a sensor. By means of measuring the damages of cyber attacks in terms of cutting off transmission lines, three solution approaches are proposed to assess and deal with the damages caused by faults or cyber attacks. Splitting incident is treated as a special situation in cascading failure propagation. A new simulation platform is built for simulating the protection procedure of ECPSs under faults. The vulnerability of ECPSs under faults is analyzed by experimental results based on IEEE 39-bus system.

Chen, L., Yue, D., Dou, C., Ge, H., Lu, J., Yang, X..  2017.  Cascading Failure Initially from Power Grid in Interdependent Networks. 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). :1–5.

The previous consideration of power grid focuses on the power system itself, however, the recent work is aiming at both power grid and communication network, this coupling networks are firstly called as interdependent networks. Prior study on modeling interdependent networks always extracts main features from real networks, the model of network A and network B are completely symmetrical, both degree distribution in intranetwork and support pattern in inter-network, but in reality this circumstance is hard to attain. In this paper, we deliberately set both networks with same topology in order to specialized research the support pattern between networks. In terms of initial failure from power grid or communication network, we find the remaining survival fraction is greatly disparate, and the failure initially from power grid is more harmful than failure initially from communication network, which all show the vulnerability of interdependency and meantime guide us to pay more attention to the protection measures for power grid.

Kim, H., Yoo, D., Kang, J. S., Yeom, Y..  2017.  Dynamic Ransomware Protection Using Deterministic Random Bit Generator. 2017 IEEE Conference on Application, Information and Network Security (AINS). :64–68.

Ransomware has become a very significant cyber threat. The basic idea of ransomware was presented in the form of a cryptovirus in 1995. However, it was considered as merely a conceptual topic since then for over a decade. In 2017, ransomware has become a reality, with several famous cases of ransomware having compromised important computer systems worldwide. For example, the damage caused by CryptoLocker and WannaCry is huge, as well as global. They encrypt victims' files and require user's payment to decrypt them. Because they utilize public key cryptography, the key for recovery cannot be found in the footprint of the ransomware on the victim's system. Therefore, once infected, the system cannot be recovered without paying for restoration. Various methods to deal this threat have been developed by antivirus researchers and experts in network security. However, it is believed that cryptographic defense is infeasible because recovering a victim's files is computationally as difficult as breaking a public key cryptosystem. Quite recently, various approaches to protect the crypto-API of an OS from malicious codes have been proposed. Most ransomware generate encryption keys using the random number generation service provided by the victim's OS. Thus, if a user can control all random numbers generated by the system, then he/she can recover the random numbers used by the ransomware for the encryption key. In this paper, we propose a dynamic ransomware protection method that replaces the random number generator of the OS with a user-defined generator. As the proposed method causes the virus program to generate keys based on the output from the user-defined generator, it is possible to recover an infected file system by reproducing the keys the attacker used to perform the encryption.