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Conference Paper
Kumari, K. A., Sadasivam, G. S., Gowri, S. S., Akash, S. A., Radhika, E. G..  2018.  An Approach for End-to-End (E2E) Security of 5G Applications. 2018 IEEE 4th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing, (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS). :133–138.
As 5G transitions from an industrial vision to a tangible, next-generation mobile technology, security remains key business driver. Heterogeneous environment, new networking paradigms and novel use cases makes 5G vulnerable to new security threats. This in turn necessitates a flexible and dependable security mechanism. End-to-End (E2E) data protection provides better security, avoids repeated security operations like encryption/decryption and provides differentiated security based on the services. E2E security deals with authentication, integrity, key management and confidentiality. The attack surface of a 5G system is larger as 5G aims for a heterogeneous networked society. Hence attack resistance needs to be a design consideration when defining new 5G protocols. This framework has been designed for accessing the manifold applications with high security and trust by offering E2E security for various services. The proposed framework is evaluated based on computation complexity, communication complexity, attack resistance rate and security defensive rate. The protocol is also evaluated for correctness, and resistance against passive, active and dictionary attacks using random oracle model and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool.
Kumar Mangi, S.V.V. Satya Surya Sravan, Hussian S.K., Saddam, Leelavathy, N..  2019.  An Approach for Sending a Confidential Message to the Restricted Users in Defence Based Organization. 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). :1–5.
After the creation of the internet, the file sharing process has been changed. Several third-party applications have come to live for sharing and chatting purposes. A spammer can profit by these applications in different ways like, can achieve countless data, can acquire the user's personal information, and furthermore. Later that untrusted cloud storages are used for uploading a file even it is maintained by the third party If they use an untrusted cloud, there is a security problem. We need to give more security for file transfer in the defense-based organization. So, we developed a secure application for group member communication in a secure medium. The user belongs to a specific department from a specific group can access the data from the storage node and decrypt it. Every user in the group needs to register in the node to send or receive the data. Group Manager can restrict the access of the users in a Defense Network and he generates a user list, users in that list can only login to the node and share or download the files. We created a secure platform to upload files and share the data with multiple users by using Dynamic broadcasting Encryption. Users in the list can only download and decrypt the files from the storage node.
V. Waghmare, K. Gojre, A. Watpade.  2015.  "Approach to Enhancing Concurrent and Self-Reliant Access to Cloud Database: A Review". 2015 International Conference on Computational Intelligence and Communication Networks (CICN). :777-781.

Now a day's cloud computing is power station to run multiple businesses. It is cumulating more and more users every day. Database-as-a-service is service model provided by cloud computing to store, manage and process data on a cloud platform. Database-as-a-service has key characteristics such as availability, scalability, elasticity. A customer does not have to worry about database installation and management. As a replacement, the cloud database service provider takes responsibility for installing and maintaining the database. The real problem occurs when it comes to storing confidential or private information in the cloud database, we cannot rely on the cloud data vendor. A curious cloud database vendor may capture and leak the secret information. For that purpose, Protected Database-as-a-service is a novel solution to this problem that provides provable and pragmatic privacy in the face of a compromised cloud database service provider. Protected Database-as-a-service defines various encryption schemes to choose encryption algorithm and encryption key to encrypt and decrypt data. It also provides "Master key" to users, so that a metadata storage table can be decrypted only by using the master key of the users. As a result, a cloud service vendor never gets access to decrypted data, and even if all servers are jeopardized, in such inauspicious circumstances a cloud service vendor will not be able to decrypt the data. Proposed Protected Database-as-a-service system allows multiple geographically distributed clients to execute concurrent and independent operation on encrypted data and also conserve data confidentiality and consistency at cloud level, to eradicate any intermediate server between the client and the cloud database.

Khan, Samar, Khodke, Priti A., Bhagat, Amol P..  2018.  An Approach to Fault Tolerant Key Generation and Secure Spread Spectrum Communiction. 2018 International Conference on Research in Intelligent and Computing in Engineering (RICE). :1—6.
Wireless communications have encountered a considerable improvement and have integrated human life through various applications, mainly by the widespread of mobile ad hoc and sensor networks. A fundamental characteristic of wireless communications are in their broadcast nature, which allows accessibility of information without placing restrictions on a user's location. However, accessibility also makes wireless communications vulnerable to eavesdropping. To enhance the security of network communication, we propose a separate key generation server which is responsible for key generation using complex random algorithm. The key will remain in database in encrypted format. To prevent brute force attack, we propose various group key generation algorithms in which every group will have separate group key to verify group member's identity. The group key will be verified with the session information before decryption, so that our system will prevent attack if any attacker knows the group key. To increase the security of the system, we propose three level encryption securities: Client side encryption using AES, Server side encryption using AES, and Artificial noise generation and addition. By using this our system is free from brute force attack as we are using three level message security and complex Random key generation algorithms.
Hoang Hai Nguyen, University of Illinois at Urbana-Champaign, Kartik Palani, University of Illinois at Urbana-Champaign, David Nicol, University of Illinois at Urbana-Champaign.  2017.  An Approach to Incorporating Uncertainty in Network Security Analysis. Symposium and Bootcamp for the Science of Security (HotSoS 2017).

Attack graphs used in network security analysis are analyzed to determine sequences of exploits that lead to successful acquisition of privileges or data at critical assets. An attack graph edge corresponds to a vulnerability, tacitly assuming a connection exists and tacitly assuming the vulnerability is known to exist. In this paper we explore use of uncertain graphs to extend the paradigm to include lack of certainty in connection and/or existence of a vulnerability. We extend the standard notion of uncertain graph (where the existence of each edge is probabilistically independent) however, as signi cant correlations on edge existence probabilities exist in practice, owing to common underlying causes for dis-connectivity and/or presence of vulnerabilities. Our extension describes each edge probability as a Boolean expression of independent indicator random variables. This paper (i) shows that this formalism is maximally descriptive in the sense that it can describe any joint probability distribution function of edge existence, (ii) shows that when these Boolean expressions are monotone then we can easily perform uncertainty analysis of edge probabilities, and (iii) uses these results to model a partial attack graph of the Stuxnet worm and a small enterprise network and to answer important security-related questions in a probabilistic manner.

Koning, Ralph, Polevoy, Gleb, Meijer, Lydia, de Laat, Cees, Grosso, Paola.  2019.  Approaches for Collaborative Security Defences in Multi Network Environments. 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom). :113–123.
Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack.
Lee, M., Choi, J., Choi, C., Kim, P..  2017.  APT Attack Behavior Pattern Mining Using the FP-Growth Algorithm. 2017 14th IEEE Annual Consumer Communications Networking Conference (CCNC). :1–4.

There are continuous hacking and social issues regarding APT (Advanced Persistent Threat - APT) attacks and a number of antivirus businesses and researchers are making efforts to analyze such APT attacks in order to prevent or cope with APT attacks, some host PC security technologies such as firewalls and intrusion detection systems are used. Therefore, in this study, malignant behavior patterns were extracted by using an API of PE files. Moreover, the FP-Growth Algorithm to extract behavior information generated in the host PC in order to overcome the limitation of the previous signature-based intrusion detection systems. We will utilize this study as fundamental research about a system that extracts malignant behavior patterns within networks and APIs in the future.

Ktob, A., Li, Z..  2017.  The Arabic Knowledge Graph: Opportunities and Challenges. 2017 IEEE 11th International Conference on Semantic Computing (ICSC). :48–52.

Semantic Web has brought forth the idea of computing with knowledge, hence, attributing the ability of thinking to machines. Knowledge Graphs represent a major advancement in the construction of the Web of Data where machines are context-aware when answering users' queries. The English Knowledge Graph was a milestone realized by Google in 2012. Even though it is a useful source of information for English users and applications, it does not offer much for the Arabic users and applications. In this paper, we investigated the different challenges and opportunities prone to the life-cycle of the construction of the Arabic Knowledge Graph (AKG) while following some best practices and techniques. Additionally, this work suggests some potential solutions to these challenges. The proprietary factor of data creates a major problem in the way of harvesting this latter. Moreover, when the Arabic data is openly available, it is generally in an unstructured form which requires further processing. The complexity of the Arabic language itself creates a further problem for any automatic or semi-automatic extraction processes. Therefore, the usage of NLP techniques is a feasible solution. Some preliminary results are presented later in this paper. The AKG has very promising outcomes for the Semantic Web in general and the Arabic community in particular. The goal of the Arabic Knowledge Graph is mainly the integration of the different isolated datasets available on the Web. Later, it can be used in both the academic (by providing a large dataset for many different research fields and enhance discovery) and commercial sectors (by improving search engines, providing metadata, interlinking businesses).

Lebiednik, Brian, Abadal, Sergi, Kwon, Hyoukjun, Krishna, Tushar.  2018.  Architecting a Secure Wireless Network-on-Chip. 2018 Twelfth IEEE/ACM International Symposium on Networks-on-Chip (NOCS). :1—8.

With increasing integration in SoCs, the Network-on-Chip (NoC) connecting cores and accelerators is of paramount importance to provide low-latency and high-throughput communication. Due to limits to scaling of electrical wires in terms of energy and delay, especially for long multi-mm distances on-chip, alternate technologies such as Wireless Network-on-Chip (WNoC) have shown promise. WNoCs can provide low-latency one-hop broadcasts across the entire chip and can augment point-to-point multi-hop signaling over traditional wired NoCs. Thus, there has been a recent surge in research demonstrating the performance and energy benefits of WNoCs. However, little to no work has studied the additional security and fault tolerance challenges that are unique to WNoCs. In this work, we study potential threats related to denial-of-service, spoofing, and eavesdropping attacks in WNoCs, due to malicious hardware trojans or faulty wireless components. We introduce Prometheus, a dropin solution inside the network interface that provides protection from all three attacks, while adhering to the strict area, power and latency constraints of on-chip systems.

Taubmann, Benjamin, Kolosnjaji, Bojan.  2017.  Architecture for Resource-Aware VMI-based Cloud Malware Analysis. Proceedings of the 4th Workshop on Security in Highly Connected IT Systems. :43–48.
Virtual machine introspection (VMI) is a technology with many possible applications, such as malware analysis and intrusion detection. However, this technique is resource intensive, as inspecting program behavior includes recording of a high number of events caused by the analyzed binary and related processes. In this paper we present an architecture that leverages cloud resources for virtual machine-based malware analysis in order to train a classifier for detecting cloud-specific malware. This architecture is designed while having in mind the resource consumption when applying the VMI-based technology in production systems, in particular the overhead of tracing a large set of system calls. In order to minimize the data acquisition overhead, we use a data-driven approach from the area of resource-aware machine learning. This approach enables us to optimize the trade-off between malware detection performance and the overhead of our VMI-based tracing system.
Stergiou, C., Psannis, K. E., Plageras, A. P., Kokkonis, G., Ishibashi, Y..  2017.  Architecture for security monitoring in IoT environments. 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE). :1382–1385.

The focus of this paper is to propose an integration between Internet of Things (IoT) and Video Surveillance, with the aim to satisfy the requirements of the future needs of Video Surveillance, and to accomplish a better use. IoT is a new technology in the sector of telecommunications. It is a network that contains physical objects, items, and devices, which are embedded with sensors and software, thus enabling the objects, and allowing for their data exchange. Video Surveillance systems collect and exchange the data which has been recorded by sensors and cameras and send it through the network. This paper proposes an innovative topology paradigm which could offer a better use of IoT technology in Video Surveillance systems. Furthermore, the contribution of these technologies provided by Internet of Things features in dealing with the basic types of Video Surveillance technology with the aim to improve their use and to have a better transmission of video data through the network. Additionally, there is a comparison between our proposed topology and relevant proposed topologies focusing on the security issue.

Park, Jiyong, Kim, Junetae, Lee, Byungtae.  2016.  Are Uber Really to Blame for Sexual Assault?: Evidence from New York City Proceedings of the 18th Annual International Conference on Electronic Commerce: E-Commerce in Smart Connected World. :12:1–12:7.

With the boom of ride-sharing platforms, there has been a growing debate on ride-sharing regulations. In particular, allegations of rape against ride-sharing drivers put sexual assault at the center of this debate. However, there is no systematic and society-wide evidence regarding ride-sharing and sexual assault. Building on a theory of crime victimization, this study examines the effect of ride-sharing on sexual assault incidents using comprehensive data on Uber transactions and crime incidents in New York City over the period from January to March 2015. Our findings demonstrate that the Uber availability is negatively associated with the likelihood of rape, after controlling for endogeneity. Moreover, the deterrent effect of Uber on sexual assault is entirely driven by the taxi-sparse areas, namely outside Manhattan. This study sheds light on the potential of ride-sharing platforms and sharing economy to improve social welfare beyond economic gains.

Kolamunna, H., Chauhan, J., Hu, Y., Thilakarathna, K., Perino, D., Makaroff, D., Seneviratne, A..  2017.  Are Wearables Ready for HTTPS? On the Potential of Direct Secure Communication on Wearables 2017 IEEE 42nd Conference on Local Computer Networks (LCN). :321–329.

The majority of available wearable computing devices require communication with Internet servers for data analysis and storage, and rely on a paired smartphone to enable secure communication. However, many wearables are equipped with WiFi network interfaces, enabling direct communication with the Internet. Secure communication protocols could then run on these wearables themselves, yet it is not clear if they can be efficiently supported.,,,,In this paper, we show that wearables are ready for direct and secure Internet communication by means of experiments with both controlled local web servers and Internet servers. We observe that the overall energy consumption and communication delay can be reduced with direct Internet connection via WiFi from wearables compared to using smartphones as relays via Bluetooth. We also show that the additional HTTPS cost caused by TLS handshake and encryption is closely related to the number of parallel connections, and has the same relative impact on wearables and smartphones.

Kee, Ruitao, Sie, Jovan, Wong, Rhys, Yap, Chern Nam.  2019.  Arithmetic Circuit Homomorphic Encryption and Multiprocessing Enhancements. 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security). :1–5.
This is a feasibility study on homomorphic encryption using the TFHE library [1] in daily computing using cloud services. A basic set of arithmetic operations namely - addition, subtraction, multiplication and division were created from the logic gates provide. This research peeks into the impact of logic gates on these operations such as latency of the gates and the operation itself. Multiprocessing enhancement were done for multiplication operation using MPI and OpenMP to reduce latency.
Kim, Y., Ahn, S., Thang, N. C., Choi, D., Park, M..  2019.  ARP Poisoning Attack Detection Based on ARP Update State in Software-Defined Networks. 2019 International Conference on Information Networking (ICOIN). :366—371.

Recently, the novel networking technology Software-Defined Networking(SDN) and Service Function Chaining(SFC) are rapidly growing, and security issues are also emerging for SDN and SFC. However, the research about security and safety on a novel networking environment is still unsatisfactory, and the vulnerabilities have been revealed continuously. Among these security issues, this paper addresses the ARP Poisoning attack to exploit SFC vulnerability, and proposes a method to defend the attack. The proposed method recognizes the repetitive ARP reply which is a feature of ARP Poisoning attack, and detects ARP Poisoning attack. The proposed method overcomes the limitations of the existing detection methods. The proposed method also detects the presence of an attack more accurately.

Kanimozhi, V., Jacob, T. Prem.  2019.  Artificial Intelligence based Network Intrusion Detection with Hyper-Parameter Optimization Tuning on the Realistic Cyber Dataset CSE-CIC-IDS2018 using Cloud Computing. 2019 International Conference on Communication and Signal Processing (ICCSP). :0033–0036.

One of the latest emerging technologies is artificial intelligence, which makes the machine mimic human behavior. The most important component used to detect cyber attacks or malicious activities is the Intrusion Detection System (IDS). Artificial intelligence plays a vital role in detecting intrusions and widely considered as the better way in adapting and building IDS. In trendy days, artificial intelligence algorithms are rising as a brand new computing technique which will be applied to actual time issues. In modern days, neural network algorithms are emerging as a new artificial intelligence technique that can be applied to real-time problems. The proposed system is to detect a classification of botnet attack which poses a serious threat to financial sectors and banking services. The proposed system is created by applying artificial intelligence on a realistic cyber defense dataset (CSE-CIC-IDS2018), the very latest Intrusion Detection Dataset created in 2018 by Canadian Institute for Cybersecurity (CIC) on AWS (Amazon Web Services). The proposed system of Artificial Neural Networks provides an outstanding performance of Accuracy score is 99.97% and an average area under ROC (Receiver Operator Characteristic) curve is 0.999 and an average False Positive rate is a mere value of 0.001. The proposed system using artificial intelligence of botnet attack detection is powerful, more accurate and precise. The novel proposed system can be implemented in n machines to conventional network traffic analysis, cyber-physical system traffic data and also to the real-time network traffic analysis.

Redmiles, Elissa M., Zhu, Ziyun, Kross, Sean, Kuchhal, Dhruv, Dumitras, Tudor, Mazurek, Michelle L..  2018.  Asking for a Friend: Evaluating Response Biases in Security User Studies. Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. :1238-1255.

The security field relies on user studies, often including survey questions, to query end users' general security behavior and experiences, or hypothetical responses to new messages or tools. Self-report data has many benefits – ease of collection, control, and depth of understanding – but also many well-known biases stemming from people's difficulty remembering prior events or predicting how they might behave, as well as their tendency to shape their answers to a perceived audience. Prior work in fields like public health has focused on measuring these biases and developing effective mitigations; however, there is limited evidence as to whether and how these biases and mitigations apply specifically in a computer-security context. In this work, we systematically compare real-world measurement data to survey results, focusing on an exemplar, well-studied security behavior: software updating. We align field measurements about specific software updates (n=517,932) with survey results in which participants respond to the update messages that were used when those versions were released (n=2,092). This allows us to examine differences in self-reported and observed update speeds, as well as examining self-reported responses to particular message features that may correlate with these results. The results indicate that for the most part, self-reported data varies consistently and systematically with measured data. However, this systematic relationship breaks down when survey respondents are required to notice and act on minor details of experimental manipulations. Our results suggest that many insights from self-report security data can, when used with care, translate to real-world environments; however, insights about specific variations in message texts or other details may be more difficult to assess with surveys.

Khorev, P. B., Zheltov, M. I..  2020.  Assessing Information Risks When Using Web Applications Using Fuzzy Logic. 2020 V International Conference on Information Technologies in Engineering Education ( Inforino ). :1—4.

The article looks at information risk concepts, how it is assessed, web application vulnerabilities and how to identify them. A prototype web application vulnerability scanner has been developed with a function of information risk assessment based on fuzzy logic. The software developed is used in laboratory sessions on data protection discipline.

Kuznetsov, Petr, Rieutord, Thibault, He, Yuan.  2018.  An Asynchronous Computability Theorem for Fair Adversaries. Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing. :387–396.
This paper proposes a simple topological characterization of a large class of fair adversarial models via affine tasks: sub-complexes of the second iteration of the standard chromatic subdivision. We show that the task computability of a model in the class is precisely captured by iterations of the corresponding affine task. Fair adversaries include, but are not restricted to, the models of wait-freedom, t-resilience, and k-concurrency. Our results generalize and improve all previously derived topological characterizations of the ability of a model to solve distributed tasks.
Gorodnichev, Mikhail G., Kochupalov, Alexander E., Gematudinov, Rinat A..  2018.  Asynchronous Rendering of Texts in iOS Applications. 2018 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT QM IS). :643–645.
This article is devoted to new asynchronous methods for rendering text information in mobile applications for iOS operating system.
Romdhane, R. B., Hammami, H., Hamdi, M., Kim, T..  2019.  At the cross roads of lattice-based and homomorphic encryption to secure data aggregation in smart grid. 2019 15th International Wireless Communications Mobile Computing Conference (IWCMC). :1067—1072.

Various research efforts have focused on the problem of customer privacy protection in the smart grid arising from the large deployment of smart energy meters. In fact, the deployed smart meters distribute accurate profiles of home energy use, which can reflect the consumers' behaviour. This paper proposes a privacy-preserving lattice-based homomorphic aggregation scheme. In this approach, the smart household appliances perform the data aggregation while the smart meter works as relay node. Its role is to authenticate the exchanged messages between the home area network appliances and the related gateway. Security analysis show that our scheme guarantees consumer privacy and messages confidentiality and integrity in addition to its robustness against several attacks. Experimental results demonstrate the efficiency of our proposed approach in terms of communication complexity.

Kwon, Albert, Corrigan-Gibbs, Henry, Devadas, Srinivas, Ford, Bryan.  2017.  Atom: Horizontally Scaling Strong Anonymity. Proceedings of the 26th Symposium on Operating Systems Principles. :406–422.

Atom is an anonymous messaging system that protects against traffic-analysis attacks. Unlike many prior systems, each Atom server touches only a small fraction of the total messages routed through the network. As a result, the system's capacity scales near-linearly with the number of servers. At the same time, each Atom user benefits from "best possible" anonymity: a user is anonymous among all honest users of the system, even against an active adversary who monitors the entire network, a portion of the system's servers, and any number of malicious users. The architectural ideas behind Atom have been known in theory, but putting them into practice requires new techniques for (1) avoiding heavy general-purpose multi-party computation protocols, (2) defeating active attacks by malicious servers at minimal performance cost, and (3) handling server failure and churn. Atom is most suitable for sending a large number of short messages, as in a microblogging application or a high-security communication bootstrapping ("dialing") for private messaging systems. We show that, on a heterogeneous network of 1,024 servers, Atom can transit a million Tweet-length messages in 28 minutes. This is over 23x faster than prior systems with similar privacy guarantees.

Cheng, Q., Kwiat, K., Kamhoua, C. A., Njilla, L..  2017.  Attack Graph Based Network Risk Assessment: Exact Inference vs Region-Based Approximation. 2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE). :84–87.

Quantitative risk assessment is a critical first step in risk management and assured design of networked computer systems. It is challenging to evaluate the marginal probabilities of target states/conditions when using a probabilistic attack graph to represent all possible attack paths and the probabilistic cause-consequence relations among nodes. The brute force approach has the exponential complexity and the belief propagation method gives approximation when the corresponding factor graph has cycles. To improve the approximation accuracy, a region-based method is adopted, which clusters some highly dependent nodes into regions and messages are passed among regions. Experiments are conducted to compare the performance of the different methods.

Plappert, Christian, Zelle, Daniel, Gadacz, Henry, Rieke, Roland, Scheuermann, Dirk, Krauß, Christoph.  2021.  Attack Surface Assessment for Cybersecurity Engineering in the Automotive Domain. 2021 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). :266–275.
Connected smart cars enable new attacks that may have serious consequences. Thus, the development of new cars must follow a cybersecurity engineering process as defined for example in ISO/SAE 21434. A central part of such a process is the threat and risk assessment including an attack feasibility rating. In this paper, we present an attack surface assessment with focus on the attack feasibility rating compliant to ISO/SAE 21434. We introduce a reference architecture with assets constituting the attack surface, the attack feasibility rating for these assets, and the application of this rating on typical use cases. The attack feasibility rating assigns attacks and assets to an evaluation of the attacker dimensions such as the required knowledge and the feasibility of attacks derived from it. Our application of sample use cases shows how this rating can be used to assess the feasibility of an entire attack path. The attack feasibility rating can be used as a building block in a threat and risk assessment according to ISO/SAE 21434.
Radoglou-Grammatikis, Panagiotis, Sarigiannidis, Panagiotis, Giannoulakis, Ioannis, Kafetzakis, Emmanouil, Panaousis, Emmanouil.  2019.  Attacking IEC-60870-5-104 SCADA Systems. 2019 IEEE World Congress on Services (SERVICES). 2642-939X:41–46.
The rapid evolution of the Information and Communications Technology (ICT) services transforms the conventional electrical grid into a new paradigm called Smart Grid (SG). Even though SG brings significant improvements, such as increased reliability and better energy management, it also introduces multiple security challenges. One of the main reasons for this is that SG combines a wide range of heterogeneous technologies, including Internet of Things (IoT) devices as well as Supervisory Control and Data Acquisition (SCADA) systems. The latter are responsible for monitoring and controlling the automatic procedures of energy transmission and distribution. Nevertheless, the presence of these systems introduces multiple vulnerabilities because their protocols do not implement essential security mechanisms such as authentication and access control. In this paper, we focus our attention on the security issues of the IEC 60870-5-104 (IEC-104) protocol, which is widely utilized in the European energy sector. In particular, we provide a SCADA threat model based on a Coloured Petri Net (CPN) and emulate four different types of cyber attacks against IEC-104. Last, we used AlienVault's risk assessment model to evaluate the risk level that each of these cyber attacks introduces to our system to confirm our intuition about their severity.