The rapid growth of Information and Communication Technology (ICT) in the 21st century has resulted in the emergence of a novel technological paradigm; known as the Internet of Things, or IoT. The IoT, which is at the heart of today's smart infrastructure, aids in the creation of a ubiquitous network of things by simplifying interconnection between smart digital devices and enabling Machine to Machine (M2M) communication. As of now, there are numerous examples of IoT use cases available, assisting every person in this world towards making their lives easier and more convenient. With the latest advancement of IoT in variety of cyber-attacks that targets these pervasive IoT environments, which can even lead to jeopardizing the lives of peoples; that are involving with it. In general, this IoT can be considered as every digital object that is connected to the Internet for intercommunication. Hence in this regard in order to analyse cyber threats that come through the Internet, here we are doing an experimental evaluation to analyse the requests, received to exploit the opened Secure Shell (SSH) connection service of an IoT device, which in our case a Raspberry Pi devices, which connected to the Internet for more than six consecutive days. By opening the SSH service on Raspberry Pi, it acts as a Honeypot device where we can log and retrieve all login attempt requests received to the SSH service opened. Inspired by evaluating the IoT security attacks that target objects in the pervasive IoT environment, after retrieving all the login requests that made through the open SSH connection we then provide a comprehensive analysis along with our observations about the origin of the requests and the focus areas of intruders; in this study.
The paper at hand presents the design of a survey aiming at the cyber-security culture assessment of critical infrastructures during the COVID-19 crisis, when living reality was heavily disturbed and working conditions fundamentally affected. The survey is rooted in a security culture framework layered into two levels, organizational and individual, further analyzed into 10 different security dimensions consisted of 52 domains. An in-depth questionnaire building analysis is presented focusing on the aims, goals, and expected results. It concludes with the survey implementation approach while u…
Recently, botnets such as Mirai and Persirai targeted IoT devices on a large scale. We consider attacks by botnets on cyber-physical systems (CPS), which require advanced capabilities such as controlling the physical processes in real-time. Traditional botnets are not suitable for this goal mainly because they lack process control capabilities, are not optimized for low latency communication, and bots generally do not leverage local resources. We argue that such attacks would require cyber-physical botnets. A cyber-physical botnet needs coordinated and heterogeneous bots, capable of performing…
Swinburne University of Technology（斯威本科技大学）；Deakin University（迪肯大学）
Stealing attack against controlled information, along with the increasing number of information leakage incidents, has become an emerging cyber security threat in recent years. Due to the booming development and deployment of advanced analytics solutions, novel stealing attacks utilize machine learning (ML) algorithms to achieve high success rate and cause a lot of damage. Detecting and defending against such attacks is challenging and urgent so that governments, organizations, and individuals should attach great importance to the ML-based stealing attacks. This survey presents the recent adva…
This paper outlines the design and development of a survey targeting the cyber-security culture assessment of critical infrastructures during the COVID-19 crisis, when living routine was seriously disturbed and working reality fundamentally affected. Its foundations lie on a security culture framework consisted of 10 different security dimensions analysed into 52 domains examined under two different pillars: organizational and individual. In this paper, a detailed questionnaire building analysis is being presented while revealing the aims, goals and expected outcomes of each question. It concl…
Facing the dynamic complex cyber environments, internal and external cyber threat intelligence, and the increasing risk of cyber-attack, knowledge graphs show great application potential in the cyber security area because of their capabilities in knowledge aggregation, representation, management, and reasoning. However, while most research has focused on how to develop a complete knowledge graph, it remains unclear how to apply the knowledge graph to solve industrial real challenges in cyber-attack and defense scenarios. In this review, we provide a brief overview of the basic concepts, schema…
An increased energy demand, and environmental pressure to accommodate higher levels of renewable energy and flexible loads like electric vehicles have led to numerous smart transformations in the modern power systems. These transformations make the cyber-physical power system highly susceptible to cyber-adversaries targeting its numerous operations. In this work, a novel black box adversarial attack strategy is proposed targeting the AC state estimation operation of an unknown power system using historical data. Specifically, false data is injected into the measurements obtained from a small s…
With the emergence of low-cost smart and connected IoT devices, the area of cyber-physical security is becoming increasingly important. Past research has demonstrated new threat vectors targeting the transition process between the cyber and physical domains, where the attacker exploits the sensing system as an attack surface for signal injection or extraction of private information. Recently, there have been attempts to characterize an abstracted model for signal injection, but they primarily focus on the path of signal processing. This paper aims to systematize the existing research on securi…
The popularity of Android system, not only in the handset devices but also in IoT devices, makes it a very attractive destination for malware. Indeed, malware is expanding at a similar rate targeting such devices that rely, in most cases, on Internet to work properly. The state-of-the-art malware mitigation solutions mainly focus on the detection of the actual malicious Android apps using dy- namic and static analyses features to distinguish malicious apps from benign ones. However, there is a small coverage for the In- ternet/network dimension of the Android malicious apps. In this paper, we …
As the internet penetration rate in Africa increases, so does the proliferation of the Internet of Things (IoT) devices. Along with this growth in internet access is the risk of cyberattacks to vulnerable IoT devices mushrooming in the African cyberspace. One way to determine IoT vulnerabilities is to find open ports within Africa s cyberspace. Our research leverages Shodan search engine, a powerful tool for discovering IoT devices facing the public internet, to find open ports across Africa. We conduct an analysis of our findings, ranking countries from most to least vulnerable to cyberattack…
Early detection of cyber-attacks is crucial for a safe and reliable operation of the smart grid. In the literature, outlier detection schemes making sample-by-sample decisions and online detection schemes requiring perfect attack models have been proposed. In this paper, we formulate the online attack/anomaly detection problem as a partially observable Markov decision process (POMDP) problem and propose a universal robust online detection algorithm using the framework of model-free reinforcement learning (RL) for POMDPs. Numerical studies illustrate the effectiveness of the proposed RL-based a…
Cyber-Physical Systems (CPS) are being widely adopted in critical infrastructures, such as smart grids, nuclear plants, water systems, transportation systems, manufacturing and healthcare services, among others. However, the increasing prevalence of cyberattacks targeting them raises a growing security concern in the domain. In particular, memory-safety attacks, that exploit memory-safety vulnerabilities, constitute a major attack vector against real-time control devices in CPS. Traditional IT countermeasures against such attacks have limitations when applied to the CPS context: they typically…
Using Infrastructure-to-Vehicle (I2V) information can be of great benefit when driving autonomously in high-density traffic situations with limited visibility, since the sensing capabilities of the vehicle are enhanced by external sensors. In this research, a method is introduced to increase the vehicle's self-awareness in intersections for one of the largest foreseen challenges when using I2V communication: cyber security. The introduced anomaly detection algorithm, running on the automated vehicle, assesses the health of the I2V communication against multiple cyber security attacks. The anal…
University of Modena and Reggio Emilia（摩德纳和雷焦艾米利亚大学）
Machine learning algorithms are effective in several applications, but they are not as much successful when applied to intrusion detection in cyber security. Due to the high sensitivity to their training data, cyber detectors based on machine learning are vulnerable to targeted adversarial attacks that involve the perturbation of initial samples. Existing defenses assume unrealistic scenarios; their results are underwhelming in non-adversarial settings; or they can be applied only to machine learning algorithms that perform poorly for cyber security. We present an original methodology for coun…
Industrial facilities and critical infrastructures are transforming into "smart" environments that dynamically adapt to external events. The result is an ecosystem of heterogeneous physical and cyber components integrated in cyber-physical systems which are more and more exposed to cyber-physical attacks, i.e., security breaches in cyberspace that adversely affect the physical processes at the core of the systems. We provide a formal compositional metric to estimate the impact of cyber-physical attacks targeting sensor devices of IoT systems formalised in a simple extension of Hennessy and Reg…
The extensive use of Information and Communication Technology in critical infrastructures such as Industrial Control Systems make them vulnerable to cyber-attacks. One particular class of cyber-attacks is advanced persistent threats where highly skilled attackers can steal user authentication information's and move in the network from host to host until a valuable target is reached. The detection of the attacker should occur as soon as possible in order to take appropriate response, otherwise the attacker will have enough time to reach sensitive assets. When facing intelligent threats, intelli…
Attacks targeting network infrastructure devices pose a threat to the security of the internet. An attack targeting such devices can affect an entire autonomous system. In recent years, malware such as VPNFilter, Navidade, and SonarDNS has been used to compromise low-cost routers and commit all sorts of cybercrimes from DDoS attacks to ransomware deployments. Routers of the type concerned are used both to provide last-mile access for home users and to manage interdomain routing (BGP). MikroTik is a particular brand of low-cost router. In our previous research, we found more than 4 million Mikr…
Cyber-physical systems (CPS) are interconnected architectures that employ analog, digital, and communication resources for their interaction with the physical environment. CPS are the backbone of enterprise, industrial, and critical infrastructure. Thus, their vital importance makes them prominent targets for malicious attacks aiming to disrupt their operations. Attacks targeting cyber-physical energy systems (CPES), given their mission-critical nature, can have disastrous consequences. The security of CPES can be enhanced leveraging testbed capabilities to replicate power system operations, d…
Ben-Gurion University of the Negev（内盖夫本-古里安大学）；University of Cagliari（卡利亚里大学）
Recently, neural network (NN)-based methods, including autoencoders, have been proposed for the detection of cyber attacks targeting industrial control systems (ICSs). Such detectors are often retrained, using data collected during system operation, to cope with the natural evolution (i.e., concept drift) of the monitored signals. However, by exploiting this mechanism, an attacker can fake the signals provided by corrupted sensors at training time and poison the learning process of the detector such that cyber attacks go undetected at test time. With this research, we are the first to demonstr…
As a consequence of the growing popularity of smart mobile devices, mobile malware is clearly on the rise, with attackers targeting valuable user information and exploiting vulnerabilities of the mobile ecosystems. With the emergence of large-scale mobile botnets, smartphones can also be used to launch attacks on mobile networks. The NEMESYS project will develop novel security technologies for seamless service provisioning in the smart mobile ecosystem, and improve mobile network security through better understanding of the threat landscape. NEMESYS will gather and analyze information about th…
The growing popularity of smart mobile devices such as smartphones and tablets has made them an attractive target for cyber-criminals, resulting in a rapidly growing and evolving mobile threat as attackers experiment with new business models by targeting mobile users. With the emergence of the first large-scale mobile botnets, the core network has also become vulnerable to distributed denial-of-service attacks such as the signaling attack. Furthermore, complementary access methods such as Wi-Fi and femtocells introduce additional vulnerabilities for the mobile users as well as the core network…
Purpose: Used extensively in the diagnosis, treatment, and prevention of disease, Medical Imaging Devices (MIDs), such as Magnetic Resonance Imaging (MRI) or Computed Tomography (CT) machines, play an important role in medicine today. MIDs are increasingly connected to hospital networks, making them vulnerable to sophisticated cyber-attacks targeting the devices' infrastructure and components, which can disrupt digital patient records, and potentially jeopardize patients' health. Attacks on MIDs are likely to increase, as attackers' skills improve and the number of unpatched devices with known…
While recognized as a theoretical and practical concept for over 20 years, only now ransomware has taken centerstage as one of the most prevalent cybercrimes. Various reports demonstrate the enormous burden placed on companies, which have to grapple with the ongoing attack waves. At the same time, our strategic understanding of the threat and the adversarial interaction between organizations and cybercriminals perpetrating ransomware attacks is lacking. In this paper, we develop, to the best of our knowledge, the first game-theoretic model of the ransomware ecosystem. Our model captures a mult…
The integration of sensors and communication technology in power systems, known as the smart grid, is an emerging topic in science and technology. One of the critical issues in the smart grid is its increased vulnerability to cyber threats. As such, various types of threats and defense mechanisms are proposed in literature. This paper offers a bibliometric survey of research papers focused on the security aspects of Internet of Things (IoT) aided smart grids. To the best of the authors' knowledge, this is the very first bibliometric survey paper in this specific field. A bibliometric analysis …
Command, Control, Communication, and Intelligence (C3I) systems are increasingly used in critical civil and military domains for achieving information superiority, operational efficacy, and greater situational awareness. Unlike traditional systems facing widespread cyber-attacks, the sensitive nature of C3I tactical operations make their cybersecurity a critical concern. For instance, tampering or intercepting confidential information in military battlefields not only damages C3I operations, but also causes irreversible consequences such as loss of human lives and mission failures. Therefore, …
XAI-CF -- Examining the Role of Explainable Artificial Intelligence in Cyber Forensics
Department of Information Security, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia（信息安全系，计算机科学与工程学院，哈伊尔大学，沙特阿拉伯）
Sound at frequencies above (ultrasonic) or below (infrasonic) the range of human hearing can, in some settings, cause adverse physiological and psychological effects to individuals. In this paper, we investigate the feasibility of cyber-attacks that could make smart consumer devices produce possibly imperceptible sound at both high (17-21kHz) and low (60-100Hz) frequencies, at the maximum available volume setting, potentially turning them into acoustic cyber-weapons. To do so, we deploy attacks targeting different smart devices and take sound measurements in an anechoic chamber. For comparison…
Given the increased growing of Internet of Things networks and their presence in critical aspects of human activities, the security of devices connected to these networks becomes critical. Machine Learning approaches are becoming prominent as enablers for security solutions in computer networks due to its capacity to process traffic information in order to detect abnormal patterns which might represent attacks targeting infrastructures. In this paper, we propose to leverage Convolutional and Recurrent Neural Networks, two artifacts that have been successfully used in contexts such as image pro…
STorage as a Service (STaaS) cloud platforms benefits such as getting access to data anywhere, anytime, on a wide range of devices made them very popular among businesses and individuals. As such forensics investigators are increasingly facing cases that involve investigation of STaaS platforms. Therefore, it is essential for cyber investigators to know how to collect, preserve, and analyse evidences of these platforms. In this paper, we describe investigation of three STaaS platforms namely SpiderOak, JustCloud, and pCloud on Windows 8.1 and iOS 8.1.1 devices. Moreover, possible changes on up…
Security issue of distributed state estimation (DSE) is an important prospect for the rapidly growing smart grid ecosystem. Any coordinated cyberattack targeting the distributed system of state estimators can cause unrestrained estimation errors and can lead to a myriad of security risks, including failure of power system operation. This article explores the security threats of a smart grid arising from the exploitation of DSE vulnerabilities. To this aim, novel adversarial strategies based on two-stage data availability and integrity attacks are proposed towards a distributed industrial Inter…
University of Murcia（穆尔西亚大学）；University of Zurich UZH（苏黎世大学（UZH））；armasuisse Science & Technology（瑞士国防科技与采购局科技处）
Device fingerprinting combined with Machine and Deep Learning (ML/DL) report promising performance when detecting cyberattacks targeting data managed by resource-constrained spectrum sensors. However, the amount of data needed to train models and the privacy concerns of such scenarios limit the applicability of centralized ML/DL-based approaches. Federated learning (FL) addresses these limitations by creating federated and privacy-preserving models. However, FL is vulnerable to malicious participants, and the impact of adversarial attacks on federated models detecting spectrum sensing data fal…
Influence of Autoencoder Latent Space on Classifying IoT CoAP Attacks
University of León（莱昂大学）；Research Institute of Applied Sciences in Cybersecurity (RIASC) MIC. University of León（网络安全应用科学研究所以MIC·莱昂大学）；University of A Coruña（拉科鲁尼亚大学）
With the recent prevalence of darkweb/deepweb (D2web) sites specializing in the trade of exploit kits and malware, malicious actors have easy-access to a wide-range of tools that can empower their offensive capability. In this study, we apply concepts from causal reasoning, itemset mining, and logic programming on historical cryptocurrency-related cyber incidents with intelligence collected from over 400 D2web hacker forums. Our goal was to find indicators of cyber threats targeting cryptocurrency traders and exchange platforms from hacker activity. Our approach found interesting activities th…
