Biblio

Critical infrastructures of all countries unites common cyberspace. In this space, there are many threats that can disrupt the security of critical infrastructure in one country, but also cause damage in other countries. This is a reality that makes it necessary to agree on intergovernmental national views on the composition of critical infrastructures, an assessment of their security and protection. The article presents an overview of views on critical infrastructures of the United States, the European Union, the United Kingdom, and the Russian Federation, the purpose of which is to develop common positions.

In this paper we report preliminary results from the novel coupling of cyber-physical emulation and interdiction optimization to better understand the impact of a CrashOverride malware attack on a notional electric system. We conduct cyber experiments where CrashOverride issues commands to remote terminal units (RTUs) that are controlling substations within a power control area. We identify worst-case loss of load outcomes with cyber interdiction optimization; the proposed approach is a bilevel formulation that incorporates RTU mappings to controllable loads, transmission lines, and generators in the upper-level (attacker model), and a DC optimal power flow (DCOPF) in the lower-level (defender model). Overall, our preliminary results indicate that the interdiction optimization can guide the design of experiments instead of performing a “full factorial” approach. Likewise, for systems where there are important dependencies between SCADA/ICS controls and power grid operations, the cyber-physical emulations should drive improved parameterization and surrogate models that are applied in scalable optimization techniques.

Mutual assured destruction is a Cold War era principle of deterrence through causing your enemy to fear that you can destroy them to at least the same extent that they can destroy you. It is based on the threat of retaliation and requires systems that can either be triggered after an enemy attack is launched and before the destructive capability is destroyed or systems that can survive an initial attack and be launched in response. During the Cold War, the weapons of mutual assured destructions were nuclear. However, with the incredible reliance on computers for everything from power generation control to banking to agriculture logistics, a cyber attack mutual assured destruction scenario is plausible. This paper presents this concept and considers the deterrent need, to prevent such a crippling attack from ever being launched, from a system of systems perspective.

The three-phase grid-connected converter control strategy, which applies to the battery energy storage system, generally ignores the interference of harmonic components in the grid voltage. As a result, it is difficult to meet the practical application requirements. To deal with this problem, it is necessary to optimize and improve the traditional control strategy, taking harmonics into consideration. And its bases are analysis of the harmonic characteristics and study of its control mechanism in the grid-connected converter. This paper proposes a method of harmonic decomposition, classifies the grid voltage harmonics and explores the control mechanism in the grid-connected converter. With the help of the simulation model built by Matlab/Simulink, the comparative simulation of the energy storage control system carried out under the control of the ideal grid voltage input and the actual one, verifies the correctness of the analytical method proposed in the article.

The threat of cybercrime is becoming increasingly complex and diverse on putting citizen's data or money in danger. Cybercrime threats are often originating from trusted, malicious, or negligent insiders, who have excessive access privileges to sensitive data. The analysis of cybercrime insider investigation presents many opportunities for actionable intelligence on improving the quality and value of digital evidence. There are several advantages of applying Deep Packet Inspection (DPI) methods in cybercrime insider investigation. This paper introduces DPI method that can help investigators in developing new techniques and performing digital investigation process in forensically sound and timely fashion manner. This paper provides a survey of the packet inspection, which can be applied to cybercrime insider investigation.

The reliability of nuclear command, control and communications has long been identified as a critical component of the strategic stability among nuclear states. Advances in offensive cyber weaponry have the potential to negatively impact this reliability, threatening strategic stability. In this paper we present a game theoretic model of preemptive cyber attacks against nuclear command, control and communications. The model is a modification of the classic two-player game of Chicken, a standard game theoretic model for nuclear brinksmanship. We fully characterize equilibria in both the complete information game and two distinct two-sided incomplete information games. We show that when both players have advanced cyber capabilities conflict is more likely in equilibrium, regardless of information structure. On the other hand, when at most one player has advanced cyber capabilities, strategic stability depends on the information structure. Under complete information, asymmetric cyber capabilities have a stabilizing effect in which the player with strong cyber has the resolve to stand firm in equilibrium. Under incomplete information, asymmetric cyber capabilities can have both stabilizing and destabilizing effects depending on prior beliefs over opponent cyber capabilities.

In operation centers, it is important to know the power transfer limit to guarantee the safety operation of the power system. The Voltage Stability Margin (VSM) is a widely used measure and needs to definition of a load growth direction (LGD) to be computed. However, different definitions of LGD can provide different VSMs and then the VSM may not be reliable. Besides, the measure of this power transfer limit usually is related to the Saddle-Node Bifurcation. In dynamic security assessment (DSA) is highly desirable to identify limit regions where the power system can operate safely due to Hopf (HB) and Saddle-Node (SNB) Bifurcations. This paper presents a modeling of the power system incorporating the LGD variation based on participation factors to evaluate the effects on the stability margin estimation due to HB and SNB. A direct method is used to calculate the stability margin of the power system for a given load direction. The analysis was performed in the IEEE 39 bus system.

Network security is a general idea to ensure information transmission over PC and portable systems. Elliptic curve cryptosystems are nowadays widely used in public communication channels for network security. Their security relies upon the complexity of clarifying the elliptic curve discrete alogarithm issue. But, there are several general attacks in them. Elliptic bend number juggling is actualized over complex fields to enhance the security of elliptic curve cryptosystems. This paper starts with the qualities of elliptic curve cryptosystems and their security administrations. At that point we talk about limited field number-crunching and its properties, prime field number-crunching, twofold field math and complex number-crunching, and elliptic bend number-crunching over prime field and parallel field. This paper proposes how to execute the unpredictable number of math under prime field and double field utilizing java BigInteger class. also, we actualize elliptic bend math and elliptic bend cryptosystems utilizing complex numbers over prime field and double field and talk about our trials that got from the usage.

Today, there are several applications which allow us to share images over the internet. All these images must be stored in a secure manner and should be accessible only to the intended recipients. Hence it is of utmost importance to develop efficient and fast algorithms for encryption of images. This paper uses chaotic generators to generate random sequences which can be used as keys for image encryption. These sequences are seemingly random and have statistical properties. This makes them resistant to analysis and correlation attacks. However, these sequences have fixed cycle lengths. This restricts the number of sequences that can be used as keys. This paper utilises neural networks as a source of perturbation in a chaotic generator and uses its output to encrypt an image. The robustness of the encryption algorithm can be verified using NPCR, UACI, correlation coefficient analysis and information entropy analysis.

In recent years, image steganography is being considered as one of the methods to secure the confidentiality of sensitive and private data sent over networks. Conventional image steganography techniques use cover images to hide secret messages. These techniques are susceptible to steganalysis algorithms based on anomaly detection. This paper proposes a new approach to image steganography without using cover images. In addition, it utilizes Deoxyribonucleic Acid (DNA) sequences. DNA sequences are used to generate key and stego-image. Experimental results show that the use of DNA sequences in this technique offer very low cracking probability and the coverless approach contributes to its high embedding capacity.

We consider a one-time digital signature scheme recently proposed by Persichetti and show that a successful key recovery attack can be mounted with limited complexity. The attack we propose exploits a single signature intercepted by the attacker, and relies on a statistical analysis performed over such a signature, followed by information set decoding. We assess the attack complexity and show that a full recovery of the secret key can be performed with a work factor that is far below the claimed security level. The efficiency of the attack is motivated by the sparsity of the signature, which leads to a significant information leakage about the secret key.

The paper deals with the design and principles of functioning of code-based schemes for formation and verification of electronic digital signature. Comparative studies of the effectiveness of the known CFS scheme and the proposed scheme have been carried out, as well as their possibilities, disadvantages and prospects for use in the post-quantum period.

This paper presents the proposed method of building a digital signature algorithm which is based on the difficulty of solving root problem and some expanded root problems on Zp. The expanded root problem is a new form of difficult problem without the solution, also originally proposed and applied to build digital signature algorithms. This proposed method enable to build a high-security digital signature platform for practical applications.

This work takes a novel approach to classifying the behavior of devices by exploiting the single-purpose nature of IoT devices and analyzing the complexity and variance of their network traffic. We develop a formalized measurement of complexity for IoT devices, and use this measurement to precisely tune an anomaly detection algorithm for each device. We postulate that IoT devices with low complexity lead to a high confidence in their behavioral model and have a correspondingly more precise decision boundary on their predicted behavior. Conversely, complex general purpose devices have lower confidence and a more generalized decision boundary. We show that there is a positive correlation to our complexity measure and the number of outliers found by an anomaly detection algorithm. By tuning this decision boundary based on device complexity we are able to build a behavioral framework for each device that reduces false positive outliers. Finally, we propose an architecture that can use this tuned behavioral model to rank each flow on the network and calculate a trust score ranking of all traffic to and from a device which allows the network to autonomously make access control decisions on a per-flow basis.

Memory corruption vulnerabilities have been around for decades and rank among the most prevalent vulnerabilities in embedded systems. Yet this constrained environment poses unique design and implementation challenges that significantly complicate the adoption of common hardening techniques. Combined with the irregular and involved nature of embedded patch management, this results in prolonged vulnerability exposure windows and vulnerabilities that are relatively easy to exploit. Considering the sensitive and critical nature of many embedded systems, this situation merits significant improvement. In this work, we present the first quantitative study of exploit mitigation adoption in 42 embedded operating systems, showing the embedded world to significantly lag behind the general-purpose world. To improve the security of deeply embedded systems, we subsequently present μArmor, an approach to address some of the key gaps identified in our quantitative analysis. μArmor raises the bar for exploitation of embedded memory corruption vulnerabilities, while being adoptable on the short term without incurring prohibitive extra performance or storage costs.

Designing secure systems is a complex task, particularly for designers who are no security experts. Cyber security plays a key role in embedded systems, especially for the domain of the Internet of Things (IoT). IoT systems of this kind are becoming increasingly important in daily life as they simplify various tasks. They are usually small, either embedded into bigger systems or battery driven, and perform monitoring or one shot tasks. Thus, they are subject to manifold constraints in terms of performance, power consumption, chip area, etc. As they are continuously connected to the internet and utilize our private data to perform their tasks, they are interesting for potential attackers. Cyber security thus plays an important role for the design of an IoT system. As the usage of security measures usually increases both computation time, as well as power consumption, a conflict between these constraints must be solved. For the designers of such systems, balancing these constraints constitutes a highly complex task. In this paper we propose a novel approach for considering possible security attacks on embedded systems, simplifying the consideration of security requirements immediately at the start of the design process. We introduce a security aware design space exploration framework which based on an architectural, behavioral and security attack description, finds the optimal design for IoT systems. We also demonstrate the feasibility and the benefits of our framework based on a door access system use case.

In today's society, even though the technology is so developed, the coloring of computer images has remained at the manual stage. As a carrier of human culture and art, film has existed in our history for hundred years. With the development of science and technology, movies have developed from the simple black-and-white film era to the current digital age. There is a very complicated process for coloring old movies. Aside from the traditional hand-painting techniques, the most common method is to use post-processing software for coloring movie frames. This kind of operation requires extraordinary skills, patience and aesthetics, which is a great test for the operator. In recent years, the extensive use of machine learning and neural networks has made it possible for computers to intelligently process images. Since 2016, various types of generative adversarial networks models have been proposed to make deep learning shine in the fields of image style transfer, image coloring, and image style change. In this case, the experiment uses the generative adversarial networks principle to process pictures and videos to realize the automatic rendering of old documentary movies.

Semi-supervised learning has recently gained increasingly attention because it can combine abundant unlabeled data with carefully labeled data to train deep neural networks. However, common semi-supervised methods deeply rely on the quality of pseudo labels. In this paper, we proposed a new semi-supervised learning method based on Generative Adversarial Network (GAN), by using discriminator to learn the feature of both labeled and unlabeled data, instead of generating pseudo labels that cannot all be correct. Our approach, semi-supervised conditional GAN (SCGAN), builds upon the conditional GAN model, extending it to semi-supervised learning by changing the discriminator's output to a classification output and a real or false output. We evaluate our approach with basic semi-supervised model on MNIST dataset. It shows that our approach achieves the classification accuracy with 84.15%, outperforming the basic semi-supervised model with 72.94%, when labeled data are 1/600 of all data.

Cryptographic hash functions play a crucial role in information security. Cryptographic hash functions are used in various cryptographic applications to verify the message authenticity and integrity. In this paper we propose a Cellular Automata Based Hashing Algorithm (CABHA) for generating strong cryptographic hash function. The proposed CABHA algorithm uses the cellular automata rules and a custom transformation function to create a strong hash from an input message and a key.

We consider a setup in which the channel from Alice to Bob is less noisy than the channel from Eve to Bob. We show that there exist encoding and decoding which accomplish error correction and authentication simultaneously; that is, Bob is able to correctly decode a message coming from Alice and reject a message coming from Eve with high probability. The system does not require any secret key shared between Alice and Bob, provides information theoretic security, and can safely be composed with other protocols in an arbitrary context.

This paper investigates the problem of generating two secret keys (SKs) simultaneously over a five-terminal system with terminals labelled as 1, 2, 3, 4 and 5. Each of terminal 2 and terminal 3 wishes to generate an SK with terminal 1 over a public channel wiretapped by a passive eavesdropper. Terminal 4 and terminal 5 respectively act as a trusted helper and an untrusted helper to assist the SK generation. All the terminals observe correlated source sequences from discrete memoryless sources (DMS) and can exchange information over a public channel with no rate constraint that the eavesdropper has access to. Based on the considered model, key capacity region is fully characterized and a source coding scheme that can achieve the capacity region is provided. Furthermore, expression for key leakage rate is obtained to analyze the security performance of the two generated keys.

For the past few decades, mobile ad hoc networks (MANETs) have been a global trend in wireless networking technology. These kind of ad-hoc networks are infrastructure less, dynamic in topology and further doesn't have a centralized network administration which makes it easier for the intruders to launch several attacks on MANETs. In this paper, we have made a comparative analysis of the network layer attack by simulating rushing and black hole attack using NS-2 network simulator. For determining the most vulnerable attack we have considered packet delivery ratio, end to end delay and throughput as a evaluation metrices. Here, AODV routing protocol has been configured for data forwarding operations. From our Simulation result, it is evident that the black hole attack is more vulnerable when compared to the rushing attack.

Advanced metering infrastructure (AMI) is a key component in the smart grid. Transmitting data robustly and reliably between the tremendous smart meters in the AMI is one of the most crucial tasks for providing various services in smart grid. Among the many efforts for designing practical routing protocols for the AMI, the Routing Protocol for Low-Power and Lossy Networks (RPL) proposed by the IETF ROLL working group is considered the most consolidated candidate. Resent research has shown cyber attacks such as blackhole attack and version number attack can seriously damage the performance of the network implementing RPL. The main reason that RPL is vulnerable to these kinds of attacks is the lack an authentication mechanism. In this paper, we study the impact of blackhole attacks on the performance of the AMI network and proposed a new blackhole attack that can bypass the existing defense mechanism. Then, we propose a cuckoo filter based RPL to defend the AMI network from blackhole attacks. We also give the security analysis of the proposed method.

Outsourcing services to cloud server (CS) becomes popular in these years. However, the outsourced services often involve with sensitive activity and CS naturally becomes a target of varieties of attacks. Even worse, CS itself can misuse the outsourced services for illegal profit. Traditional online banking system also can make use of a cloud framework to provide economical and high-speed online services to the consumers, which makes the financial dealing easy and convenient. Most of the banking organizations provide services through passbook, ATM, mobile banking, electronic banking (e-banking) etc. Among these, the e-banking and mobile banking are more convenient and becomes essential. Therefore, it is critical to provide an efficient, reliable and more importantly, secure e-banking services to the consumers. The cloud environment is suitable paradigm to a new, small and medium scale banking organization as it eliminates the requirement for them to start with small resources and increase gradually as the service demand rises. However, security is one of the main concerns since it deals with many sensitive data of the valuable customers. In addition to this, the access of various data needs to be restricted to prevent any unauthorized transaction. Nagaraju et al. presented a framework to achieve reliability and security in public cloud based online banking using multi-factor authentication concept. Unfortunately, the login and authentication protocol of this framework is prone to impersonation attack. In this paper, we have revised the framework to avoid this attack.

We are living in a society where technology is present everywhere we go. We are striving towards smart homes, smart cities, Internet of Things, Internet of Everything. Not so long ago, a password was all you needed for secure authentication. Nowadays, even the most complicated passwords are not considered enough. Multi-factor authentication is gaining more and more terrain. Complex system may also require more than one solution for real, strong security. The present paper proposes a framework based with MFA as a basis for access control and data analytics. Events within a cyber-physical system are processed and analyzed in an attempt to detect, prevent and mitigate possible attacks.