Conventional Attacks Research Articles

Robust watermarking algorithm for medical images based on log-polar transform

In the information age, network security has gradually become a potentially huge problem, especially in the medical field, it is essential to ensure the accuracy and safety of images, and patient information needs to be included with minimal change. Combined log-polar transform (LPT) and discrete cosine transform (DCT), a novel robust watermarking algorithm for medical images, is proposed. It realized the lossless embedding of patient information into medical images. In the process of feature extraction and watermark embedding, the proposed algorithm reflects the characteristics of LPT, scale invariance and rotation invariance, and retains the advantages of DCT's ability to resist conventional attacks and robustness. As it adopts zero-watermarking embedding technology, it solves the defects caused by the traditional watermark embedding technology to modify the original image data and guaranteed the quality of medical images. The good experimental results show the effectiveness of this algorithm.

Attack Detection in Power Distribution Systems Using a Cyber-Physical Real-Time Reference Model

This paper develops a novel intrusion detection system for power distribution systems that utilizes a cyber-physical real-time reference model to accurately replicate the complex behavior of power distribution components for attack detection. The proposed intrusion detection system analyzes the consistency of the physical data from sensor readings and control commands in contrast with their digital counterpart obtained from the real-time reference model. Therefore, a residual-based online attack detection mechanism that utilizes the chi-square test is able to determine the presence of malicious data. The proposed mechanism is implemented on a hardware-in-the-loop simulation testbed on a test power distribution system with distributed energy resources and energy storage systems. The results show that the proposed solution is able to quickly detect multiple types of cyber attacks for different levels of accuracy of the real-time reference model. The simulations illustrate that the proposed approach outperforms conventional attack detection mechanisms such as one-class classifiers and residual-based approaches that utilize Kalman filters or neural networks.

A New Full Chaos Coupled Mapping Lattice and Its Application in Privacy Image Encryption

Since chaotic cryptography has a long-term problem of dynamic degradation, this paper presents proof that chaotic systems resist dynamic degradation through theoretical analysis. Based on this proof, a novel one-dimensional two-parameter with a wide-range system mixed coupled map lattice model (TWMCML) is given. The evaluation of TWMCML shows that the system has the characteristics of strong chaos, high sensitivity, broader parameter ranges and wider chaos range, which helps to enhance the security of chaotic sequences. Based on the excellent performance of TWMCML, it is applied to the newly proposed encryption algorithm. The algorithm realizes double protection of private images under the premise of ensuring efficiency and safety. First, the important information of the image is extracted by edge detection technology. Then the important area is scrambled by the three-dimensional bit-level coupled XOR method. Finally, the global image is more fully confused by the dynamic index diffusion formula. The simulation experiment verified the effectiveness of the algorithm for grayscale and color images. Security tests show that the application of TWMCML makes the encryption algorithm have a better ability to overcome conventional attacks.

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Assessing China-U.S. Inadvertent Nuclear Escalation

Abstract China-U.S. inadvertent escalation has been a focus of recent international relations literature. The current debate, however, has not paid sufficient attention to two important factors: the survivability of China's nuclear forces under unintentional conventional attacks; and China's nuclear command, control, and communication (NC3) system. Based on detailed analysis of these two variables, three potential mechanisms of China-U.S. inadvertent escalation are examined: use-it-or-lose-it, unauthorized/accidental, and damage-limitation. Although the possibility of a major China-U.S. conventional war inadvertently escalating to a nuclear level cannot be excluded, the risk is extremely low. China's nuclear forces would survive U.S. inadvertent conventional attacks and, thus, are unlikely to be significantly undermined. Even though China's NC3 system might be degraded during a conventional war with the United States, Chinese leadership would likely maintain minimum emergency communications with its nuclear forces. Moreover, China's NC3 system is highly centralized, and it prioritizes “negative control,” which can help to prevent escalation. China's nuclear retaliatory capability, although limited, could impede U.S. damage-limitation strikes to some extent. To keep the risk of inadvertent escalation low, both sides must take appropriate precautions and exercise self-restraint in their planning and operations.

Hybrid Successive CFA Image Encryption-Watermarking Algorithm Based on the Quaternionic Wavelet Transform (QWT)

In this paper, we present a new robust hybrid algorithm combining successively chaotic encryption and blind watermarking of images based on the quaternionic wavelet transform (QWT) to ensure the secure transfer of digital data. The calculations of the different evaluation parameters have been performed in order to determine the robustness of our algorithm to certain attacks. The application of this hybrid algorithm on CFA (Color Filter Array) images, allowed us to guarantee the integrity of the digital data and to propose an autonomous transmission system. The results obtained after simulation of this successive hybrid algorithm of chaotic encryption and then blind watermarking are appreciated through the values of the evaluation parameters which are the peak signal-to-noise ratio (PSNR) and the correlation coefficient (CC), and by the visual observation of the extracted watermarks before and after attacks. The values of these parameters show that this successive hybrid algorithm is robust against some conventional attacks.

Cryptanalysis of compressive interference-based optical encryption using a U-net deep learning network

We present a deep learning (DL) framework based on a U-type convolutional neural network (U-net) to analysis the security of optical interference-based encryption system with sparsity constraints. In the optical cryptosystem, two phase-only masks (POMs) can be obtained by using phase retrieval algorithm (PRA) with the constraints of complementary binary amplitude masks (BAMs). By integrating the interference technique and phase encoding, the encryption scheme achieves a high security level and is immune to conventional attack methods. Here, we investigate and construct a neural network architecture for evaluating the security of the cryptosystem based on the idea of U-net. In this method, we achieve the approximate equivalent model of the compressive interference-based optical cryptosystem by using a U-net model, which has been pre-trained by a series of ciphertext–plaintext pairs. It can be found that the cryptosystem can be broken by using the proposed DL network. The plaintexts can be retrieved from their corresponding ciphertexts without the use of security keys, such as the diffraction distances, the BAMs, etc. The results of numerical experiments are presented to show the good performance of our proposed DL-based method.

Robust and Secure Zero-Watermarking Algorithm for Medical Images Based on Harris-SURF-DCT and Chaotic Map

To protect the patient information in medical images, this article proposes a robust watermarking algorithm for medical images based on Harris-SURF-DCT. First, the corners of the medical image are extracted using the Harris corner detection algorithm, and then, the previously extracted corners are described using the method of describing feature points in the SURF algorithm to generate the feature descriptor matrix. Then, the feature descriptor matrix is processed through the perceptual hash algorithm to obtain the feature vector of the medical image, which is a binary feature vector with a size of 32 bits. Secondly, to enhance the security of the watermark information, the logistic map algorithm is used to encrypt the watermark before embedding the watermark. Finally, with the help of cryptography knowledge, third party, and zero-watermarking technology, the algorithm can embed the watermark without modifying the medical image. When extracting the watermark, the algorithm can extract the watermark from the test image without the original image. In addition, the algorithm has strong robustness to conventional attacks and geometric attacks. Especially under geometric attacks, the algorithm performs better.

A Novel Invariant Based Commutative Encryption and Watermarking Algorithm for Vector Maps

Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks but poor resistance to vertex attacks (e.g., addition, deletion, etc.). To solve this problem, here we propose a novel invariant-based CEW algorithm for vector maps, which consists of permutation-based encryption scheme and coordinates-based watermarking scheme. In the encryption scheme, the encryption key is generated via the Gaussian distribution method combined with the SHA-512 hash method; then, the double random position permutation strategy is applied to the vector map encryption. In watermarking embedding scheme, the original watermark image is scrambled via logistic chaotic encryption before embedding, and the coordinates of all the vertices are normalized. Then, the scrambled watermark image is embedded into the normalized coordinates. Results show that: proposed method is more robust to conventional attacks (e.g., vertex addition and deletion, reordering and data format conversion) and geometric attacks (e.g., scaling and translation). In addition, compared with the existing CEW methods for vector maps, the proposed method has higher security and stronger robustness against vertex attacks.

A Mutual Security Authentication Method for RFID-PUF Circuit Based on Deep Learning

The Industrial Internet of Things ( IIoT ) is designed to refine and optimize the process controls, thereby leveraging improvements in economic benefits, such as efficiency and productivity. However, the Radio Frequency Identification ( RFID ) technology in an IIoT environment has problems such as low security and high cost. To overcome such issues, a mutual authentication scheme that is suitable for RFID systems, wherein techniques in Deep Learning ( DL ) are incorporated onto the Arbiter Physical Unclonable Function ( APUF ) for the secured access authentication of the IC circuits on the IoT, is proposed. The design applies the APUF-MPUF mutual authentication structure obtained by DL to generate essential real-time authentication information, thereby taking advantage of the feature that the tag in the PUF circuit structure does not need to store any essential information and resolving the problem of key storage. The proposed scheme also uses a bitwise comparison method, which hides the PUF response information and effectively reduces the resource overhead of the system during the verification process, to verify the correctness of the two strings. Security analysis demonstrates that the proposed scheme has high robustness and security against different conventional attack methods, and the storage and communication costs are 95.7% and 42.0% lower than the existing schemes, respectively.

An SVD Values Ordering Scheme for Medical Image Watermarking

In order to increase the security of medical image sharing and transfer, we present in this work a watermarking approach to protect medical images. This approach consists of inserting hospital signature information and patient data into the medical image. The goal of our work is to integrate the watermark with as little distortion as possible to retain the medical information in the image. In this approach DWT decomposition is applied to the image which allows a very fine adjustment during the insertion. An SVD is then applied to the three subbands LL, LH and HL, which allows storing the maximum energy of the image in a minimum of singular values. A combination of the three resulting singular value matrices is then performed for watermark integration. The proposed approach ensures data integrity, confidentiality when sharing data, and robustness to several conventional attacks.

A flexible image encryption algorithm based on 3D CTBCS and DNA computing

In this paper, a novel image encryption algorithm based on a new discrete chaotic system is presented. The chaotic characteristics of the new chaotic system are analyzed by phase diagram, Lyapunov exponent, bifurcation diagram and complexity analysis. The randomness of chaotic sequences is test by the NIST SP 800-22 test package. The calculation time with different length sequence is recorded. Based on the analyses results, a flexible encryption scheme is designed for 2D image and 3D image. The hash value which is calculated from the SHA-256 hash function is used to change the initial conditions of the discrete system firstly. And then, the chaotic sequences are used to scramble and spread the value for the images by Arnold matrix and DNA diffusion algorithm. The security analysis shows that the proposed encryption algorithm possesses higher security features to preserve the subject and resist conventional attack. The results of this paper offer a different realization scheme for protection of image files.

Conventional Attack vs Digital Attack in the Light of International Law

International law does not currently possess adequate instruments to define aggression in cyberspace, as well as to identify and punish perpetrators. The classical definition of aggression is inadequate to the reality of cyberspace, in the area of legal doctrine and practice, the international law is not adjusted to the contemporary digital reality and the destinations in which the digital reality is heading. The current definition of aggression reflects past conflicts. Conventional aggression is related to the attack on the physical elements of a state (related to the territory). Whereas, a digital attack may, but does not have to, have a direct relation to the territory of the state. The nature of cyberspace varies from other spaces. The a-territorial character of cyberspace influences the assortment of difficulties in the international legal issues regarding cyberspace. Cyberspace is not an additional or a marginal field of the operations of units, organisations andthe state, but an area to which the entire sphere of operations is transferring. The war of the future will take place to a large extent in cyberspace.

A lossless DWT-SVD domain watermarking for medical information security.

The goal of this work is to protect as much as possible the images exchanged in telemedicine, to avoid any confusion between the patient’s radiographs, these images are watermarked with the patient’s information as well as the acquisition data. Thus, during the extraction, the doctor will be able to affirm with certainty that the images belong to the treated patient. The ultimate goal of our completed work is to properly integrate the watermark with as little distortion as possible to typically retain the medical information in the image. In this innovative approach used DWT decomposition is appropriately applied to the image which allows a remarkably satisfactory adjustment during the insertion. An SVD is then applied to the three subbands LL, LH and HL, which ideally allows retaining the maximum energy of the used image in a guaranteed minimum of singular values. A specific combination of the three resulting singular value matrices is then performed for watermark integration. The proposed approach ensures data integrity, patient confidentiality when sharing data, and robustness to several conventional attacks.

A Hybrid Adaptive Development Algorithm and Machine Learning Based Method for Intrusion Detection and Prevention System

Network Intrusion detection and prevention Systems (NIDPS) are employed in monitoring a network which safeguards user integrity, privacy thereby ensuring the data security and availability in a network. Such systems not only monitor the suspicious activities in a network but also used as control systems to eliminate the malicious users from the network. In this paper, a Hybrid Adaptive Development Algorithm and Machine Learning Algorithm (ADA-MLA) method is proposed to identify the malicious activities and eliminating them from the network. The deployment of honeypot-based intrusion is improved adaptive development algorithm. Machine learning algorithm has been employed in the Hybrid IDPS for learning the network data patterns which also identifies the maximum probable attacks in the network. The signatures for the DARPA 99 data set have been updated during the implementation of intrusion prevention system on a real-time basis. The hybrid method works on (i) classifying the attacks based on protocols and (ii) classifying the attacks on pre-determined threshold values. Hence, both known and unknown attacks can be easily captured in the proposed hybrid IDPS method which thereby achieves higher attack detection and prevention accuracy while compared to the conventional attack detection and prevention methodologies.

Robust SVD-based schemes for medical image watermarking

Nowadays, several information security issues can compromise the medical images administration. The source and origin of the medical image must be authenticated to verify that it corresponds to the right patient. A second issue is to avoid detachment between an electronic medical record and the corresponding images. One possible solution is the use of digital watermarking techniques applied to medical images, considering the imperceptibility and robustness requirements of the medical imaging watermarking. To increase the security of medical image sharing and transfer, we present in this work a watermarking approach to protect medical images. This innovative approach consists precisely of carefully inserting hospital signature information and patient data into the medical image. The ambitious goal of our work is to properly integrate the watermark with as little distortion as possible to typically retain the medical information in the image. In this flexible approach DWT decomposition is applied to the image which allows a remarkably satisfactory adjustment during the insertion. An SVD is then applied to the three subbands LL, LH and HL, which allows retaining the maximum energy of the image in a necessary minimum of singular values. A possible combination of the three resulting singular value matrices is then performed for watermark integration. A possible combination of the three resulting singular value matrices is then performed for watermark integration. The proposed approach ensures information integrity, patient confidentiality when sharing data, and robustness to several conventional attacks.

The security of transport of radioactive and nuclear material in Belgium

This article describes and assesses the security of transport of radioactive and nuclear material in Belgium that has been boosted after the terrorist attacks in Brussels in 2016. The article looks at the different possibilities of terrorist attacks on transports of radioactive and nuclear material and the possible consequences: theft of radioactive material for use in a radioactive exposure device, a radioactive dispersal device, or an improvised nuclear weapon; or a conventional attack on a transport, releasing radiation into the environment. The focus on insider threat is a step forward, but it may not divert attention from regularly updating security measures against outsider threat. Some recommendations are provided to ensure continuous improvement in the transport of radioactive and nuclear material.

Vulnerability analysis in RF locking systems of vehicles in Bogotá, Colombia.

A car electronic security system aims to prevent its theft, the theft of its parts or of elements in its interior. Studying these systems allows identifying and mitigating vulnerabilities. Nowadays, there are different types of attacks on these systems to exploit their vulnerabilities, such as replay, relay, brute-force or jamming attacks, among others. In the last five years in Bogotá, Colombia, the average number of stolen vehicles was 3,073 per year. This research project proposes the detection of vulnerabilities in the security system of vehicles in this city. A sample of 43 vehicles of different brands sold and registered in the city is taken. The replay attack was executed, as well as a modification of the brute-force attack. Results show that most of the implemented security systems in Bogotá are susceptible of being successfully attacked through the proposed methods. The analysis done on the brute-force attack highlights a considerable reduction in time for unlocking the vehicle compared to the conventional attack in more vulnerable RKE systems. Replay attacks turn successful in great part of the sample and, furthermore, it is concluded that the unlocking key code can be generated from the locking one.

A robust blind medical image watermarking approach for telemedicine applications.

In order to enhance the security of exchanged medical images in telemedicine, we propose in this paper a blind and robust approach for medical image protection. This approach consists in embedding patient information and image acquisition data in the image. This imperceptible integration must generate the least possible distortion. The watermarked image must present the same clinical reading as the original image. The proposed approach is applied in the frequency domain. For this purpose, four transforms were used: discrete wavelets transform, non-subsampled contourlet transform, non-subsampled shearlet transform and discreet cosine transform. All these transforms was combined with Schur decomposition and the watermark bits were integrated in the upper triangular matrix. To obtain a satisfactory compromise between robustness and imperceptibility, the integration was performed in the medium frequencies of the image. Imperceptibility and robustness experimental results shows that the proposed methods maintain a high quality of watermarked images and are remarkably robust against several conventional attacks.

Fighting ISIS in Syria: Operation Euphrates Shield and the lessons learned from the al-Bab Battle

ABSTRACT This paper analyses the Operation Euphrates Shield (OES) al-Bab battle and presents the lessons learned. OES started with a mixed force of Free Syrian Army, Turkish special forces and armoured units. During the operation, the aims and the force structure gradually changed, yet not the command structure. When OES aimed to capture al-Bab, ISIS employed conventional active defence strategy. The OES commander’s insistence on employing special forces increased own casualties and al-Bab was seized only after resorting to a conventional urban attack. OES presents tactical and operational lessons for the militaries on structure and execution of operations against an irregular adversary employing conventional means.