Top Attack Research Articles

Investigation of Multi layered Mitigation Systems for Protection from 120mm Mortar HE Top Attacks

This paper investigates the protection of reinforced concrete (RC) structures from the Mortar 120mm HE (high explosive) top attacks. Two multi-layered mitigation systems are proposed to be added on RC structures' roofs to achieve full protection against the Mortar 120mm destroying effects (i.e. ballistic penetration and explosion effects). The proposed mitigation systems combine relatively high-strength materials, to stop or slow down the projectile, with lightweight porous materials, to attenuate the explosion shock wave. Another function of the porous materials is to increase the thickness of the proposed mitigation systems and hence increasing the explosion stand-off distance. Traditional construction materials, steel and RC, were used as cheap high-strength materials, whereas commercial rigid polyurethane foam and light-weight brick were examined as shock wave absorbers. Two firing tests of the 120mm bomb from cannon barrels against one-story RC structures strengthened with the proposed protection systems were executed. A numerical simulation of the real firing tests was performed via Autodyn hydrocode to further analyze the performance of the constituting components in alleviating the round effects. The current study demonstrated that the proposed mitigation systems, which are based on the multi-layering concept, are efficient and have their merits in defeating the Mortar 120mm HE attacks.

Query-Efficient Generation of Adversarial Examples for Defensive DNNs via Multiobjective Optimization

Due to the inherent vulnerability of Deep Neural Networks (DNNs), Adversarial Example (AE) attack has become a serious threat to intelligent systems, e.g., the failure cause of an image classification system. Different to existing works, in this paper we are interested in the generation of AEs for DNNs with defensive mechanisms. To make the attack more practical, we exploit a query-based method to generate image AEs in a black-box attack setting. Considering that the generation of AEs is inherently a constrained optimization problem, this paper first formulates three objectives regarding to defensive DNNs, i.e, attack effectiveness, attack evasiveness and attack coverage. Then, this paper proposes a query-efficient AE attack based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to address the perturbation optimization problem. To improve the efficiency of search and query, AE-specific operators including block-level and pixel-level crossovers, discrete perturbation mutation and direction-driven reproduction are designed within the GA-based search framework. In addition, predication-based adaptation of reproduction-related parameters is implemented to speed up the search convergence. PSO-based jumping process is further devised to avoid stuck in local optimum. Benchmark-based experiments evaluated the efficiency of our method, which can achieve an attack success rate of 100% with averagely 52.95% reduced queries in contrast to existing black-box attacks on non-defensive models. For defensive DNN models, our method can obtain top attack performance with the query reduction up to 70.92% comparing with the candidates.

Hospital cybersecurity risks and gaps: Review (for the non-cyber professional).

BackgroundHealthcare is facing a growing threat of cyberattacks. Myriad data sources illustrate the same trends that healthcare is one of the industries with the highest risk of cyber infiltration and is seeing a surge in security incidents within just a few years. The circumstances thus begged the question: are US hospitals prepared for the risks that accompany clinical medicine in cyberspace?ObjectiveThe study aimed to identify the major topics and concerns present in today's hospital cybersecurity field, intended for non-cyber professionals working in hospital settings.MethodsVia structured literature searches of the National Institutes of Health's PubMed and Tel Aviv University's DaTa databases, 35 journal articles were identified to form the core of the study. Databases were chosen for accessibility and academic rigor. Eighty-seven additional sources were examined to supplement the findings.ResultsThe review revealed a basic landscape of hospital cybersecurity, including primary reasons hospitals are frequent targets, top attack methods, and consequences hospitals face following attacks. Cyber technologies common in healthcare and their risks were examined, including medical devices, telemedicine software, and electronic data. By infiltrating any of these components of clinical care, attackers can access mounds of information and manipulate, steal, ransom, or otherwise compromise the records, or can use the access to catapult themselves to deeper parts of a hospital's network. Issues that can increase healthcare cyber risks, like interoperability and constant accessibility, were also identified. Finally, strategies that hospitals tend to employ to combat these risks, including technical, financial, and regulatory, were explored and found to be weak. There exist serious vulnerabilities within hospitals' technologies that many hospitals presently fail to address. The COVID-19 pandemic was used to further illustrate this issue.ConclusionsComparison of the risks, strategies, and gaps revealed that many US hospitals are unprepared for cyberattacks. Efforts are largely misdirected, with external—often governmental—efforts negligible. Policy changes, e.g., training employees in cyber protocols, adding advanced technical protections, and collaborating with several experts, are necessary. Overall, hospitals must recognize that, in cyber incidents, the real victims are the patients. They are at risk physically and digitally when medical devices or treatments are compromised.

Reinforcement Learning for Hyperparameter Tuning in Deep Learning-based Side-channel Analysis

Deep learning represents a powerful set of techniques for profiling sidechannel analysis. The results in the last few years show that neural network architectures like multilayer perceptron and convolutional neural networks give strong attack performance where it is possible to break targets protected with various countermeasures. Considering that deep learning techniques commonly have a plethora of hyperparameters to tune, it is clear that such top attack results can come with a high price in preparing the attack. This is especially problematic as the side-channel community commonly uses random search or grid search techniques to look for the best hyperparameters.In this paper, we propose to use reinforcement learning to tune the convolutional neural network hyperparameters. In our framework, we investigate the Q-Learning paradigm and develop two reward functions that use side-channel metrics. We mount an investigation on three commonly used datasets and two leakage models where the results show that reinforcement learning can find convolutional neural networks exhibiting top performance while having small numbers of trainable parameters. We note that our approach is automated and can be easily adapted to different datasets. Several of our newly developed architectures outperform the current state-of-the-art results. Finally, we make our source code publicly available.
 https://github.com/AISyLab/Reinforcement-Learning-for-SCA

Model Indicators and Evaluation Criteria of Strength Readiness of Highly Qualified Arm-Wrestlers

In the arm-wrestling technique, the main element is the attack phase, which aims to achieve a quick superiority over the enemy. Researchers Zhivora and Usanov classified four main attack methods: top attack, hook attack, push attack, and side attack. During a side attack, a great deal of stress is placed on the flexors of the hand. In connection with this, four strength exercises were selected as test indicators: flexion of the fingers, stretch with a hammer, hook and bending of the hand. These exercises were chosen to determine the level of strength readiness of highly qualified arm-wrestlers. The work aimed to determine the model indicators of strength readiness of highly qualified arm-wrestlers of different weight categories. The study involved 24 arm-wrestlers, 8 in the weight category up to 80 kg, 8 – from 80 to 100 kg and 8 – over 100 kg. Three test athletes are world champions in arm-wrestling, 7 are winners of European and world championships, 9 are participants in European and world championships, 5 are winners of national championships of Ukraine. The following research methods were used in work: theoretical analysis and generalization of scientific, methodological and notable information, pedagogical observation, pedagogical experiment, methods of mathematical statistics. The analysis of the strength capabilities of highly qualified arm-wrestlers and their strength readiness models made it possible to develop assessment criteria for the level of strength readiness of highly qualified arm-wrestlers of three weight categories. Three levels of strength readiness have been identified: low (х ̅ - σ), high (х ̅ + σ) and medium – more (х ̅ - σ), but less (х ̅ + σ). The conducted research allowed to establish the peculiarities of the levels of strength readiness development among highly qualified arm-wrestlers by weight categories. Model indicators of strength readiness of highly qualified arm-wrestlers were also determined. The analysis made it possible to state that athletes of lightweight categories (up to 80 kg and 80-100 kg) are more harmoniously developed according to the test results. Heavy arm-wrestlers (over 100 kg) showed worse results than expected.

Ballistic Protection of Military Shelters from Mortar Fragmentation and Blast Effects using a Multi layer Structure

In addition to its usage as a top attack ammunition in the battle field against troops, 120 mm mortar bomblethas been recently used in the terror attacks against military shelters and civil constructions. This research studiesthe protection of vehicle and personnel military shelters against mortar fragmentation warhead projectile and it’sdestroying effects. The mortar warhead threat combines both blast load and ballistic fragment penetration effects. Composite structure layers are proposed herein to be integrated with concertina walls to achieve full protection against the mortar projectile destroying effects. The current paper investigates the ability of the proposed layers to stop the mortar’s fragments and to mitigate its blast load. The velocity and the mass distribution of the produced projectile fragments were estimated using Split-X software. Besides, the ability of the proposed protection layers to stop the fragments and mitigate the blast wave was evaluated using AUTODYN hydrocode. A static firing test was then performed to validate the theoretical results and verify the effectiveness of the proposed protection added layers. The current study showed that the proposed composite layers are sufficient to protect the military shelters from the mortar’s destroying ballistic effects.

Secure Integrated Circuit with Physical Attack Detection based on Reconfigurable Top Metal Shield

Invasive physical attacks on integrated circuits (ICs), such as de-packaging, focused ion beam (FIB) chip editing, and micro-probing attempts, constitute security threats for chips with potentially valuable information, such as smart cards. Using a state-of-the-art circuit-editing technique, an attacker can remove an IC’s top metal layer, leaving its secure information exposed to micro-probing attacks. Security ICs can be seriously threatened by such attacks and thus require on-chip countermeasures. Conventional active shields, however, have difficulty coping with physical attacks based on FIB chip editing (i.e., bypassing the top metal shield). This study presents a novel countermeasure against physical attacks based on the use of a reconfigurable metal shield for both top metal removal and microprobing attack detection. This shield consists of two circuits: an FIB chip editing detection circuit consisting of a random number generator and a micro-probing attempt detection circuit consisting of two conditionally synchronized ring oscillators. Both circuits share a randomly reconfigured top metal shield, which represents a promising solution for security against state-of-the-art invasive attacks.

Effect of Explosive Reactive Armour Cover Plate on Interaction of ERA and Explosively Formed Projectile

Explosive reactive armour (ERA) is used to protect the armoured vehicles against chemical energy warheads and long‐rod penetrators. ERA generally consists of an ERA sandwich and an outer steel cover to protect it from unintended initiation. Explosively formed projectiles (EFPs) are used as antiarmour warheads, and their use in top attack antiarmour weapons is increasing. Interaction of EFP with the ERA sandwich alone has been studied in the past. This paper studies the effect of the cover plate and its thickness on the interaction of the EFP and the ERA sandwich. Numerical simulations and experiments have been used to study the interaction. It has been found that the penetration in the target is reduced as the thickness of the cover plate increases. Moreover, the decrease in penetration is directly proportional to the thickness of the cover plate. Also it has been found that the residual EFP after penetrating the cover plate has sufficient energy to initiate the ERA sandwich. The results of the numerical simulation and the experiments are in close agreement.

Network Security Intelligence Center as a combination of SIC and NOC

In modern networks, information security (IS) incidents have become not only numerous and diverse, but more damaging and disruptive. According to 2017 Cyber Attacks Statistics from hackmaggedon.com, among top attacks are malware, account and DNS hijacking, targeted attacks, DDoS, defacements, malvertising, and SQL injection. Various preventive controls based on IS risk assessment results decrease the majority, but not all IS incidents. Any delay and only reactive actions to IS incidents puts organization’s assets under risk. Therefore, an IS incident management system has become an integral part of the whole organization’s governance system. Thus, in this paper, we propose to unite together all advantages of a Security Intelligence Center and a Network Operations Center in a unified Network Security Intelligence Center (NSIC).

Recommender System based on Empirical Study of Geolocated Clustering and Prediction Services for Botnets Cyber-Intelligence in Malaysia

A recommender system is becoming a popular platform that predicts the ratings or preferences in studying human behaviors and habits. The predictive system is widely used especially in marketing, retailing and product development. The system responds to users preferences in goods and services and gives recommendations via Machine Learning algorithms deployed catered specifically for such services. The same recommender system can be built for predicting botnets attack. Via our Integrated Cyber-Evidence (ICE) Big Data system, we build a recommender system based on collected data on telemetric Botnets networks traffics. The recommender system is trained periodically on cyber-threats enriched data from Coordinated Malware Eradication & Remedial Platform system (CMERP), specifically the geolocations and the timestamp of the attacks. The machine learning is based on K-Means and DBSCAN clustering. The result is a recommendation of top potential attacks based on ranks from a given geolocations coordinates. The recommendation also includes alerts on locations with high density of certain botnets types.

Empirical Analysis of Web Attacks

The web applications are becoming more popular and complex in today's era of Internet. These on-line applications provide rich benefits along with risk to organization, brand and data. Malicious attackers continue to exploit vulnerabilities in applications in order to steal sensitive information. The outlines of this paper is to analyze web attacks in recent years that have compromised web applications, its data or its users. This paper includes the web attacks analysis from Website Hacking Incident Database (WHID) and other information security and news websites. Also, it is an effort to analyze various attacks on major categories of web sites which is a guide to developers to take respective appropriate preventive measures in future. The top web attacks have been identified and also the top vulnerable categories of web applications are analyzed.

Guidance Philosophy for Impact Angle Maximization for Anti-Tank Flight Vehicle

Abstract In general, anti tank weapons are designed to attack the tank on the top of the tank, where the armour is relatively weak compared to the front and sides of the tank. In this paper, a generalized guidance philosophy for top attack mode is described. This paper presents a novel guidance philosophy which enhances the impact angle for top attack mode by using seeker measurements. This proposed method also reduces the weight and cost of the weapon system by eliminating the need for Laser Range Finder, which is primarily used for target range measurement. Sensitivity analysis of the algorithm is carried out with different parameter perturbations. Lastly, the performance of the algorithm is evaluated through nonlinear Six Degrees of Freedom simulation in time domain.

Automatic control of an anti-tank guided missile based on polynomial functions

The paper presents algorithms of automatic control of an intelligent anti-tank guided missile with the possibility of attacking a target from the upper ceiling (top attack). Polynomial functions have been used to determine program trajectories. The numerical analysis of chosen algorithms has been performed. The results of work are presented in a graphical form. It appears from the conducted research that the proposed algorithms of automatic control of the anti-tank guided missile work correctly during attack from the upper ceiling, both movable and fixed.

Development of a Small Shaped Charge Insensitive Munitions Threat Test

Rocket propelled grenade (RPG) shaped charge attack threats are of particular concern for Insensitive Munitions (IM) development. In response to these threats, the U.S. Project Engineering Office for Ammunition (PEO Ammo) worked with ARDEC to develop a highly reproducible and well characterized standardized 81mm shaped charge jet initiation test configuration. This test was adopted by the U.S. DoD for RPG threat testing as specified in MIL-STD-2105D and is completed as per STANAG 4526. Recent U.S. Insensitive Munitions shaped charge initiation attention has been focused on realistic smaller shaped charge threats. STANAG 4526 discusses standardized threats related to “Top Attack Bomblets” and SCJ with “Characteristics of 50mm Rockeye”. As a representative shaped charge for smaller size threats than the RPG, the 50mm Rockeye munition has been commonly recommended for testing. However, recent testing of the 50mm Rockeye munitions has shown a large undesirable variability of jet tip characteristics. This large variability in jet tip characteristics would be consistent with a large variability in munitions response to the 50mm Rockeye jet attack. Additionally, it has become clear that this shaped charge does not represent a commonly observed threat. For this reason, an effort is currently underway to identify a dominant smaller shaped charge threat and to develop a surrogate small shaped charge threat test configuration that provides very reproducible jet characteristics. The result to date is that 40mm grenades have been identified as a dominant smaller shaped charge threat and a surrogate consistent in approach with previous efforts has been designed.

A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing

The long-term potential benefits through reduction of cost of services and improvement of business outcomes make Cloud Computing an attractive proposition these days. To make it more marketable in the wider IT user community one needs to address a variety of information security risks. In this paper, we present an extensive review on cloud computing with the main focus on gaps and security concerns. We identify the top security threats and their existing solutions. We also investigate the challenges/obstacles in implementing threat remediation. To address these issues, we propose a proactive threat detection model by adopting three main goals: (i) detect an attack when it happens, (ii) alert related parties (system admin, data owner) about the attack type and take combating action, and (iii) generate information on the type of attack by analyzing the pattern (even if the cloud provider attempts subreption). To emphasize the importance of monitoring cyber attacks we provide a brief overview of existing literature on cloud computing security. Then we generate some real cyber attacks that can be detected from performance data in a hypervisor and its guest operating systems. We employ modern machine learning techniques as the core of our model and accumulate a large database by considering the top threats. A variety of model performance measurement tools are applied to verify the model attack prediction capability. We observed that the Support Vector Machine technique from statistical machine learning theory is able to identify the top attacks with an accuracy of 97.13%. We have detected the activities using performance data (CPU, disk, network and memory performance) from the hypervisor and its guest operating systems, which can be generated by any cloud customer using built-in or third party software. Thus, one does not have to depend on cloud providers’ security logs and data. We believe our line of thoughts comprising a series of experiments will give researchers, cloud providers and their customers a useful guide to proactively protect themselves from known or even unknown security issues that follow the same patterns.

Theoretical study on the mechanism of the (3)CH(2) + NO(2) reaction.

The complex doublet potential energy surface of the CH(2)NO(2) system is investigated at the B3LYP/6-31G(d,p) and QCISD(T)/6-311G(d,p) (single-point) levels to explore the possible reaction mechanism of the triplet CH(2) radical with NO(2). Forty minimum isomers and 92 transition states are located. For the most relevant reaction pathways, the high-level QCISD(T)/6-311 + G(2df,2p) calculations are performed at the B3LYP/6-31G(d,p) geometries to accurately determine the energetics. It is found that the top attack of the (3)CH(2) radical at the N-atom of NO(2) first forms the branched open-chain H(2)CNO(2) a with no barrier followed by ring closure to give the three-membered ring isomer cC(H(2))ON-O b that will almost barrierlessly dissociate to product P(1) H(2)CO + NO. The lesser followed competitive channel is the 1,3-H-shift of a to isomer HCN(O)OH c, which will take subsequent cis-trans conversion and dissociation to P(2) OH + HCNO. The direct O-extrusion of a to product P(3) (3)O + H(2)CNO is even much less feasible. Because the intermediates and transition states involved in the above three channels are all lower than the reactants in energy, the title reaction is expected to be rapid, as is consistent with the measured large rate constant at room temperature. Formation of the other very low-lying dissociation products such as NH(2) + CO(2), OH + HNCO and H(2)O + NCO seems unlikely due to kinetic hindrance. Moreover, the (3)CH(2) attack at the end-O of NO(2) is a barrier-consumed process, and thus may only be of significance at very high temperatures. The reaction of the singlet CH(2) with NO(2) is also briefly discussed. Our calculated results may assist in future laboratory identification of the products of the title reaction.

Theoretical study on reaction mechanism of the CF radical with nitrogen dioxide

The singlet potential energy surface of the [CFNO2] system is investigated at the B3LYP and CCSD(T) (single-point) levels to explore the possible reaction mechanism of CF radical with NO2. The top attack of C-atom of CF radical at the N-atom of NO2 molecule first forms the adduct isomer FCNO21 followed by oxygen-shift to give trans-OC(F)NO 2 and then to cis-OC(F)NO 3. Subsequently, the most favorable channel is a direct dissociation of 2 and 3 to product P1 FCO+NO. The second and third less favorable channels are direct dissociation of 3 to product P2 FNO+CO and isomerization of 3 to a complex NOFCO 4, which can easily dissociate to product P3 FON+CO, respectively. The large exothermicity released in these processes further drives most of the three products P1, P2, and P3 to take secondary dissociation to the final product P12 F+CO+NO. Another energetically allowed channel is formation of product P41NF+CO2, yet it is much less competitive than P1, P2, P3, and P12. The present calculations can well interpret one recent experimental fact that the title reaction is quite fast yet still much slower than the analogous reaction CH+NO2. Also, the results presented in this article may be useful for future product distribution analysis of the title reaction as well as for the analogous CCl and CBr reactions. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1907–1919, 2001

The powerful role of the Commanders Decision Aid (CDS) software and acoustic sensor to increasing ground combat vehicle survivability

With the proliferation of diverse anti-tank guided missiles and top attack munitions, ground combat vehicles require the use of multispectral sensors. The issues that arise by adding sensors to these vehicles are the additional cost, size, weight, and power required. Even more critical is the ability of the sensor to provide timely, high-confidence, low-false alarm rate threat detection and classification information to the crew. Amidst a heavy signal clutter battlefield and multiple sensors aboard the vehicle, the concerns are information overload for the crew, being detected by enemy sensors, and quickly depleting limited countermeasure assets by responding to false alarms. The use of infrared and laser warning receivers (IRW, LWR) has been assessed to be very beneficial toward this aim, but not sufficient. Operations analysis has shown that with the addition of an acoustic sensor and decision aid software, crew survivability increases dramatically with low cost. The paper reviews the ground combat vehicle problem space, the data, the complementary data the IRW, LWR, and acoustic sensors provide, and how the Commander’s Decision Aid (CDA) software performs multispectral/multisensor fusion, threat classification, threat prioritization, countermeasures response management, and countermeasures effectiveness assessment via various scenario descriptions.

Millimetric Wave Seeker for Third Generation Antitank Guided Missiles

For the third generation antitank guided missiles (ATGMs) with fire-and-forget and top attack capabilities, a noncoherent millimetric wave (MMW) active radar seeker has been configured with all weather capabilities. To meet the stringent dimensional and weight constraints and beamwidth requirements of ATGM, a W-band system has been designed with trans-twist antenna with a compact comparator. The paper covers the system description and critical design issues, and presents the performance results achieved so far. Areas for improvements, especially for achieving a higher range, have also been pointed out.