Biblio

At present, the acoustic emission (AE) method has the advantages of live measurement and easy fault location, so it is very suitable for insulation defect detection of power equipments such as GIS, etc. While the conventional AE detection system or instruments always can't give a right discrimination result, because them always work based on the reference voltage or phase information from an auxiliary 220V voltage signal source rather than the operation high voltage (HV) with the real phase information corresponding to the detected AE pulsed signals. So there is a random phase difference between the reference phase and operation phase. The discharge fingerprint formed by the detected AE pulsed signals with reference phase using the same processing process is compared to the discharge fingerprint database formed in the HV laboratory with the real phase information, therefore, the system may not be able to discriminate the discharge mode of the field measured data from GIS in substation operation. In this paper, in order to design and develop a general fast analysis algorithm model for PD acoustic detection system to make an assistant diagnosis, the pattern identification with phase compensation was designed and applied. The results show that the method is effective and useful to deatl with AE signals meased in operation situation.

Prior work on mobile app reviews has demonstrated that user reviews contain a wealth of information and are seen as a potential source of requirements. However, most of the studies done in this area mainly focused on mining and analyzing user reviews from the US App Store, leaving reviews of users from other countries unexplored. In this paper, we seek to understand if the perception of the same apps between users from other countries and that from the US differs through analyzing user reviews. We retrieve 300,643 user reviews of the 15 most downloaded iOS apps of 2018, published directly by Apple, from nine English-speaking countries over the course of 5 months. We manually classify 3,358 reviews into several software quality and improvement factors. We leverage a random forest based algorithm to identify factors that can be used to differentiate reviews between the US and other countries. Our preliminary results show that all countries have some factors that are proportionally inconsistent with the US.

Message Queue Telemetry Transport (MQTT) is widely accepted as a data exchange protocol in Internet of Things (IoT) environment. For security, MQTT supports Transport Layer Security (MQTT-TLS). However, MQTT-TLS provides thing-to-broker channel encryption only because data can still be exposed after MQTT broker. In addition, ACL becomes impractical due to the increasing number of rules for authorizing massive IoT devices. For solving these problems, we propose MQTT Thing-to-Thing Security (MQTT-TTS) which provides thing-to-thing security which prevents data leak. MQTT-TTS also provides the extensibility to include demanded security mechanisms for various security requirements. Moreover, the transparency of MQTT-TTS lets IoT application developers implementing secure data exchange with less programming efforts. Our MQTT-TTS implementation is available on https://github.com/beebit-sec/beebit-mqttc-sdk for evaluation.

In today's IIoT world, most of the IoT platform providers like Microsoft, Amazon and Google are focused towards connecting devices and extract data from the devices and send the data to the Cloud for analytics. Only there are few companies concentrating on Security measures implemented on Edge Node. Gartner estimates that by 2020, more than 25 percent of all enterprise attackers will make use of the Industrial IoT. As Cyber Security Threat is getting more important, it is essential to ensure protection of data both at rest and at motion. The reflex of Cyber Security in the Industrial IoT Domain is much more severe when compared to the Consumer IoT Segment. The new bottleneck in this are security services which employ computationally intensive software operations and system services [1]. Resilient services consume considerable resources in a design. When such measures are added to thwart security attacks, the resource requirements grow even more demanding. Since the standard IIoT Gateways and other sub devices are resource constrained in nature the conventional design for security services will not be applicable in this case. This paper proposes an intelligent architectural paradigm for the Constrained IIoT Gateways that can efficiently identify the Cyber-Attacks in the Industrial IoT domain.

As Electric Power is one of the major concerns, so the concept of the automatic lighting and security system saves the electrical energy. By using the automatic lightning, the consumption of electrical power can be minimized to a greater extent and for that sensors and microcontrollers can be designed in such a manner such that lights get ON/OFF based on motion in a room. The various sensors used for sensing the motion in an area are PIR motion sensor, IR Motion Sensor. An IR sensor senses the heat of an object and detects its motion within some range as it emits infrared radiations and this complete process can be controlled by microcontroller. Along with that security system can be applied in this concept by programming the microcontroller in such a way that if there is some movement in an area then lights must get ON/OFF automatically or any alarm must start. This chapter proposes the framework for the smart lightning with security systems in a building so that electrical power can be utilized efficiently and secures the building.

With the globalization of manufacturing and supply chains, ensuring the security and trustworthiness of ICs has become an urgent challenge. Split manufacturing (SM) and layout camouflaging (LC) are promising techniques to protect the intellectual property (IP) of ICs from malicious entities during and after manufacturing (i.e., from untrusted foundries and reverse-engineering by end-users). In this paper, we strive for “the best of both worlds,” that is of SM and LC. To do so, we extend both techniques towards 3D integration, an up-and-coming design and manufacturing paradigm based on stacking and interconnecting of multiple chips/dies/tiers. Initially, we review prior art and their limitations. We also put forward a novel, practical threat model of IP piracy which is in line with the business models of present-day design houses. Next, we discuss how 3D integration is a naturally strong match to combine SM and LC. We propose a security-driven CAD and manufacturing flow for face-to-face (F2F) 3D ICs, along with obfuscation of interconnects. Based on this CAD flow, we conduct comprehensive experiments on DRC-clean layouts. Strengthened by an extensive security analysis (also based on a novel attack to recover obfuscated F2F interconnects), we argue that entering the next, third dimension is eminent for effective and efficient IP protection.

Intellectual property (IP) and integrated circuit (IC) piracy are of increasing concern to IP/IC providers because of the globalization of IC design flow and supply chains. Such globalization is driven by the cost associated with the design, fabrication, and testing of integrated circuits and allows avenues for piracy. To protect the designs against IC piracy, we propose a fingerprinting scheme based on side-channel power analysis and machine learning methods. The proposed method distinguishes the ICs which realize a modified netlist, yet same functionality. Our method doesn't imply any hardware overhead. We specifically focus on the ability to detect minimal design variations, as quantified by the number of logic gates changed. Accuracy of the proposed scheme is greater than 96 percent, and typically 99 percent in detecting one or more gate-level netlist changes. Additionally, the effect of temperature has been investigated as part of this work. Results depict 95.4 percent accuracy in detecting the exact number of gate changes when data and classifier use the same temperature, while training with different temperatures results in 33.6 percent accuracy. This shows the effectiveness of building temperature-dependent classifiers from simulations at known operating temperatures.

Trademarks are recognizable images and/or words used to distinguish various products or services. They become associated with the reputation, innovation, quality, and warranty of the products. Countries around the world have offices for industrial/intellectual property (IP) registration. A new trademark image in application for registration should be distinct from all the registered trademarks. Due to the volume of trademark registration applications and the size of the databases containing existing trademarks, it is impossible for humans to make all the comparisons visually. Therefore, technological tools are essential for this task. In this work we use a pre-trained, publicly available Convolutional Neural Network (CNN) VGG19 that was trained on the ImageNet database. We adapted the VGG19 for the trademark image retrieval (TIR) task by fine tuning the network using two different databases. The VGG19v was trained with a database organized with trademark images using visual similarities, and the VGG19c was trained using trademarks organized by using conceptual similarities. The database for the VGG19v was built using trademarks downloaded from the WEB, and organized by visual similarity according to experts from the IP office. The database for the VGG19c was built using trademark images from the United States Patent and Trademarks Office and organized according to the Vienna conceptual protocol. The TIR was assessed using the normalized average rank for a test set from the METU database that has 922,926 trademark images. We computed the normalized average ranks for VGG19v, VGG19c, and for a combination of both networks. Our method achieved significantly better results on the METU database than those published previously.

Within “Industrie 4.0” approach 3D printing technology is characterized as one of the disruptive innovations. Conventional supply chains are replaced by value-added networks. The spatially distributed development of printed components, e.g. for the rapid delivery of spare parts, creates a new challenge when differentiating between “original part”, “copy” or “counterfeit” becomes necessary. This is especially true for safety-critical products. Based on these changes classic branded products adopt the characteristics of licensing models as we know them in the areas of software and digital media. This paper describes the use of digital rights management as a key technology for the successful transition to Additive Manufacturing methods and a key for its commercial implementation and the prevention of intellectual property theft. Risks will be identified along the process chain and solution concepts are presented. These are currently being developed by an 8-partner project named SAMPL (Secure Additive Manufacturing Platform).

This paper presents a methodology for IP core protection of CE devices from both buyer's and seller's perspective. In the presented methodology, buyer fingerprint is embedded along seller watermark during architectural synthesis phase of IP core design. The buyer fingerprint is inserted during scheduling phase while seller watermark is implanted during register allocation phase of architectural synthesis process. The presented approach provides a robust mechanisms of IP core protection for both buyer and seller at zero area overhead, 1.1 % latency overhead and 0.95 % design cost overhead compared to a similar approach (that provides only protection to IP seller).

Field-programmable gate arrays (FPGAs) are widely applied in various fields for its merit of reconfigurability. The reusable intellectual property (IP) design blocks are usually adopted in the more complex FPGA designs to shorten design cycle. IP infringement hence becomes a concern. In this paper, we propose a new pay-per-use scheme using the lock and key mechanism for the protection of FPGA IP. Physical Unclonable Function (PUF) is adopted to generate a unique ID for each IP instance. An extra Finite State Machine (FSM) is introduced for the secure retrieval of PUF information by the FPGA IP vendor. The lock is implemented on the original FSM. Only when the FPGA developer can provide a correct license, can the FSM be unlocked and start normal operation. The FPGA IP can hence be protected from illegal use or distribution. The scheme is applied on some benchmarks and the experimental results show that it just incurs acceptably low overhead while it can resist typical attacks.

Diagnostic research methods were designed to draw attention to the needs of future engineers in the field of innovative methods of acquiring knowledge, skills and competencies in the protection of intellectual property in order to prepare for functioning in the economy 4.0.

A trademark may be a word, phrase, symbol, sound, color, scent or design, or combination of these, that identifies and distinguishes the products or services of a particular source from those of others. Obtaining a trademark is a complex, time intensive and costly process that involves varied steps before the trademark can be registered including searching prior trademarks, filing of the trademark application, review of the trademark application and final publication for opposition by the public. Currently, the process of trademark registration, renewal and validation faces numerous challenges such as the requirement for registration in different jurisdictions, maintenance of centralized databases in different jurisdictions, proving the authenticity of the physical trademark documents, identifying the violation and abuse of the intellectual property etc. to name a few. Recently, blockchain technology has shown great potential in a variety of industries such as finance, education, energy and resource management, healthcare, due to its decentralization and non-tampering features. Furthermore, in the recent years, smart contracts have attracted increased attention due to the popularity of blockchains. In this study, we have utilized Hyperledger fabric as the permissioned blockchain framework along with smart contracts to provide solution to the financial, procedural, enforcement and protection related challenges of the current trademark system. Our blockchain based application seeks to provide a secure, decentralized, immutable trademark system that can be utilized by the intellectual property organizations across different jurisdictions for easily and effectively registering, renewing, validating and distributing digital trademark certificates.

The characteristics of decentralization, tamper-resistance and transaction anonymity of blockchain can resolve effectively the problems in traditional intellectual property such as the difficulty of electronic obtaining for evidence, the high cost and low compensation when safeguarding the copyrights. Blockchain records the information through encryption algorithm, removes the third party, and stores the information in all nodes to prevent the information from being tampered with, so as to realize the protection of intellectual property. Starting from the bottom layer of blockchain, this paper expounds in detail the characteristics and the technical framework of blockchain. At the same time, according to the existing problems in transaction throughput, time delay and resource consumption of blockchain system, optimization mechanisms such as cross-chain and proof of stake are analyzed. Finally, combined with the characteristics of blockchain technology and existing application framework, this paper summarizes the existing problems in the industry and forecasts the development trend of intellectual property based on blockchain technology.

Researchers develop bioassays by rigorously experimenting in the lab. This involves significant fiscal and skilled person-hour investment. A competitor can reverse engineer a bioassay implementation by imaging or taking a video of a biochip when in use. Thus, there is a need to protect the intellectual property (IP) rights of the bioassay developer. We introduce a novel 3D multilayer-based obfuscation to protect a biochip against reverse engineering.

Increased use of secure chat and voice/ video apps has transformed the social life. While the benefits and facilitations are seemingly limitless, so are the asscoiacted vulnerabilities and threats. Besides ensuring confidentiality requirements for common users, known facts of non-readable contents over the network make these apps more attractive for criminals. Though access to contents of cryptograhically secure sessions is not possible, network forensics of secure apps can provide interesting information which can be of great help during criminal invetigations. In this paper, we presented a novel framework of profiling the secure chat and voice/ video calling apps which can be employed to extract hidden patterns about the app, information of involved parties, activities of chatting, voice/ video calls, status indications and notifications while having no information of communication protocol of the app and its security architecture. Signatures of any secure app can be developed though our framework and can become base of a large scale solution. Our methodology is considered very important for different cases of criminal investigations and bussiness intelligence solutions for service provider networks. Our results are applicable to any mobile platform of iOS, android and windows.

Software Engineering is a field of new challenges every day. With every passing day, new technologies emerge. There was an era of web Applications, but the time has changed and most of the web Applications are available as Mobile Applications as well. The Mobile Applications are either android based or iOS based. To deliver error free, secure and reliable Application, it is necessary to test the Applications properly. Software testing is a phase of software development life cycle, where we test an Application in all aspects. Nowadays different type of tools are available for testing an Application automatically but still we have too many challenges for applying test cases on a given Application. In this paper the authors will discuss the challenges of automation of test cases for a Mobile based payment Application.

The majority of security breaches in cloud infrastructure in recent years are caused by human errors and misconfigured resources. Novel security models are imperative to overcome these issues. Such models must be customer-centric, continuous, not focused on traditional security paradigms like intrusion detection and adopt proactive techniques. Thus, this paper proposes CloudStrike, a cloud security system that implements the principles of Chaos Engineering to enable the aforementioned properties. Chaos Engineering is an emerging discipline employed to prevent non-security failures in cloud infrastructure via Fault Injection Testing techniques. CloudStrike employs similar techniques with a focus on injecting failures that impact security i.e. integrity, confidentiality and availability. Essentially, CloudStrike leverages the relationship between dependability and security models. Preliminary experiments provide insightful and prospective results.

In this contemporary world, working on internet is a crucial task owing to the security threats in the network like intrusions, injections etc. To recognize and reduce these system attacks, analysts and academicians have introduced Intrusion Detection Systems (IDSs) with the various standards and applications. There are different types of Intrusion Detection Systems (IDS) arise to solve the attacks in various environments. Though IDS is more powerful, it produces the results on the abnormal behaviours said to be attacks with false positive and false negative rates which leads to inaccurate detection rate. The other problem is that, there are more number of attacks arising simultaneously with different behaviour being detected by the IDS with high false positive rates which spoils the strength and lifetime of the system, system's efficiency and fault tolerance. Complex Event Processing (CEP) plays a vital role in handling the alerts as events in real time environment which mainly helps to recognize and reduce the redundant alerts.CEP identifies and analyses relationships between events in real time, allowing the system to proactively take efficient actions to respond to specific alerts.In this study, the tendency of Complex Event Processing (CEP) over Intrusion Detection System (IDS) which offers effective handling of the alerts received from IDS in real time and the promotion of the better detection of the attacks are discussed. The merits and challenges of CEP over IDS described in this paper helps to understand and educate the IDS systems to focus on how to tackle the dynamic attacks and its alerts in real time.

With the growing number of electronic features in cars and their connections to the cloud, smartphones, road-side equipment, and neighboring cars the need for effective cybersecurity is paramount. Beyond the concern of brand degradation, warranty fraud, and recalls, what keeps manufacturers up at night is the threat of malicious attacks which can affect the safety of vehicles on the road. Would any single protection technique provide the security needed over the long lifetime of a vehicle? We present a new methodology for automotive cybersecurity where the designs are made to withstand attacks in the future based on the concepts of high availability and malicious fault-tolerance through self-defending techniques. When a system has an intrusion, self-defending technologies work to contain the breach using integrity verification, self-healing, and fail-over techniques to keep the system running.

While cyberattacks pose a relatively new challenge for power grid control systems, commercial cloud systems have needed to address similar threats for many years. However, technology and approaches developed for cloud systems do not necessarily transfer directly to the power grid, due to important differences between the two domains. We discuss our experience adapting intrusion-tolerant cloud technologies to the power domain and describe the challenges we have encountered and potential directions for overcoming those obstacles.

Many complex dynamical systems consist of a large number of interacting subsystems that operate harmoniously and make decisions that are designed for the benefit of the entire enterprise. If, in an attempt to disrupt the operation of the entire system, one subsystem gets attacked and is made to operate in a manner that is adversarial with the others, then the entire system suffers, resulting in an adversarial decision-making environment among its subsystems. Such an environment may affect not only the decision-making process of the attacked subsystem but also possibly the other remaining subsystems as well. The disruption caused by the attacked subsystem may cause the remaining subsystems to either coalesce as a unified team making team-based decisions, or disintegrate and act as independent decision-making entities. The decision-making process in these types of complex systems of systems is best analyzed within the general framework of cooperative and non-cooperative game theory. In this paper, we will develop an analysis that provides a theoretical basis for modeling the decision-making process in such complex systems. We show how cooperation among the subsystems can produce Noninferior Nash Strategies (NNS) that are fair and acceptable to all subsystems within the team while at the same time provide the subsystems in the team with the security of the Nash equilibrium against the opposing attacked subsystem. We contrast these strategies with the all Nash Strategies (NS) that would result if the operation of the entire system disintegrated and became adversarial among all subsystems as a result of the attack. An example of a system consisting of three subsystems with one opposing subsystem as a result of an attack is included to illustrate the results.

The motion process of multi-dimensional chaotic system is complex and variable, the randomness of motion state is stronger, and the motion state is more unpredictable within a certain range. This feature of multi-dimensional chaotic system can effectively improve the security performance of digital image encryption algorithm. In this paper, the hyper-chaotic Lorenz map is used to design the encryption sequence to improve the random performance of the encryption sequence, thus optimizing the performance of the digital image encryption algorithm. In this paper, the chaotic sequence is used to randomly select the row vector of the Hadamard matrix to form the Hadamard matrix to determine the measurement matrix, which simplifies the computational difficulty of the algorithm and solves the problem of the discontinuity of the key space in the random matrix design.

With the increase in the number of cyber attacks on industrial control systems, especially in critical infrastructure facilities, the problem of comprehensive analysis of the security of such systems becomes urgent. This, in turn, requires the availability of fundamental mathematical, methodological and instrumental basis for modeling automated systems, modeling attacks on their information resources, which would allow realtime system protection analysis. The paper proposes a basis for simulating protected industrial control systems, based on the developed reference security model, and a model for attacks on information resources of automated systems. On the basis of these mathematical models, a complex model of a protected automated system was developed, which can be used to build protection systems for automated systems used in production.

The authors carry out the analysis of the process of modeling threats to information security of automated process control systems. Basic principles of security threats model formation are considered. The approach to protection of automated process control systems based on the Shtakelberg game in a strategic form was modeled. An abstract mathematical model of information security threats to automated process control systems was developed. A formalized representation of a threat model is described, taking into account an intruder's potential. Presentation of the process of applying the described threat model in the form of a continuous Deming-Shewhart cycle is proposed.