Biblio

This paper introduces a new methodology to generate additional hardware security in commercial off-the-shelf (COTS) system-on-a-chip (SoC) integrated circuits (ICs) that have already been fabricated and packaged. On-chip analog hardware blocks such as analog to digital converters (ADCs), digital to analog converters (DACs) and comparators residing within an SoC are repurposed and connected to one another to generate unique physically unclonable function (PUF) responses. The PUF responses are digitized and processed on-chip to create keys for use in encryption and device authentication activities. Key generation and processing algorithms are presented that minimize the effects of voltage and temperature fluctuations to maximize the repeatability of a key within a device. Experimental results utilizing multiple on-chip analog blocks inside a common COTS microcontroller show reliable key generation with minimal overhead.

With the continuously development of smart meter-reading technologies for decades, remote information collection of electricity, water, gas and heat meters have been realized. Due to the difference of electrical interfaces and communication protocols among various types of meters, communication modes of meter terminals are not so compatible, it is difficult to realize communication optimization of electricity, water, gas and heat meters information collection services. In addition, with the development of power consumption information acquisition system, the number of acquisition terminals soars greatly and the data of terminal access is highly concurrent. Therefore, the risk of security access is increasing. This paper presents a light-weighted security access scheme of power line communication based on multi-source data acquisition of electricity, water, gas and heat meters, which separates multi-source data acquisition services and achieve services security isolation and channel security isolation. The communication reliability and security of the meter-reading service of "electricity, water, gas and heat" will be improved and the integrated meter service will be realized reliably.

The communication security issue is of great importance and should not be ignored in backbone optical networks which is undergoing the evolution toward software defined networks (SDN). With the aim to solve this problem, this paper conducts deep analysis into the security challenge of software defined optical networks (SDON) and proposes a so-called security-enhanced signaling scheme of SDON. The proposed scheme makes full advantage of current OpenFIow protocol with some necessary extensions and security improvement, by combining digital signatures and message feedback with efficient PKI (Public Key Infrastructure) in signaling procedure of OpenFIow interaction. Thus, this security-enhanced signaling procedure is also designed in details to make sure the end-to-end trusted service connection. Simulation results show that this proposed approach can greatly improve the security level of large-scale optical network for Energy Internet services with better performance in term of connection success rate performance.

Industry 4.0 is based on the CPS architecture since it is the next generation in the industry. The CPS architecture is a system based on Cloud Computing technology and Internet of Things where computer elements collaborate for the control of physical entities. The security framework in this architecture is necessary for the protection of two parts (physical and information) so basically, security in CPS is classified into two main parts: information security (data) and security of control. In this work, we propose two models to solve the two problems detected in the security framework. The first proposal SCCAF (Smart Cloud Computing Adoption Framework) treats the nature of information that serves for the detection and the blocking of the threats our basic architecture CPS. The second model is a modeled detector related to the physical nature for detecting node information.

The evolution of the microelectronics manufacturing industry is characterized by increased complexity, analysis, integration, distribution, data sharing and collaboration, all of which is enabled by the big data explosion. This evolution affords a number of opportunities in improved productivity and quality, and reduced cost, however it also brings with it a number of risks associated with maintaining security of data systems. The International Roadmap for Devices and System Factory Integration International Focus Team (IRDS FI IFT) determined that a security technology roadmap for the industry is needed to better understand the needs, challenges and potential solutions for security in the microelectronics industry and its supply chain. As a first step in providing this roadmap, the IFT conducted a security survey, soliciting input from users, suppliers and OEMs. Preliminary results indicate that data partitioning with IP protection is the number one topic of concern, with the need for industry-wide standards as the second most important topic. Further, the "fear" of security breach is considered to be a significant hindrance to Advanced Process Control efforts as well as use of cloud-based solutions. The IRDS FI IFT will endeavor to provide components of a security roadmap for the industry in the 2018 FI chapter, leveraging the output of the survey effort combined with follow-up discussions with users and consultations with experts.

In Mobile Ad hoc Networks (MANET) the nodes act as a host as well as a router thereby forming a self-organizing network that does not rely upon fixed infrastructure, other than gateways to other networks. MANET provides a quick to deploy flexible networking capability with a dynamic topology due to node mobility. MANET nodes transmit, relay and receive traffic from neighbor nodes as the network topology changes. Security is important for MANET and trust computation is used to improve collaboration between nodes. MANET trust frameworks utilize real-time trust computations to maintain the trust state for nodes in the network. If the trust computation is not resilient against attack, the trust values computed could be unreliable. This paper proposes an Artificial Immune System based approach to compute trust and thereby provide a resilient reputation mechanism.

This paper presents a contemporary review of communication architectures and topographies for MANET-connected Internet-of-Things (IoT) systems. Routing protocols for multi-hop MANETs are analyzed with a focus on the standardized Routing Protocol for Low-power and Lossy Networks. Various security threats and vulnerabilities in current MANET routing are described and security enhanced routing protocols and trust models presented as methodologies for supporting secure routing. Finally, the paper identifies some key research challenges in the emerging domain of MANET-IoT connectivity.

There are two types of network architectures are presents those are wired network and wireless network. MANETs is one of the examples of wireless network. Each and every network has their own features which make them different from other types of network. Some of the features of MANETs are; infrastructure less network, mobility, dynamic network topology which make it different and more popular from wired network but these features also generate different problems for achieving security due to the absence of centralized authority inside network as well as sending of data due to its mobility features. Achieving security in wired network is little-bit easy compare to MANETs because in wired network user need to just protect main centralized authority for achieving security whereas in MANETs there is no centralized authority available so protecting server in MANETs is difficult compare to wired network. Data sending and receiving process is also easy in wired network but mobility features makes this data sending and receiving process difficult in MANETs. Protecting server or central repository without making use of secrete sharing in wired network will create so many challenges and problem in terms of security. The proposed system makes use of Secrete sharing method to protect server from malicious nodes and `A New particle Swarm Optimization Method for MANETs' (NPSOM) for performing data sending and receiving operation in optimization way. NPSOM technique get equated with the steady particle swarm optimizer (PSO) technique. PSO was essentially designed by Kennedy, Eberhart in 1995. These methods are based upon 4 dissimilar types of parameters. These techniques were encouraged by common performance of animals, some of them are bird assembling and fish tuition, ant colony. The proposed system converts this PSO in the form of MANETs where Particle is nothing but the nodes in the network, Swarm means collection of multiple nodes and Optimization means finding the best and nearer root to reach to destination. Each and every element study about their own previous best solution which they are having with them for the given optimization problem, likewise they see for the groups previous best solution which they got for the same problem and finally they correct its solution depending on these values. This same process gets repeated for finding of the best and optimal solutions value. NPSOM technique, used in proposed system there every element changes its location according to the solution which they got previously and which is poorest as well as their collection's earlier poorest solution for finding best, optimal value. In this proposed system we are concentrating on, sidestepping element's and collections poorest solution which they got before.

Due to the changing nature of Mobile Ad-Hoc Network (MANET) security is an important concern and hence in this paper, we carryout vector-based trust mechanism, which is established on the behavior of nodes in forwarding and dropping the data packets determines the trust on each node and we are using the Enhanced Certificate Revocation scheme (ECR), which avoid the attacker by blacklisting the blackhole attacker. To enhance more security for node and network, we assign a unique key for every individual node which can avoid most of the attacks in MANET

Mobile Ad hoc Network (MANET for short) is a new art of wireless technology that connect a group of mobile nodes in a dynamically decentralized fashion without the need of a base station, or a centralized administration, whereas each mobile node can work as a router. MANET topology changes frequently, because of the MANET dynamically formation nature, and freely to move randomly. MANET can function as standalone or can be connected to external networks. Mobile nodes are characterized with minimal human interaction, weight, less memory, and power. Despite all the pros of MANET and the widely spreading in many and critical industries, MANET has some cons and suffers from severe security issues. In this survey we emphasize on the different types of attacks at MANET protocol stack, and show how MANET is vulnerable to those attacks.

Conventional SDN-based MTD techniques have been mainly developed with a single SDN controller which exposes a single point of failure as well as raises a scalability issue for large-scale networks in achieving both security and performance. The use of multiple SDN controllers has been proposed to ensure both performance and security of SDN-based MTD systems for large-scale networks; however, the effect of using multiple SDN controllers has not been investigated in the state-of-the-art research. In this paper, we propose the SDN based MTD architecture using multiple SDN controllers and validate their security effect (i.e., attack success probability) by implementing an IP shuffling MTD in a testbed using ONOS SDN controllers.

The imbalance relationship between FPGA hardware/software providers and FPGA users challenges the assurance of secure design on FPGAs. Existing efforts on FPGA security primarily focus on reverse engineering the downloaded FPGA configuration, retrieving the authentication code or crypto key stored on the embedded memory in FPGAs, and countermeasures for the security threats above. In this work, we investigate new security threats from malicious FPGA tools, and identify stealthy attacks that could occur during FPGA deployment. To address those attacks, we exploit the principles of moving target defense (MTD) and propose a FPGA-oriented MTD (FOMTD) method. Our method is composed of three defense lines, which are formed by an improved user constraint file, random selection of design replicas, and runtime submodule assembling, respectively. The FPGA emulation results show that the proposed FOMTD method reduces the hardware Trojan hit rate by 60% over the baseline, at the cost of 10.76% more power consumption.

Software-defined networking (SDN) is a recently developed approach to computer networking that brings a centralized orientation to network control, thereby improving network architecture and management. However, as with any communication environment that involves message transmission among users, SDN is confronted by the ongoing challenge of protecting user privacy. In this “Work in Progress (WIP)” research, we propose an SDN security model that applies the moving target defense (MTD) technique to protect communication links from sensitive data leakages. MTD is a security solution aimed at increasing complexity and uncertainty for attackers by concealing sensitive information that may serve as a gateway from which to launch different types of attacks. The proposed MTD-based security model is intended to protect user identities contained in transmitted messages in a way that prevents network intruders from identifying the real identities of senders and receivers. According to the results from preliminary experiments, the proposed MTD model has potential to protect the identities contained in transmitted messages within communication links. This work will be extended to protect sensitive data if an attacker gets access to the network device.

Moving Target Defense (MTD) is a research hotspot in the field of network security. Moving Target Network Defense (MTND) is the implementation of MTD at network level. Numerous related works have been proposed in the field of MTND. In this paper, we focus on the scope and area of MTND, systematically present the recent representative progress from four aspects, including IP address and port mutation, route mutation, fingerprint mutation and multiple mutation, and put forward the future development directions. Several new perspectives and elucidations on MTND are rendered.

This paper presents a control strategy for Cyber-Physical System defense developed in the framework of the European Project ATENA, that concerns Critical Infrastructure (CI) protection. The aim of the controller is to find the optimal security configuration, in terms of countermeasures to implement, in order to address the system vulnerabilities. The attack/defense problem is modeled as a multi-agent general sum game, where the aim of the defender is to prevent the most damage possible by finding an optimal trade-off between prevention actions and their costs. The problem is solved utilizing Reinforcement Learning and simulation results provide a proof of the proposed concept, showing how the defender of the protected CI is able to minimize the damage caused by his her opponents by finding the Nash equilibrium of the game in the zero-sum variant, and, in a more general scenario, by driving the attacker in the position where the damage she/he can cause to the infrastructure is lower than the cost it has to sustain to enforce her/his attack strategy.

Problem: Today, many methods of influencing on personnel in the communication process are available to social engineers and information security specialists, but in practice it is difficult to say which method and why it is appropriate to use one. Criteria and indicators of effective communication are not formalized. Purpose: to formalize the concept of effective communication, to offer a tool for combining existing methods and means of communication, to formalize the purpose of communication. Methods: Use of the terminal model of a control system for a non-stochastic communication object. Results. Two examples demonstrating the possibility of using the terminal model of the communication control system, which allows you to connect tools and methods of communication, justify the requirements for the structure and feedback of communication, select the necessary communication algorithms depending on the observed response of the communication object. Practical significance: the results of the research can be used in planning and conducting effective communication in the process of information protection, in business, in private relationships and in other areas of human activity.

Modern operating systems, such as iOS, use multiple access control policies to define an overall protection system. However, the complexity of these policies and their interactions can hide policy flaws that compromise the security of the protection system. We propose iOracle, a framework that logically models the iOS protection system such that queries can be made to automatically detect policy flaws. iOracle models policies and runtime context extracted from iOS firmware images, developer resources, and jailbroken devices, and iOracle significantly reduces the complexity of queries by modeling policy semantics. We evaluate iOracle by using it to successfully triage executables likely to have policy flaws and comparing our results to the executables exploited in four recent jailbreaks. When applied to iOS 10, iOracle identifies previously unknown policy flaws that allow attackers to modify or bypass access control policies. For compromised system processes, consequences of these policy flaws include sandbox escapes (with respect to read/write file access) and changing the ownership of arbitrary files. By automating the evaluation of iOS access control policies, iOracle provides a practical approach to hardening iOS security by identifying policy flaws before they are exploited.

For the occurrence of network attacks, the most important thing for network security managers is how to conduct attack security defenses under low-risk control. And in the attack risk control, the first and most important step is to choose the defense node of risk control. In this paper, aiming to solve the problem of network attack security risk control under complex networks, we propose a game attack risk control node selection method based on game theory. The method utilizes the relationship between the vulnerabilities and analyzes the vulnerability intent information of the complex network to construct an attack risk diffusion network. In order to truly reflect the different meanings of each node in the attack risk diffusion network for attack and defense, this paper uses the host vulnerability attack and defense income evaluation calculation to give each node in the network its offensive and defensive income. According to the above-mentioned attack risk spread network of offensive and defensive gains, this paper combines game theory and maximum benefit ideas to select the best Top defense node information. In this paper, The method proposed in this paper can be used to select network security risk control nodes on complex networks, which can help network security managers to play a good auxiliary role in cyber attack defense.

Connected and automated vehicles aim to improve the comfort and the safety of the driver and passengers. To this end, car manufacturers continually improve actual standardized methods to ensure their customers safety, privacy, and vehicles security. However, these methods do not support fully autonomous vehicles, linkability and confusion threats. To address such gaps, we propose a systematic threat analysis and risk assessment framework, SARA, which comprises an improved threat model, a new attack method/asset map, the involvement of the attacker in the attack tree, and a new driving system observation metric. Finally, we demonstrate its feasibility in assessing risk with two use cases: Vehicle Tracking and Comfortable Emergency Brake Failure.

This paper presents HyperFlow, a processor that enforces secure information flow, including control over timing channels. The design and implementation of HyperFlow offer security assurance because it is implemented using a security-typed hardware description language that enforces secure information flow. Unlike prior processors that aim to enforce simple information-flow policies such as noninterference, HyperFlow allows complex information flow policies that can be configured at run time. Its fine-grained, decentralized information flow mechanisms allow controlled communication among mutually distrusting processes and system calls into different security domains. We address the significant challenges in designing such a processor architecture with contributions in both the hardware architecture and the security type system. The paper discusses the architecture decisions that make the processor secure and describes ChiselFlow, a new secure hardware description language supporting lightweight information-flow enforcement. The HyperFlow architecture is prototyped on a full-featured processor that offers a complete RISC-V instruction set, and is shown to add moderate overhead to area and performance.

Security-sensitive workflows impose constraints on the control-flow and authorization policies that may lead to unsatisfiable instances. In these cases, it is still possible to find "least bad" executions where costs associated to authorization violations are minimized, solving the so-called Multi-Objective Workflow Satisfiability Problem (MO-WSP). The MO-WSP is inspired by the Valued WSP and its generalization, the Bi-Objective WSP, but our work considers quantitative solutions to the WSP without abstracting control-flow constraints. In this paper, we define variations of the MO-WSP and solve them using bounded model checking and optimization modulo theories solving. We validate our solutions on real-world workflows and show their scalability on synthetic instances.

Todays analyzing web weaknesses and vulnerabilities in order to find security attacks has become more urgent. In case there is a communication contrary to the system security policies, a covert channel has been created. The attacker can easily disclosure information from the victim's system with just one public access permission. Covert timing channels, unlike covert storage channels, do not have memory storage and they draw less attention. Different methods have been proposed for their identification, which generally benefit from the shape of traffic and the channel's regularity. In this article, an entropy-based detection method is designed and implemented. The attacker can adjust the amount of channel entropy by controlling measures such as changing the channel's level or creating noise on the channel to protect from the analyst's detection. As a result, the entropy threshold is not always constant for detection. By comparing the entropy from different levels of the channel and the analyst, we conclude that the analyst must investigate traffic at all possible levels.

Information security has become a growing concern. Computer covert channel which is regarded as an important area of information security research gets more attention. In order to detect these covert channels, a variety of detection algorithms are proposed in the course of the research. The algorithms of machine learning type show better results in these detection algorithms. However, the common machine learning algorithms have many problems in the testing process and have great limitations. Based on the deep learning algorithm, this paper proposes a new idea of network covert channel detection and forms a new detection model. On the one hand, this algorithmic model can detect more complex covert channels and, on the other hand, greatly improve the accuracy of detection due to the use of a new deep learning model. By optimizing this test model, we can get better results on the evaluation index.

A covert channel is a communication channel that is subjugated for illegal flow of information in a way that violates system security policies. It is a dangerous, invisible, undetectable, and developed security attack. Recently, Packet length covert channel has motivated many researchers as it is a one of the most undetectable network covert channels. Packet length covert channel generates a covert traffic that is very similar to normal terrific which complicates the detection of such type of covert channels. This motivates us to introduce a machine learning based detection scheme. Recently, a machine learning approach has proved its capability in many different fields especially in security field as it usually brings up a reliable and realistic results. Based in our developed content and frequency-based features, the developed detection scheme has been fully trained and tested. Our detection scheme has gained an excellent degree of detection accuracy which reaches 98% (zero false negative rate and 0.02 false positive rate).

We propose a novel cross-stack sensor framework for realizing lightweight, context-aware, high-interaction network and endpoint deceptions for attacker disinformation, misdirection, monitoring, and analysis. In contrast to perimeter-based honeypots, the proposed method arms production workloads with deceptive attack-response capabilities via injection of booby-traps at the network, endpoint, operating system, and application layers. This provides defenders with new, potent tools for more effectively harvesting rich cyber-threat data from the myriad of attacks launched by adversaries whose identities and methodologies can be better discerned through direct engagement rather than purely passive observations of probe attempts. Our research provides new tactical deception capabilities for cyber operations, including new visibility into both enterprise and national interest networks, while equipping applications and endpoints with attack awareness and active mitigation capabilities.