Biblio
This paper provides a proof-of-concept demonstration of the potential benefit of using logical implications for detection of combinational hardware trojans. Using logic simulation, valid logic implications are selected and added to to the checker circuitry to detect payload delivery by a combinational hardware trojan. Using combinational circuits from the ISCAS benchmark suite, and a modest hardware budget for the checker, simulation results show that the probability of a trojan escaping detection using our approach was only 16%.
A technique of finding a set of sequential circuit nodes in which Trojan Circuits (TC) may be implanted is suggested. The technique is based on applying the precise (not heuristic) random estimations of internal node observability and controllability. Getting the estimations we at the same time derive and compactly represent all sequential circuit full states (depending on input and state variables) in which of that TC may be switched on. It means we obtain precise description of TC switch on area for the corresponding internal node v. The estimations are computed with applying a State Transition Graph (STG) description, if we suppose that TC may be inserted out of the working area (out of the specification) of the sequential circuit. Reduced Ordered Binary Decision Diagrams (ROBDDs) for the combinational part and its fragments are applied for getting the estimations by means of operations on ROBDDs. Techniques of masking TCs are proposed. Masking sub-circuits overhead is appreciated.
Rapid advancement in wearable technology has unlocked a tremendous potential of its applications in the medical domain. Among the challenges in making the technology more useful for medical purposes is the lack of confidence in the data thus generated and communicated. Incentives have led to attacks on such systems. We propose a novel lightweight scheme to securely log the data from bodyworn sensing devices by utilizing neighboring devices as witnesses who store the fingerprints of data in Bloom filters to be later used for forensics. Medical data from each sensor is stored at various locations of the system in chronological epoch-level blocks chained together, similar to the blockchain. Besides secure logging, the scheme offers to secure other contextual information such as localization and timestamping. We prove the effectiveness of the scheme through experimental results. We define performance parameters of our scheme and quantify their cost benefit trade-offs through simulation.
Internet of Thing (IoT) provide services by linking the different platform devices. They have the limitation in providing intelligent service. The IoT devices are heterogeneous which includes wireless sensors to less resource constrained devices. These devices are prone to hardware/software and network attacks. If not properly secured, it may lead to security issues like privacy and confidentiality. To resolve the above problem, an Intelligent Security Framework for IoT Devices is proposed in this paper. The proposed method is made up of (1) the light weight Asymmetric cryptography for securing the End-To-End devices which protects the IoT service gateway and the low power sensor nodes and (2) implements Lattice-based cryptography for securing the Broker devices/Gateway and the cloud services. The proposed architecture implements Asymmetric Key Encryption to share session key between the nodes and then uses this session key for message transfer This protects the system from Distributed Denial of Service Attacks, eavesdropping and Quantum algorithm attacks. The proposed protocol uses the unique Device ID of the sensors to generate key pair to establish mutual authentication between Devices and Services. Finally, the Mutual authentication mechanism is implemented in the gateway.
Deep web, a hidden and encrypted network that crawls beneath the surface web today has become a social hub for various criminals who carry out their crime through the cyber space and all the crime is being conducted and hosted on the Deep Web. This research paper is an effort to bring forth various techniques and ways in which an internet user can be safe online and protect his privacy through anonymity. Understanding how user's data and private information is phished and what are the risks of sharing personal information on social media.
Recently, cellular operators have started migrating to IPv6 in response to the increasing demand for IP addresses. With the introduction of IPv6, cellular middleboxes, such as firewalls for preventing malicious traffic from the Internet and stateful NAT64 boxes for providing backward compatibility with legacy IPv4 services, have become crucial to maintain stability of cellular networks. This paper presents security problems of the currently deployed IPv6 middleboxes of five major operators. To this end, we first investigate several key features of the current IPv6 deployment that can harm the safety of a cellular network as well as its customers. These features combined with the currently deployed IPv6 middlebox allow an adversary to launch six different attacks. First, firewalls in IPv6 cellular networks fail to block incoming packets properly. Thus, an adversary could fingerprint cellular devices with scanning, and further, she could launch denial-of-service or over-billing attacks. Second, vulnerabilities in the stateful NAT64 box, a middlebox that maps an IPv6 address to an IPv4 address (and vice versa), allow an adversary to launch three different attacks: 1) NAT overflow attack that allows an adversary to overflow the NAT resources, 2) NAT wiping attack that removes active NAT mappings by exploiting the lack of TCP sequence number verification of firewalls, and 3) NAT bricking attack that targets services adopting IP-based blacklisting by preventing the shared external IPv4 address from accessing the service. We confirmed the feasibility of these attacks with an empirical analysis. We also propose effective countermeasures for each attack.
The Department of Homeland Security Cyber Security Division (CSD) chose Moving Target Defense as one of the fourteen primary Technical Topic Areas pertinent to securing federal networks and the larger Internet. Moving Target Defense over IPv6 (MT6D) employs an obscuration technique offering keyed access to hosts at a network level without altering existing network infrastructure. This is accomplished through cryptographic dynamic addressing, whereby a new network address is bound to an interface every few seconds in a coordinated manner. The goal of this research is to produce a Register Transfer Level (RTL) network security processor implementation to enable the production of an Application Specific Integrated Circuit (ASIC) variant of MT6D processor for wide deployment. RTL development is challenging in that it must provide system level functions that are normally provided by the Operating System's kernel and supported libraries. This paper presents the architectural design of a hardware engine for MT6D (HE-MT6D) and is complete in simulation. Unique contributions are an inline stream-based network packet processor with a Complex Instruction Set Computer (CISC) architecture, Network Time Protocol listener, and theoretical increased performance over previous software implementations.
The article issue is the enterprise information protection within the internet of things concept. The aim of research is to develop arrangements set to ensure secure enterprise IPv6 network operating. The object of research is the enterprise IPv6 network. The subject of research is modern switching equipment as a tool to ensure network protection. The research task is to prioritize functioning of switches in production and corporation enterprise networks, to develop a network host protection algorithm, to test the developed algorithm on the Cisco Packet Tracer 7 software emulator. The result of research is the proposed approach to IPv6-network security based on analysis of modern switches functionality, developed and tested enterprise network host protection algorithm under IPv6-protocol with an automated network SLAAC-configuration control, a set of arrangements for resisting default enterprise gateway attacks, using ACL, VLAN, SEND, RA Guard security technology, which allows creating sufficiently high level of networks security.
RPL is a lightweight IPv6 network routing protocol specifically designed by IETF, which can make full use of the energy of intelligent devices and compute the resource to build the flexible topological structure. This paper analyzes the security problems of RPL, sets up a test network to test RPL network security, proposes a RPL based security routing protocol M-RPL. The routing protocol establishes a hierarchical clustering network topology, the intelligent device of the network establishes the backup path in different clusters during the route discovery phase, enable backup paths to ensure data routing when a network is compromised. Setting up a test prototype network, simulating some attacks against the routing protocols in the network. The test results show that the M-RPL network can effectively resist the routing attacks. M-RPL provides a solution to ensure the Internet of Things (IoT) security.
In Germany, as of 2017, a new smart metering infrastructure based on high security and privacy requirements will be deployed. It provides interfaces to connect meters for different commodities, to allow end users to retrieve the collected measurement data, to connect to the metering operators, and to connect Controllable Local Systems (CLSs) that establish a TLS secured connection to third parties in order to exchange data or for remote controlling of energy devices. This paper aims to connect industrial machines as CLS devices since it shows that the demands and main ideas of remotely controlled devices in the Smart Grid context and Industrial Cloud Applications match on the communication level. It describes the general architecture of the Smart Metering infrastructure in Germany, introduces the defined roles, depicts the configuration process on the different organizational levels, demonstrates the connection establishment and the initiating partners, concludes on the potential industrial use cases of this infrastructure, and provides open questions and room for further research.
This research in progress paper describes the role of cyber security measures undertaken in an ICT system for integrating electric storage technologies into the grid. To do so, it defines security requirements for a communications gateway and gives detailed information and hands-on configuration advice on node and communication line security, data storage, coping with backend M2M communications protocols and examines privacy issues. The presented research paves the road for developing secure smart energy communications devices that allow enhancing energy efficiency. The described measures are implemented in an actual gateway device within the HORIZON 2020 project STORY, which aims at developing new ways to use storage and demonstrating these on six different demonstration sites.
Security of sensible data for ultraconstrained IoT smart devices is one of the most challenging task in modern design. The needs of CPA-resistant cryptographic devices has to deal with the demanding requirements of small area and small impact on the overall power consumption. In this work, a novel current-mode feedback suppressor as on-chip analog-level CPA countermeasure is proposed. It aims to suppress differences in power consumption due to data-dependency of CMOS cryptographic devices, in order to counteract CPA attacks. The novel countermeasure is able to improve MTD of unprotected CMOS implementation of at least three orders of magnitude, providing a ×1.1 area and ×1.7 power overhead.
When supporting commercial or defense systems, a perennial challenge is providing effective test and diagnosis strategies to minimize downtime, thereby maximizing system availability. Potentially one of the most effective ways to maximize downtime is to be able to detect and isolate as many faults in a system at one time as possible. This is referred to as the "multiple-fault diagnosis" problem. While several tools have been developed over the years to assist in performing multiple-fault diagnosis, considerable work remains to provide the best diagnosis possible. Recently, a new model for evolutionary computation has been developed called the "Factored Evolutionary Algorithm" (FEA). In this paper, we combine our prior work in deriving diagnostic Bayesian networks from static fault isolation manuals and fault trees with the FEA strategy to perform abductive inference as a way of addressing the multiple-fault diagnosis problem. We demonstrate the effectiveness of this approach on several networks derived from existing, real-world FIMs.
Supervisory control and data acquisition (SCADA) systems are the key driver for critical infrastructures and industrial facilities. Cyber-attacks to SCADA networks may cause equipment damage or even fatalities. Identifying risks in SCADA networks is critical to ensuring the normal operation of these industrial systems. In this paper we propose a Bayesian network-based cyber-security risk assessment model to dynamically and quantitatively assess the security risk level in SCADA networks. The major distinction of our work is that the proposed risk assessment method can learn model parameters from historical data and then improve assessment accuracy by incrementally learning from online observations. Furthermore, our method is able to assess the risk caused by unknown attacks. The simulation results demonstrate that the proposed approach is effective for SCADA security risk assessment.
Advances in nanotechnology, large scale computing and communications infrastructure, coupled with recent progress in big data analytics, have enabled linking several billion devices to the Internet. These devices provide unprecedented automation, cognitive capabilities, and situational awareness. This new ecosystem–termed as the Internet-of-Things (IoT)–also provides many entry points into the network through the gadgets that connect to the Internet, making security of IoT systems a complex problem. In this position paper, we argue that in order to build a safer IoT system, we need a radically new approach to security. We propose a new security framework that draws ideas from software defined networks (SDN), and data analytics techniques; this framework provides dynamic policy enforcements on every layer of the protocol stack and can adapt quickly to a diverse set of industry use-cases that IoT deployments cater to. Our proposal does not make any assumptions on the capabilities of the devices - it can work with already deployed as well as new types of devices, while also conforming to a service-centric architecture. Even though our focus is on industrial IoT systems, the ideas presented here are applicable to IoT used in a wide array of applications. The goal of this position paper is to initiate a dialogue among standardization bodies and security experts to help raise awareness about network-centric approaches to IoT security.
Building lightweight security for low-cost pervasive devices is a major challenge considering the design requirements of a small footprint and low power consumption. Physical Unclonable Functions (PUFs) have emerged as a promising technology to provide a low-cost authentication for such devices. By exploiting intrinsic manufacturing process variations, PUFs are able to generate unique and apparently random chip identifiers. Strong-PUFs represent a variant of PUFs that have been suggested for lightweight authentication applications. Unfortunately, many of the Strong-PUFs have been shown to be susceptible to modelling attacks (i.e., using machine learning techniques) in which an adversary has access to challenge and response pairs. In this study, we propose an obfuscation technique during post-processing of Strong-PUF responses to increase the resilience against machine learning attacks. We conduct machine learning experiments using Support Vector Machines and Artificial Neural Networks on two Strong-PUFs: a 32-bit Arbiter-PUF and a 2-XOR 32-bit Arbiter-PUF. The predictability of the 32-bit Arbiter-PUF is reduced to $\approx$ 70% by using an obfuscation technique. Combining the obfuscation technique with 2-XOR 32-bit Arbiter-PUF helps to reduce the predictability to $\approx$ 64%. More reduction in predictability has been observed in an XOR Arbiter-PUF because this PUF architecture has a good uniformity. The area overhead with an obfuscation technique consumes only 788 and 1080 gate equivalents for the 32-bit Arbiter-PUF and 2-XOR 32-bit Arbiter-PUF, respectively.
The data accessibility anytime and anywhere is nowadays the key feature for information technology enabled by the ubiquitous network system for huge applications. However, security and privacy are perceived as primary obstacles to its wide adoption when it is applied to the end user application. When sharing sensitive information, personal s' data protection is the paramount requirement for the security and privacy to ensure the trustworthiness of the service provider. To this end, this paper proposes communication security protocol to achieve data protection when a user is sending his sensitive data to the network through gateway. We design a cipher content and key exchange computation process. Finally, the performance analysis of the proposed scheme ensure the honesty of the gateway service provider, since the user has the ability to control who has access to his data by issuing a cryptographic access credential to data users.
There is a long-standing need for improved cybersecurity through automation of attack signature detection, classification, and response. In this paper, we present experimental test bed results from an implementation of autonomic control plane feedback based on the Observe, Orient, Decide, Act (OODA) framework. This test bed modeled the building blocks for a proposed zero trust cloud data center network. We present test results of trials in which identity management with automated threat response and packet-based authentication were combined with dynamic management of eight distinct network trust levels. The log parsing and orchestration software we created work alongside open source log management tools to coordinate and integrate threat response from firewalls, authentication gateways, and other network devices. Threat response times are measured and shown to be a significant improvement over conventional methods.
This paper introduces a multi-factors security key generation mechanism for self-organising Internet of Things (IoT) network and nodes. The mechanism enables users to generate unique set of security keys to enhance IoT security while meeting various business needs. The multi-factor security keys presents an additional security layer to existing security standards and practices currently being adopted by the IoT community. The proposed security key generation mechanism enables user to define and choose any physical and logical parameters he/she prefers, in generating a set of security keys to be encrypted and distributed to registered IoT nodes. IoT applications and services will only be activated after verifying that all security keys are present. Multiple levels of authorisation for different user groups can be easily created through the mix and match of the generated multi-factors security keys. A use case, covering indoor and outdoor field tests was conducted. The results of the tests showed that the mechanism is easily adaptable to meet diverse multivendor IoT devices and is scalable for various applications.
We propose secure RAID, i.e., low-complexity schemes to store information in a distributed manner that is resilient to node failures and resistant to node eavesdropping. We generalize the concept of systematic encoding to secure RAID and show that systematic schemes have significant advantages in the efficiencies of encoding, decoding and random access. For the practical high rate regime, we construct three XOR-based systematic secure RAID schemes with optimal encoding and decoding complexities, from the EVENODD codes and B codes, which are array codes widely used in the RAID architecture. These schemes optimally tolerate two node failures and two eavesdropping nodes. For more general parameters, we construct efficient systematic secure RAID schemes from Reed-Solomon codes. Our results suggest that building “keyless”, information-theoretic security into the RAID architecture is practical.
Cloud computing is significantly reshaping the computing industry built around core concepts such as virtualization, processing power, connectivity and elasticity to store and share IT resources via a broad network. It has emerged as the key technology that unleashes the potency of Big Data, Internet of Things, Mobile and Web Applications, and other related technologies; but it also comes with its challenges - such as governance, security, and privacy. This paper is focused on the security and privacy challenges of cloud computing with specific reference to user authentication and access management for cloud SaaS applications. The suggested model uses a framework that harnesses the stateless and secure nature of JWT for client authentication and session management. Furthermore, authorized access to protected cloud SaaS resources have been efficiently managed. Accordingly, a Policy Match Gate (PMG) component and a Policy Activity Monitor (PAM) component have been introduced. In addition, other subcomponents such as a Policy Validation Unit (PVU) and a Policy Proxy DB (PPDB) have also been established for optimized service delivery. A theoretical analysis of the proposed model portrays a system that is secure, lightweight and highly scalable for improved cloud resource security and management.
Reversible circuits are vulnerable to intellectual property and integrated circuit piracy. To show these vulnerabilities, a detailed understanding on how to identify the function embedded in a reversible circuit is crucial. To obtain the embedded function, one needs to know the synthesis approach used to generate the reversible circuit in the first place. We present a machine learning based scheme to identify the synthesis approach using telltale signs in the design.
Scan-based test is commonly used to increase testability and fault coverage, however, it is also known to be a liability for chip security. Research has shown that intellectual property (IP) or secret keys can be leaked through scan-based attacks. In this paper, we propose a dynamically-obfuscated scan design for protecting IPs against scan-based attacks. By perturbing all test patterns/responses and protecting the obfuscation key, the proposed architecture is proven to be robust against existing non-invasive scan attacks, and can protect all scan data from attackers in foundry, assembly, and system developers (i.e., OEMs) without compromising the testability. Furthermore, the proposed architecture can be easily plugged into EDA generated scan chains without having a noticeable impact on conventional integrated circuit (IC) design, manufacturing, and test flow. Finally, detailed security and experimental analyses have been performed on several benchmarks. The results demonstrate that the proposed method can protect chips from existing brute force, differential, and other scan-based attacks that target the obfuscation key. The proposed design is of low overhead on area, power consumption, and pattern generation time, and there is no impact on test time.
The Internet of Things is a disruptive paradigm based on the cooperation of a plethora of heterogeneous smart things to collect, transmit, and analyze data from the ambient environment. To this end, many monitored variables are combined by a data analysis module in order to implement efficient context-aware decision mechanisms. To ensure resource efficiency, aggregation is a long established solution, however it is applicable only in the case of one sensed variable. We extend the use of aggregation to the complex context of IoT by proposing a novel approach for secure cooperation of smart things while granting confidentiality and integrity. Traditional solutions for data concealment in resource constrained devices rely on hop-by-hop or end-to-end encryption, which are shown to be inefficient in our context. We use a more sophisticated scheme relying on homomorphic encryption which is not compromise resilient. We combine fully additive encryption with fully additive secret sharing to fulfill the required properties. Thorough security analysis and performance evaluation show a viable tradeoff between security and efficiency for our scheme.