Biblio
ICT systems have become an integral part of business and life. At the same time, these systems have become extremely complex. In such systems exist numerous vulnerabilities waiting to be exploited by potential threat actors. pwnPr3d is a novel modelling approach that performs automated architectural analysis with the objective of measuring the cyber security of the modeled architecture. Its integrated modelling language allows users to model software and hardware components with great level of details. To illustrate this capability, we present in this paper the metamodel of UNIX, operating systems being the core of every software and every IT system. After describing the main UNIX constituents and how they have been modelled, we illustrate how the modelled OS integrates within pwnPr3d's rationale by modelling the spreading of a self-replicating malware inspired by WannaCry.
Internet of Things (IoT) is characterized by heterogeneous devices that interact with each other on a collaborative basis to fulfill a common goal. In this scenario, some of the deployed devices are expected to be constrained in terms of memory usage, power consumption and processing resources. To address the specific properties and constraints of such networks, a complete stack of standardized protocols has been developed, among them the Routing Protocol for Low-Power and lossy networks (RPL). However, this protocol is exposed to a large variety of attacks from the inside of the network itself. To fill this gap, this paper focuses on the design and the integration of a novel Link reliable and Trust aware model into the RPL protocol. Our approach aims to ensure Trust among entities and to provide QoS guarantees during the construction and the maintenance of the network routing topology. Our model targets both node and link Trust and follows a multidimensional approach to enable an accurate Trust value computation for IoT entities. To prove the efficiency of our proposal, this last has been implemented and tested successfully within an IoT environment. Therefore, a set of experiments has been made to show the high accuracy level of our system.
Securing Internet of Things is a challenge because of its multiple points of vulnerability. In particular, Distributed Denial of Service (DDoS) attacks on IoT devices pose a major security challenge to be addressed. In this paper, we propose a DNS query-based DDoS attack mitigation system using Software-Defined Networking (SDN) to block the network traffic for DDoS attacks. With some features provided by SDN, we can analyze traffic patterns and filter suspicious network flows out. To show the feasibility of the proposed system, we particularly implemented a prototype with Dirichlet process mixture model to distinguish benign traffic from malicious traffic and conducted experiments with the dataset collected from real network traces. We demonstrate the effectiveness of the proposed method by both simulations and experiment data obtained from the real network traffic traces.
Software Defined Networking (SDN) has proved to be a promising approach for creating next generation software based network ecosystems. It has provided us with a centralized network provision, a holistic management plane and a well-defined level of abstraction. But, at the same time brings forth new security and management challenges. Research in the field of SDN is primarily focused on reconfiguration, forwarding and network management issues. However in recent times the interest has moved to tackling security and maintenance issues. This work is based on providing a means to mitigate security challenges in an SDN environment from a DDoS attack based point of view. This paper introduces a Multi-Agent based intrusion prevention and mitigation architecture for SDN. Thus allowing networks to govern their behavior and take appropriate measures when the network is under attack. The architecture is evaluated against filter based intrusion prevention architectures to measure efficiency and resilience against DDoS attacks and false policy based attacks.
This paper introduces a hardware Trojan detection method using Chip ID which is generated by Relative Time-Delays (RTD) of sensor chains and the effectiveness of RTD is verified by post-layout simulations. The rank of time-delays of the sensor chains would be changed in Trojan-inserted chip. RTD is an accurate approach targeting to all kinds of Trojans, since it is based on the RELATIVE relationship between the time-delays rather than the absolute values, which are hard to be measured and will change with the fabricate process. RTD needs no golden chip, because the RELATIVE values would not change in most situations. Thus the genuine ID can be generated by simulator. The sensor chains can be inserted into a layout utilizing unused spaces, so RTD is a low-cost solution. A Trojan with 4x minimum NMOS is placed in different places of the chip. The behavior of the chip is obtained by using transient based post-layout simulation. All the Trojans are detected AND located, thus the effectiveness of RTD is verified.
This paper investigates closed-form expressions to evaluate the performance of the Compressive Sensing (CS) based Energy Detector (ED). The conventional way to approximate the probability density function of the ED test statistic invokes the central limit theorem and considers the decision variable as Gaussian. This approach, however, provides good approximation only if the number of samples is large enough. This is not usually the case in CS framework, where the goal is to keep the sample size low. Moreover, working with a reduced number of measurements is of practical interest for general spectrum sensing in cognitive radio applications, where the sensing time should be sufficiently short since any time spent for sensing cannot be used for data transmission on the detected idle channels. In this paper, we make use of low-complexity approximations based on algebraic transformations of the one-dimensional Gaussian Q-function. More precisely, this paper provides new closed-form expressions for accurate evaluation of the CS-based ED performance as a function of the compressive ratio and the Signal-to-Noise Ratio (SNR). Simulation results demonstrate the increased accuracy of the proposed equations compared to existing works.
It is a challenging problem to preserve the friendly-correlations between individuals when publishing social-network data. To alleviate this problem, uncertain graph has been presented recently. The main idea of uncertain graph is converting an original graph into an uncertain form, where the correlations between individuals is an associated probability. However, the existing methods of uncertain graph lack rigorous guarantees of privacy and rely on the assumption of adversary's knowledge. In this paper we first introduced a general model for constructing uncertain graphs. Then, we proposed an algorithm under the model which is based on differential privacy and made an analysis of algorithm's privacy. Our algorithm provides rigorous guarantees of privacy and against the background knowledge attack. Finally, the algorithm we proposed satisfied differential privacy and showed feasibility in the experiments. And then, we compare our algorithm with (k, ε)-obfuscation algorithm in terms of data utility, the importance of nodes for network in our algorithm is similar to (k, ε)-obfuscation algorithm.
This paper aims to address the security challenges on physical unclonable functions (PUFs) raised by modeling attacks and denial of service (DoS) attacks. We develop a hardware isolation-based secure architecture extension, namely PUFSec, to protect the target PUF from security compromises without modifying the internal PUF design. PUFSec achieves the security protection by physically isolating the PUF hardware and data from the attack surfaces accessible by the adversaries. Furthermore, we deploy strictly enforced security policies within PUFSec, which authenticate the incoming PUF challenges and prevent attackers from collecting sufficient PUF responses to issue modeling attacks or interfering with the PUF workflow to launch DoS attacks. We implement our PUFSec framework on a Xilinx SoC equipped with ARM processor. Our experimental results on the real hardware prove the enhanced security and the low performance and power overhead brought by PUFSec.
Trying to solve the risk of data privacy disclosure in classification process, a Random Forest algorithm under differential privacy named DPRF-gini is proposed in the paper. In the process of building decision tree, the algorithm first disturbed the process of feature selection and attribute partition by using exponential mechanism, and then meet the requirement of differential privacy by adding Laplace noise to the leaf node. Compared with the original algorithm, Empirical results show that protection of data privacy is further enhanced while the accuracy of the algorithm is slightly reduced.
This paper proposed a feedback shift register structure which can be split, it is based on a research of operating characteristics about 70 kinds of cryptographic algorithms and the research shows that the “different operations similar structure” reconfigurable design is feasible. Under the configuration information, the proposed structure can implement the multiplication in finite field GF(2n), the multiply/divide linear feedback shift register and other operations. Finally, this paper did a logic synthesis based on 55nm CMOS standard-cell library and the results show that the proposed structure gets a hardware resource saving of nearly 32%, the average power consumption saving of nearly 55% without the critical delay increasing significantly. Therefore, the “different operations similar structure” reconfigurable design is a new design method and the proposed feedback shift register structure can be an important processing unit for coarse-grained reconfigurable cryptologic array.
Reliability and robustness of Internet of Things (IoT)-cloud-based communication is an important issue for prospective development of the IoT concept. In this regard, a robust and unique client-to-cloud communication physical layer is required. Physical Unclonable Function (PUF) is regarded as a suitable physics-based random identification hardware, but suffers from reliability problems. In this paper, we propose novel hardware concepts and furthermore an analysis method in CMOS technology to improve the hardware-based robustness of the generated PUF word from its first point of generation to the last cloud-interfacing point in a client. Moreover, we present a spectral analysis for an inexpensive high-yield implementation in a 65nm generation. We also offer robust monitoring concepts for the PUF-interfacing communication physical layer hardware.
Hardware implementations of cryptographic algorithms may leak information through numerous side channels, which can be used to reveal the secret cryptographic keys, and therefore compromise the security of the algorithm. Power Analysis Attacks (PAAs) [1] exploit the information leakage from the device's power consumption (typically measured on the supply and/or ground pins). Digital circuits consume dynamic switching energy when data propagate through the logic in each new calculation (e.g. new clock cycle). The average power dissipation of a design can be expressed by: Ptot(t) = α · (Pd(t) + Ppvt(t)) (1) where α is the activity factor (the probability that the gate will switch) and depends on the probability distribution of the inputs to the combinatorial logic. This induces a linear relationship between the power and the processed data [2]. Pd is the deterministic power dissipated by the switching of the gate, including any parasitic and intrinsic capacitances, and hence can be evaluated prior to manufacturing. Ppvt is the change in expected power consumption due to nondeterministic parameters such as process variations, mismatch, temperature, etc. In this manuscript, we describe the design of logic gates that induce data-independent (constant) α and Pd.
Security of control systems have become a new and important field of research since malicious attacks on control systems indeed occurred including Stuxnet in 2011 and north eastern electrical grid black out in 2003. Attacks on sensors and/or actuators of control systems cause malfunction, instability, and even system destruction. The impact of attack may differ by which instrumentation (sensors and/or actuators) is being attacked. In particular, for control systems with multiple sensors, attack on each sensor may have different impact, i.e., attack on some sensors leads to a greater damage to the system than those for other sensors. To investigate this, we consider sensor bias injection attacks in linear control systems equipped with anomaly detector, and quantify the maximum impact of attack on sensors while the attack remains undetected. Then, we introduce a notion of sensor security index for linear dynamic systems to quantify the vulnerability under sensor attacks. Method of reducing system vulnerability is also discussed using the notion of sensor security index.
Side-channel collision attacks have been one of the most powerful attack techniques, combining advantages of traditional side-channel attack and mathematical cryptanalysis. In this paper, we propose a novel multiple-bits side-channel collision attack based on double distance voting detection, which can find all 120 relations among 16 key bytes with only 32 averaged power traces when applied to AES (Advanced Encryption Standard) algorithm. Practical attack experiments are performed successfully on a hardware implementation of AES on FPGA board. Results show that the necessary number of traces for our method is about 50% less than correlation-enhanced collision attack and 76% less than binary voting test with 90% success rate.
This paper presents a true random number generator that exploits the subthreshold properties of jitter of events propagating in a self-timed ring and jitter of events propagating in an inverter based ring oscillator. Design was implemented in 180nm CMOS flash process. Devices provide high quality random bit sequences passing FIPS 140-2 and NIST SP 800-22 statistical tests which guaranty uniform distribution and unpredictability thanks to the physics based entropy source.
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.
Security Evaluation and Management (SEM) is considerably important process to protect the Embedded System (ES) from various kinds of security's exploits. In general, SEM's processes have some challenges, which limited its efficiency. Some of these challenges are system-based challenges like the hetero-geneity among system's components and system's size. Some other challenges are expert-based challenges like mis-evaluation possibility and experts non-continuous availability. Many of these challenges were addressed by the Multi Metric (MM) framework, which depends on experts' or subjective evaluation for basic evaluations. Despite of its productivity, subjective evaluation has some drawbacks (e.g. expert misevaluation) foster the need for considering objective evaluations in the MM framework. In addition, the MM framework is system centric framework, thus, by modelling complex and huge system using the MM framework a guide is needed indicating changes toward desirable security's requirements. This paper proposes extensions for the MM framework consider the usage of objective evaluations and work as guide for needed changes to satisfy desirable security requirements.
We have proposed a method of designing embedded clock-cycle-sensitive Hardware Trojans (HTs) to manipulate finite state machine (FSM). By using pipeline to choose and customize critical path, the Trojans can facilitate a series of attack and need no redundant circuits. One cannot detect any malicious architecture through logic analysis because the proposed circuitry is the part of FSM. Furthermore, this kind of HTs alerts the trusted systems designers to the importance of clock tree structure. The attackers may utilize modified clock to bypass certain security model or change the circuit behavior.