scholarly journals Towards Automated Detection of Higher-Order Command Injection Vulnerabilities in IoT Devices

2021 ◽  
Vol 13 (6) ◽  
pp. 1-14
Author(s):  
Lei Yu ◽  
Haoyu Wang ◽  
Linyu Li ◽  
Houhua He

Command injection vulnerabilities are among the most common and dangerous attack vectors in IoT devices. Current detection approaches can detect single-step injection vulnerabilities well by fuzzing tests. However, an attacker could inject malicious commands in an IoT device via a multi-step exploit if he first abuses an interface to store the injection payload and later use it in a command interpreter through another interface. We identify a large class of such multi-step injection attacks to address these stealthy and harmful threats and define them as higher-order command injection vulnerabilities (HOCIVs). We develop an automatic system named Request Linking (ReLink) to detect data stores that would be transferred to command interpreters and then identify HOCIVs. ReLink is validated on an experimental embedded system injected with 150 HOCIVs. According to the experimental results, ReLink is significantly better than existing command injection detection tools in terms of detection rate, test space and time.

Author(s):  
Dao Xuan Uoc

Zigbee wireless network built on IEEE 802.15.4 standard is becoming one of the most popular wireless networks in modern IoT devices. One of the disadvantages of Zigbee networks is the short transmission distance between devices. This paper focuses on researching and comparing routing algorithms in Zigbee networks, thereby building the optimal routing algorithm in the existing system. The paper’s objective is to form the basis for making Zigbee tree and mesh networks, which improves the transmission distance for Zigbee networks better than the star network.


Author(s):  
Kundankumar Rameshwar Saraf ◽  
Malathi P. Jesudason

This chapter explores the encryption techniques used for the internet of things (IoT). The security algorithm used for IoT should follow many constraints of an embedded system. Hence, lightweight cryptography is an optimum security solution for IoT devices. This chapter mainly describes the need for security in IoT, the concept of lightweight cryptography, and various cryptographic algorithms along with their shortcomings given IoT. This chapter also describes the principle of operation of all the above algorithms along with their security analysis. Moreover, based on the algorithm size (i.e., the required number of gate equivalent, block size, key size, throughput, and execution speed of the algorithm), the chapter reports the comparative analysis of their performance. The chapter discusses the merits and demerits of these algorithms along with their use in the IoT system.


This chapter delivers general format of higher order neural networks (HONNs) for nonlinear data analysis and six different HONN models. Then, this chapter mathematically proves that HONN models could converge and have mean squared errors close to zero. Moreover, this chapter illustrates the learning algorithm with update formulas. HONN models are compared with SAS nonlinear (NLIN) models, and results show that HONN models are 3 to 12% better than SAS nonlinear models. Finally, this chapter shows how to use HONN models to find the best model, order, and coefficients without writing the regression expression, declaring parameter names, and supplying initial parameter values.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jooyoung Lee ◽  
Jihye Byun ◽  
Jaedeok Lim ◽  
Jaeyun Lee

High-occupancy vehicle (HOV) lanes or congestion toll discount policies are in place to encourage multipassenger vehicles. However, vehicle occupancy detection, essential for implementing such policies, is based on a labor-intensive manual method. To solve this problem, several studies and some companies have tried to develop an automated detection system. Due to the difficulties of the image treatment process, those systems had limitations. This study overcomes these limits and proposes an overall framework for an algorithm that effectively detects occupants in vehicles using photographic data. Particularly, we apply a new data labeling method that enables highly accurate occupant detection even with a small amount of data. The new labeling method directly labels the number of occupants instead of performing face or human labeling. The human labeling, used in existing research, and occupant labeling, this study suggested, are compared to verify the contribution of this labeling method. As a result, the presented model’s detection accuracy is 99% for the binary case (2 or 3 occupants or not) and 91% for the counting case (the exact number of occupants), which is higher than the previously studied models’ accuracy. Basically, this system is developed for the two-sided camera, left and right, but only a single side, right, can detect the occupancy. The single side image accuracy is 99% for the binary case and 87% for the counting case. These rates of detection are also better than existing labeling.


Author(s):  
Sam Noble ◽  
K Kurien Issac

We address the problem of improving mobility of rovers with rocker-bogie suspension. Friction and torque requirements for climbing a single step were considered as performance parameters. The main contribution of the paper is an improved formulation for rover optimization using smooth functions, which enables use of powerful gradient based nonlinear programming (NLP) solvers for finding solutions. Our formulation does not have certain shortcomings present in some earlier formulations. We first formulate the problem of determining optimal torques to be applied to the wheels to minimize (a) friction requirement, and (b) torque requirement, and obtain demonstrably optimal solutions. We then formulate the problem of optimal design of the rover itself. Our solution for climbing a step of height two times the wheel radius is 13% better than that of the nominal rover. This solution is verified to be a local minimum by checking Karush–Kuhn–Tucker conditions. Optimal solutions were obtained for both forward and backward climbing. We show that some earlier formulations cannot obtain optimal solutions in certain situations. We also obtained optimal design for climbing steps of three different heights, with a friction requirement which is 15% lower than that of the nominal rover.


2019 ◽  
Vol 35 (19) ◽  
pp. 3727-3734 ◽  
Author(s):  
Noël Malod-Dognin ◽  
Nataša Pržulj

Abstract Motivation Protein–protein interactions (PPIs) are usually modeled as networks. These networks have extensively been studied using graphlets, small induced subgraphs capturing the local wiring patterns around nodes in networks. They revealed that proteins involved in similar functions tend to be similarly wired. However, such simple models can only represent pairwise relationships and cannot fully capture the higher-order organization of protein interactomes, including protein complexes. Results To model the multi-scale organization of these complex biological systems, we utilize simplicial complexes from computational geometry. The question is how to mine these new representations of protein interactomes to reveal additional biological information. To address this, we define simplets, a generalization of graphlets to simplicial complexes. By using simplets, we define a sensitive measure of similarity between simplicial complex representations that allows for clustering them according to their data types better than clustering them by using other state-of-the-art measures, e.g. spectral distance, or facet distribution distance. We model human and baker’s yeast protein interactomes as simplicial complexes that capture PPIs and protein complexes as simplices. On these models, we show that our newly introduced simplet-based methods cluster proteins by function better than the clustering methods that use the standard PPI networks, uncovering the new underlying functional organization of the cell. We demonstrate the existence of the functional geometry in the protein interactome data and the superiority of our simplet-based methods to effectively mine for new biological information hidden in the complexity of the higher-order organization of protein interactomes. Availability and implementation Codes and datasets are freely available at http://www0.cs.ucl.ac.uk/staff/natasa/Simplets/. Supplementary information Supplementary data are available at Bioinformatics online.


2014 ◽  
Vol 24 (2-3) ◽  
pp. 218-283 ◽  
Author(s):  
J. IAN JOHNSON ◽  
ILYA SERGEY ◽  
CHRISTOPHER EARL ◽  
MATTHEW MIGHT ◽  
DAVID VAN HORN

AbstractIn the static analysis of functional programs, pushdown flow analysis and abstract garbage collection push the boundaries of what we can learn about programs statically. This work illuminates and poses solutions to theoretical and practical challenges that stand in the way of combining the power of these techniques. Pushdown flow analysis grants unbounded yet computable polyvariance to the analysis of return-flow in higher-order programs. Abstract garbage collection grants unbounded polyvariance to abstract addresses which become unreachable between invocations of the abstract contexts in which they were created. Pushdown analysis solves the problem of precisely analyzing recursion in higher-order languages; abstract garbage collection is essential in solving the “stickiness” problem. Alone, our benchmarks demonstrate that each method can reduce analysis times and boost precision by orders of magnitude. We combine these methods. The challenge in marrying these techniques is not subtle: computing the reachable control states of a pushdown system relies on limiting access during transition to the top of the stack; abstract garbage collection, on the other hand, needs full access to the entire stack to compute a root set, just as concrete collection does.Conditionalpushdown systems were developed for just such a conundrum, but existing methods are ill-suited for the dynamic nature of garbage collection. We show fully precise and approximate solutions to the feasible paths problem for pushdown garbage-collecting control-flow analysis. Experiments reveal synergistic interplay between garbage collection and pushdown techniques, and the fusion demonstrates “better-than-both-worlds” precision.


2015 ◽  
Vol 1092-1093 ◽  
pp. 748-752 ◽  
Author(s):  
Shao Jie Feng ◽  
Yan Fei Dong ◽  
Shi Guo Sun ◽  
Sheng Lei Kan

Based on the numerical simulation method and a sample slope engineer of waste dump, the failure modes of waste dump slope is analyzed. By means of analyzing working conditions such as different slope angles, single step, many steps, the failure modes of waste dump slope under different working conditions is obtained. The results show that the slope stability of multiple steps waste dump is better than the slope stability of single step waste dump, and the deformation of the slope is small.


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