A novel botnet attack detection for IoT networks based on communication graphs

Intrusion detection systems have been proposed for the detection of botnet attacks.Various types of centralized or distributed cloud-based machine learning and deep learning models have been suggested.However,the emergence of the Internet of Things(loT)has brought about a huge increase in connected devices,necessitating a different approach.In this paper,we propose to perform detection on IoT-edge devices.The suggested architecture includes an anomaly intrusion detection system in the application layer of IoT-edge devices,arranged in software-defined networks.loT-edge devices request information from the software-defined networks controller about their own behaviour in the network.This behaviour is represented by communication graphs and is novel for IoT networks.This representation better characterizes the behaviour of the device than the traditional analysis of network traffc,with a lower volume of information.Botnet attack scenarios are simulated with the IoT-23 dataset.Experimental results show that attacks are detected with high accuracy using a deep learning model with low device memory requirements and significant storage reduction for training.

Experiments in Consensus-based Decentralized Information Feedback Control Strategies on a Real Robotic Fish Platform

A decentralized information feedback mechanism was introduced to a group of mobile robots such that the robots asymptotically converge to a given moving formation. While various distributed cooperative control strategies have been studied in theory,few of them have been systematically validated on experimental platforms. This paper demonstrates the experimental results of consensus-based decentralized information feedback mechanism on a multiple mobile robotic fish platform. In this paper, we firstly introduced a fundamental consensus algorithm for systems model and the cooperative control experimental platform,and then experimentally implemented and validated the formation control algorithm through setting transit point and lookup table method and so on. The experimental results show the effectiveness of the consensus-based decentralized information feedback control strategies.

Epidemic-Like Proximity-Based Traffic Offloading

Cellular networks are overloaded due to the mobile traffic surge,and mobile social networks(MSNets) can be leveraged for traffic offloading.In this paper,we study the issue of choosing seed users for maximizing the mobile traffic offloaded from cellular networks.We introduce a gossip-style social cascade(GSC) model to model the epidemic-like information diffusion process in MSNets.For static-case and mobile-case networks,we establish an equivalent view and a temporal mapping of the information diffusion process,respectively.We further prove the submodularity in the information diffusion and propose a greedy algorithm to choose the seed users for traffic offloading,yielding a sub-optimal solution to the NP-hard traffic offloading maximization(TOM) problem.Experiments are carried out to study the offloading performance,illustrating that the greedy algorithm significantly outperforms the heuristic and random algorithms,and user mobility can help further reduce cellular load.

Distributed adaptive prescribed-time orbit containment control for satellite cluster flight

The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is investigated.The directed information communication topology between followers is taken into account in the overall paper.When the satellite mass is assumed to be constant,a distributed prescribed-time orbit containment controller is,firstly,presented to drive the followers into the dynamic convex hull produced by multiple leaders.Then,the parameter uncertainty is considered,and a prescribed-time sliding mode estimator is introduced to estimate the desired velocity of each follower.Based on the estimated state,a novel distributed adaptive prescribed-time orbit containment control scheme is proposed.The Lyapunov stability theory is utilized to prove the prescribed-time stability of the closed-loop system.Finally,several numerical simulations and comparison of different control methods are provided to verify the effectiveness and superiority of the proposed control method.

Review of attitude consensus of multiple spacecraft

A group of cooperative agents can finish complicated missions that are difficult for a large machine.In the past two decades,spacecraft attitude coordination has attracted significant research attention owing to its wide potential applications.This paper presents a survey of recent research progress on the spacecraft attitude consensus problem,paying particular attention to the papers published in major aerospace,dynamics,automation,and robotics journals since 2015.Attitude consensus concepts for centralized,decentralized,and distributed cases are reviewed.This overview summarizes results on system dynamics and consensus algorithms based on frequently used attitude representations,such as Euler angles,modified Rodrigues parameters,unit quaternions,and rotation matrices.Studies conducted under complicated operating conditions are also covered.Experimental results on attitude consensus are discussed.In the final section,the main conclusions are drawn and several potential research directions are provided.

DroidEcho:an in-depth dissection of malicious behaviors in Android applications

A precise representation for attacks can benefit the detection of malware in both accuracy and efficiency.However,it is still far from expectation to describe attacks precisely on the Android platform.In addition,new features on Android,such as communication mechanisms,introduce new challenges and difficulties for attack detection.In this paper,we propose abstract attack models to precisely capture the semantics of various Android attacks,which include the corresponding targets,involved behaviors as well as their execution dependency.Meanwhile,we construct a novel graph-based model called the inter-component communication graph(ICCG)to describe the internal control flows and inter-component communications of applications.The models take into account more communication channel with a maximized preservation of their program logics.With the guidance of the attack models,we propose a static searching approach to detect attacks hidden in ICCG.To reduce false positive rate,we introduce an additional dynamic confirmation step to check whether the detected attacks are false alarms.Experiments show that DROIDECHO can detect attacks in both benchmark and real-world applications effectively and efficiently with a precision of 89.5%.