39 results about "Hacker" patented technology

The present application relates to the technical field of computer vision and natural language processing, and provides a cross-modal transferable backdoor attack method and device, comprising: constructing a backdoor dataset containing a trigger based on an unlabeled original dataset; inputting the original dataset and the backdoor dataset containing the trigger into a pre-constructed hacker network, and respectively calculating clean data silence loss and backdoor toxicity loss with the trigger; pre-training the pre-constructed hacker network by minimizing the clean data silence loss and the backdoor toxicity loss; calculating feature representation of a target category through image data and text data of the target category, generating a target CLIP model with a backdoor by using the pre-trained hacker network and the feature representation of the target category; and attacking by using the generated model. The backdoor trigger can be embedded in multi-modal data at the same time, has strong cross-modal transferability and concealment, and does not depend on large-scale labeled data.

The present disclosure provides a method for tracing a path of an attack on a smart contract on a blockchain, belonging to the technical field of blockchains. The method specifically includes: determining a hacker's attack address, and determining an attack's start time and an attack's stop time according to a data record of the hacker's attack address; and determining hash values of all transactions from a hacker's attack destination address between the attack's start time and the attack's stop time automatically, and obtaining a fungible token and a non-fungible token by parsing the hash values automatically. The problems of large error and low efficiency during original manual extraction are solved, accuracy and efficiency are higher, and the overall security is improved.

Various embodiments of systems and methods for an at-risk system identification via analysis of discussions from various online hacker communities are disclosed herein.

The invention discloses a data transmission method and a data transmission system, and relates to the technical field of information security. The method comprises the following steps: under the condition of establishing communication with an application server, receiving a first data transmission request sent by the application server, the data transmission request comprising to-be-transmitted first service data; generating an encryption key, and encrypting the first service data based on the encryption key to obtain a first encrypted file; and under the condition of establishing communication with the target terminal equipment, transmitting the first encrypted file to the target terminal equipment through the USB interface. According to the technical scheme provided by the invention, the risks that the sensitive data is decrypted after the terminal equipment is stolen and a hacker simulates and counterfeits a legal terminal to forge service data to be transmitted back for enforcement can be effectively reduced, and the data transmission security requirement of a high-security requirement unit on the network-free terminal equipment can be met.

The invention provides an Internet of Vehicles master-slave multi-chain architecture method based on a block chain. The method comprises five stages of system initialization, vehicle registration, data preprocessing, slave chain consensus and global synchronization. The risk of single-point failure and privacy disclosure due to the fact that the traditional Internet of Vehicles depends on a third-party trust mechanism to carry out data transmission is considered. Therefore, according to the method, the distributed technology of the block chain is adopted, the PBFT consensus algorithm is optimized by fusing the reputation mechanism and the utility guidance strategy, and the corresponding smart contract is deployed on the node of the block chain, so that the data transmission efficiency is remarkably improved, and the data tampering and stealing behaviors of hackers can be effectively resisted. Meanwhile, distributed storage of a large amount of data is achieved in combination with the IPFS storage technology, and the storage pressure of the server is relieved. Besides, a hybrid encryption mechanism combining a symmetric key and an asymmetric key is adopted, so that vehicle coordination and interaction among different cities are guaranteed, and consistency, integrity and security of data transmission are ensured.

According to the BMS direct current charging non-inductive upgrading method and device, the electronic equipment and the storage medium, online upgrading of software firmware is synchronously carried out in the vehicle direct current charging process, and high-stability non-inductive flashing is achieved. According to the scheme, the defects of a traditional mode are effectively avoided; compared with offline UDS flashing of a 4S store, normal use of the vehicle is not affected at all; compared with remote OTA flashing, the system has the advantages that flashing failure or system reset risks caused by network problems are completely eradicated by the aid of stable and reliable charging connection, the upgrading process is independent of a CAN (controller area network) and the internet in the vehicle, and extra loads cannot be caused. Meanwhile, according to the scheme, hacker attacks are effectively defended through a safe communication mechanism, upgrading information is stored by using technologies such as a block chain, and complete historical tracing and clear three-party responsibility definition are realized. According to the scheme, a high-performance chip does not need to be upgraded for the BMS or an advanced gateway does not need to be additionally arranged for the vehicle, and the vehicle cost is remarkably reduced.

The present invention relates to a cloud-based roadway equipment monitoring system that mainly provides and constructs a plurality of servers to receive and record the return data transmitted from all roadway equipment, such as vehicle detector, changeable message sign, automatic vehicle identification, traffic signal controller, electronic tag and more, within a specific area through a router monitoring data device that replaces the existing internet-connected router-modem devices. The present invention can monitor, record, and prevent hacker invasion to enhance the availability of devices of the roadway equipment and help the traffic control center to clarify responsibility of equipment vendors.

Various embodiments for predicting which software vulnerabilities will be exploited by malicious hackers and hence prioritized by patching are disclosed.

Malicious users (or hackers) can take advantage of user devices on or communicably connected to an autonomous vehicle (AV) to gain unauthorized access to AV subsystems (e.g., AV compute system, AV sensors, AV controls system, and AV cabin system). To address this concern, a one-way Ethernet communication link can be placed between the AV subsystems and the user devices. The one-way communication link can physically ensure that the user devices may only receive content from the AV systems, and that the user devices may not send data to the AV systems on the one-way communication link. A feature-limited backchannel that may be normally used for transporting audio data on a daisy-chained bus can be used by the user devices to transmit (8-bit) code words that correspond to specific messages to convey messages back to the AV systems.

The invention belongs to the technical field of network security and machine learning, and discloses an industrial control hacker organization identification method based on a Gaussian self-organizing incremental neural network. Dividing the network attack traffic into a plurality of traffic sessions through the session time threshold; representing each flow session in an attack mode, and introducing an attack time feature into the attack mode; and learning the time sequence characteristics of the attack pattern. Performing feature selection; classifying the attack modes after feature selection based on a Gaussian self-organizing incremental neural network; constructing a network attack heterogeneous graph; constructing a hacker relationship meta-path set: researching the relationship between hackers by evaluating all combinations of node types to form a meta-path; filtering meaningless meta-paths to obtain an effective meta-path set; learning attribute features and structural features of the nodes to obtain embedded vectors of the nodes; and incremental clustering is carried out on the embedded vectors of the hacker nodes through a Gaussian self-organizing incremental neural network, and industrial control hacker organizations are identified.

The embodiment of the specification discloses a kind of based on smart contract's blockchain asset protection method and device, wherein the method includes: creating and deploying the smart contract for blockchain asset protection, the method of smart contract includes the storage, unlocking, taking out, recovery operation and / or setting time lock to the blockchain asset;Call storage method, so that the blockchain asset to be protected is saved to smart contract;When user intends to take out blockchain asset, call unlocking method, so that blockchain asset is marked as to be taken out;When time lock expires, call taking out method, so that the blockchain asset to be taken out is transferred to hot wallet address;When user intends to stop taking out blockchain asset, call recovery method, so that the blockchain asset to be taken out is reset to locked state.The present application scheme introduces time lock and recovery double mechanism on the basis of smart contract, by dynamically adjusting hot wallet address and time lock, can effectively prevent hacker from stealing blockchain asset.

The invention provides a text classification model training method, system and equipment based on reinforcement learning, and the method comprises the steps: constructing a training data set passing initial verification, and generating a response text containing a reasoning process and a classification result based on a pre-training language model for a to-be-classified text in the training data set; acquiring a historical reasoning process corresponding to the classification result in the dynamic historical cache region, calculating the similarity between the reasoning process and the historical reasoning process, judging whether the similarity falls into a preset similarity interval or not, and determining whether the reasoning process meets diversity requirements or not; determining a target reward value based on the correctness of the target classification result and whether the reasoning process meets diversity requirements; and updating parameters of the pre-training language model through a reinforcement learning algorithm by using the target reward value. According to the invention, the training data is generated based on self-consistent verification, so that the marking cost is reduced; and in combination with diversified rewards, hacker reward behaviors are inhibited, so that the real reasoning ability and classification performance of the model are improved.

Embodiments of the present disclosure disclose a computing power resource safe calling method and device, a storage medium and a program product. The method comprises: obtaining real calling information of a computing power resource node, generating virtual calling information of the computing power resource node based on the real calling information; receiving a computing power calling request of a user end, authenticating the computing power calling request, and determining a target computing power resource node requested by the user; if the authentication is successful, sending the real calling information of the target computing power resource node to the user end, so that the user end calls the target computing power resource node; if the authentication fails, sending the virtual calling information of the target computing power resource node to the user end. The method can determine whether to send real or virtual calling information to the user end through authentication, which can ensure the safety of computing power resources and prevent hackers from illegally logging in and misusing.

Methods are disclosed for selectively controlling access to a resource that is accessible to multiple nodes in a multi-node system or multiple processors in a multi-processor system to prevent hackers, malware, and ransomware attacks. The multi-node or multi-processor systems receive both matching and non-duplicated requests. In operation, each node or processor receives either a matching or non-duplicated request to access the resource. For the matching request, indicia of the request to access the resource is computed at each node or processor and is then compared between nodes or processors. Access to the resource is given to a node or processor when the computed indicia matches. For the non-duplicated request, a determination is made as to whether direct access to the resource is authorized for the request, and, if direct access is authorized, access to the resource is given to a node or processor.

Hacker attacks that involve stimulating voltage variations in an integrated circuit package are detected by deploying a network of elementary detectors distributed across the integrated circuit package. Each detector is positioned at a respective location within the package and is configured to generate an alarm signal in response to a voltage variation occurring at that specific location. The elementary detectors include a first component and a second component (such as flip-flops) with respective outputs configured to be set to complementary binary levels. Logic circuitry is coupled to the outputs of the first and second components and is designed to generate an alarm signal when the outputs of the first and second components no longer exhibit complementary binary levels, indicating a hacker attack involving a localized voltage variation within the integrated circuit package.

The application provides a network security defense device actively responding to hacker intrusion, belonging to the technical field of network security, comprising a collection platform, an analysis platform, a blocking platform and an alarm platform connected in sequence, the collection platform is provided with multiple simulation probes, including multiple first, second and third simulation probes, the analysis platform is connected with each of the first, second and third simulation probes to obtain the traffic data collected by the simulation probes and store the collected data, when the IP address in the traffic data does not match the IP address in the white list, the behavior of the IP address in the traffic data is labeled and then output to the blocking platform, the blocking platform takes different blocking measures according to different objects attacked by the attack IP address, and after the blocking is completed, the alarm platform sends alarm information to the network security administrator. The application can discover the attacker in time, actively block and alarm, does not need manual participation, enhances the defense effect, improves the operation and maintenance efficiency and reduces the operation and maintenance pressure.

The invention discloses a live broadcast transparent transmission method in a monitoring system, and the method comprises the following steps: S1, enabling a user to obtain the control right of monitoring equipment, firstly needing to be connected to a system server, and verifying the identity through a user name password; s2, after the identity verification succeeds, acquiring a passing token corresponding to the monitoring equipment, and acquiring network address information of the monitoring equipment, otherwise, requiring re-authentication by the user; s3, judging whether the monitoring equipment and the user are in the same network or not, if so, directly connecting the monitoring equipment through the pass token, and otherwise, establishing special connection; s4, if the communication token is valid, the monitoring device can be controlled and the real-time monitoring video can be watched, otherwise, the user cannot control the monitoring device, by adopting the method, the user directly connects the monitoring device in a point-to-point encryption connection mode, the server pressure and the bandwidth pressure can be reduced, hackers can be effectively prevented from intercepting and tampering data, the safety is higher, and the user experience is improved. Wide application prospects are realized, and popularization and application are facilitated.

The disclosed invention comprises a tokenisation method in which a computer-based system implements consistent tokenisation on a decentralized blockchain network. The blockchain consists of multiple independent nodes that ensure hacker-resistant operation and maintenance. Users can create wallets to store programmable payment tokens, which are securely tradable in real-time between users and their devices via the blockchain. The currently valid countervalue of each programmable payment token is automatically calculated through technical means, based on: (i) a gold value component tied to a fixed quantity of physical gold, (ii) a dynamic, inflation-adjusted M Unit derived from official monetary data sources including M2, CPI, and optionally Stablecoin-Adjusted M2 (M2S), and (iii) an optional reserve or cash component representing a defined percentage of the combined value of (i) and (ii).

One variation of the method includes: at an application, accessing a data stream, encrypting the data stream, and passing the data stream to a data protection tool; at the data protection tool, encrypting the data stream and passing the data stream to a data store; and at the data store, encrypting the data stream; and storing the data stream. This variation of the method also includes, at the application: receiving a request to access the data stream from a first entity; accessing a set of user attributes representing an authentic user; accessing a set of entity attributes; calculating a first trust score for the entity based on the set of user attributes and the set of entity attributes; and, in response to the first trust score falling below a first threshold trust score, generating a decoy data stream and serving the decoy data stream to the entity.

The embodiment of the invention provides a data processing method and device, equipment, a storage medium and a program product, and particularly relates to the technical field of information security. The method comprises the following steps: acquiring collected fire-fighting monitoring data; encrypting the fire-fighting monitoring data to obtain encrypted data, and performing hash processing on the fire-fighting monitoring data to obtain a corresponding first hash value; and storing the encrypted data and the first hash value in a block chain node of a block chain network. The method is used for achieving the effects of ensuring the data security of the fire-fighting monitoring data and preventing the data from being leaked and attacked by hackers.

The application relates to an abnormality detection method and device, equipment, a storage medium and a program product, and belongs to the technical field of information security. For host data in each dimension sent by a to-be-detected device, all data frequent items, same-process-group frequent items and same-session frequent items are calculated. Historical command in the host data is input into a prediction model to obtain predicted command type information output by the prediction model. The predicted command type information is compared with type information of real commands in the host data to obtain an abnormality comparison result. The abnormality comparison result, all data frequent items, same-process-group frequent items and same-session frequent items are input into a classification model to obtain a target abnormal event type. An abnormality detection result is generated based on the target abnormal event type. Through the application, the detection accuracy of abnormality detection on a behavior sequence of a host can be improved, the security of the host is improved, and the probability of a business collapse caused by a hacker attack on the host is reduced.

The application provides a kind of ship network security protection system and method, it is related to ship network security technical field, the system includes storage module, detection management module, selection module and auditing and output module, the ship network security protection system and method provided by the application adopt double confirmation mechanism, the access or change of ship network key parameters is confirmed twice using automated vulnerability scanning tool, additional confirmation step and security requirement are increased, the defense capability of system to potential security threat is significantly improved, it is helpful to prevent hacker or malicious user from executing illegal operation by forging identity or exploiting system vulnerability, so as to protect the safe and stable operation of ship network system, and adopt priority sequencing rule, improve vulnerability processing efficiency, and high-risk vulnerability is processed preferentially to help reduce the exposure of system, reduce the possibility of being attacked by attacker, to improve the overall security of system, protect critical data and business from being violated.

A method of providing cyber security to an industrial control system is described. The method includes detecting an anomaly and recording and reporting the detected anomaly to a control system within a network associated with the industrial control system. Detecting the anomaly may include recording all unauthorized attempts to connect to a communication port in the network, capturing identifying information associated with the unauthorized attempts, detecting scanning activity of a hacker in the network, detecting an attempt to manipulate a log file to conceal malicious activity in the network; and recording and reporting the detected anomaly to a controller within the network.

A reset pad circuit has first and second inputs coupled, respectively, to a first reset access port receiving a first reset request and a second reset access port. The reset pad circuit generates a first reset state signal. An internal reset activation gate has inputs coupled to internal resources and an output that applies a reset request to the second reset access port. A memory element has first and second inputs coupled, respectively, to the output of the reset activation gate and the output of the reset pad circuit. The memory element generates a second reset state signal when receiving the reset request until receiving the first reset state signal. A reset forward gate coupled to outputs of the reset pad circuit and the memory element generates a system reset request in response to the first reset state signal or the second state signal.

The invention discloses a cellular network access point selection and network slicing method based on deep reinforcement learning. According to the method, network slicing and AP selection are optimized through a soft actor commentator and a constrained Markov decision process algorithm so as to meet QoS requirements of different UE in IIOT. By maximizing the long-term proportional fairness of the UE, the problem caused by imperfect CSI is solved, and the reliability and efficiency of uplink communication are improved. In addition, according to the invention, the decision of the network slice is guided through SINR prediction, so that the phenomenon of rewarding hackers is effectively avoided, and the robustness of the system and the fairness of resource allocation are improved. Through a dynamic resource allocation mechanism, resource waste can be reduced, user service experience is guaranteed, and the utilization efficiency of network resources is optimized. According to the method provided by the invention, the resource utilization rate in the cellular-removed large-scale MIMO network can be remarkably improved, the network efficiency and the service quality are ensured, and the method has relatively strong intelligent scheduling capability.

The application discloses a message sending method and device and a storage medium, and comprises the following steps: receiving a message, the message will be detected and processed by a hop-by-hop network node in a message forwarding path; carrying a control plane identifier for uploading on a message extension header, the control plane identifier is used to indicate that the message is carried on the information of a control plane or a forwarding plane; and sending the message. According to the application, on the basis of supporting existing hop-by-hop processing functions, the ability of processing message information hop by hop on a forwarding plane can also be supported, and the function can meet the needs of new technologies such as slicing and flow detection. The control plane identifier for uploading can be effectively prevented from being tampered with or used by hackers to attack network nodes.

The utility model discloses an anti-hacking microphone-forbidding circuit of an intelligent voice sound box. The anti-hacking microphone-forbidding circuit comprises an MCU, a key circuit, a switching circuit, a Mic circuit and a power supply circuit. The MCU is electrically connected with the key circuit, the power supply circuit and the switching circuit respectively; the switching circuit is connected between the power supply circuit and the MIC circuit; and the MCU controls the on / off of the switching circuit according to the obtained input signal of the key circuit so as to connect or disconnect the connection between the power supply circuit and the Mic circuit. By implementing the intelligent voice product, sensitive privacy information can be timely prevented from being intercepted through the MIC of the product, the cost is low, the power consumption is low, the safety and the reliability are realized, and the problem that the privacy information of a user is leaked due to the fact that the voice information acquired by the MIC is easily intercepted by a hacker in the existing intelligent voice product is solved.

The application provides a component updating method and device, a storage medium and a computer device. Each parameter in a component updating version is used to perform hot updating on a corresponding parameter in a verification code component, and a corresponding verification code is generated based on the hot updated verification code component. In the application, the hot updating can bypass the audit process in the version updating process, flexibly and quickly repair problems in the application, and therefore, the verification code component is updated by using the hot updating mode, without human cost of the access party, and real-time updating can be performed. When the verification code component is updated by using the latest component updating version, the client is preconfigured with a set running space for the verification code component, and then, more functions can be updated at the same time during the component updating, such as a verification code style, a burying point parameter, a check bit logic and the like. Through the real-time updating of the verification code component, diversified attacks of hackers can be effectively prevented.

The invention provides a ship network security protection system and method, and relates to the technical field of ship network security, and the system comprises a storage module, a detection management module, a selection module and an auditing and outputting module. An automatic vulnerability scanning tool is used for carrying out secondary confirmation on access or change of ship network key parameters, additional confirmation steps and security requirements are added, the defense capability of the system for potential security threats is remarkably improved, hackers or malicious users can be prevented from executing illegal operations by counterfeiting identities or utilizing system vulnerabilities, and the safety of the system is improved. Therefore, safe and stable operation of the ship network system is protected, a priority ranking rule is adopted, vulnerability processing efficiency is improved, high-risk vulnerabilities are processed preferentially, the exposed surface of the system is reduced, the possibility of being used by attackers is reduced, the overall safety of the system is improved, and key data and services are protected from being damaged.