A true random metastable flip-flop (TRMFF) compiler generates an electrical architecture for a TRMFF chain. The compiler selects components for the TRMFF chain from a library of standard cells and logically connects these components in accordance with a primitive polynomial to generate the electrical architecture. The TRMFF chain provides a sequence of random numbers from one or more physical processes in accordance with the primitive polynomial. During operation, one or more microscopic phenomena inside and/or outside of the TRMFF chain can cause one or more low-level, statistically random entropy noise signals to be present within the TRMFF chain. The TRMFF chain advantageously utilizes the one or more low-level, statistically random entropy noise signals to provide the sequence of random numbers.

The present disclosure is directed to systems and methods for the selective introduction of low-level pseudo-random noise into at least a portion of the weights used in a neural network model to increase the robustness of the neural network and provide a stochastic transformation defense against perturbation type attacks. Random number generation circuitry provides a plurality of pseudo-random values. Combiner circuitry combines the pseudo-random values with a defined number of least significant bits/digits in at least some of the weights used to provide a neural network model implemented by neural network circuitry. In some instances, selection circuitry selects pseudo-random values for combination with the network weights based on a defined pseudo-random value probability distribution.

A random bit circuit includes four storage cells controlled by four different word lines. The first storage cell and the second storage cell are disposed along a first direction sequentially, and the first storage cell and the third storage cell are disposed along a second direction sequentially. The third storage cell and the fourth storage cell are disposed along the first direction sequentially. The first storage cell and the fourth storage cell are coupled in series, and the second storage cell and the third storage cell are coupled in series.

A method of writing data to a protected region in response to a request from a host includes receiving a first write request including a first host message authentication code and a first random number from the host, verifying the first write request based on a write count, the first random number, and the first host message authentication code, updating the write count based on a result of verifying the first write request, generating a first device message authentication code based on the updated write count and the first random number, and providing the host with a first response including the first device message authentication code and a result of the verifying of the first write request.

Systems and methods are described for resource-efficient memory deduplication and write-protection. In an example, a method includes receiving, by a computing device having a processor, a request to assess deduplication for a plurality of candidate files. The computing device may perform one or more iterative steps for deduplication. The iterative steps may include: receiving, from the plurality of candidate files, a candidate file that is not write-protected; determining, based on a predetermined Bernoulli distribution, a decision to write-protect the candidate file; rendering the candidate file as a write-protected candidate file; determining, based on a review of other candidate files from the plurality of candidate files, that the write-protected candidate file can be deduplicated; and deduplicating the write-protected candidate file.

A method for correcting spatially variable electron flux in a true random number generator (TRNG) is presented. The TRNG comprises a radioactive source and an array of detectors, and the method comprises: (a) segmenting the array of detectors into a plurality of groups; (b) for each group: (1) detecting via multiple detectors an electron signal from the decay of the radioactive source; (2) determining a number of detections based on the detection of step (b)(1); (3) determining a group median count based on the number of detections; (4) comparing the group median count to either (A) a detection count from a single detector within the group, or (B) a detection count from multiple detectors within the group; (5) based on the comparison, assigning a value to a string of values; and (c) determining a true random number based on the string of values. A TRNG implementing the method is also disclosed.

A random bit generator includes a voltage source, a bit data cell, and a sensing control circuit. The voltage source provides a scan voltage during enroll operations. The data cell includes a first transistor and a second transistor. The first transistor has a first terminal coupled to a first bit line, a second terminal coupled to the voltage source, and a control terminal. The second transistor has a first terminal coupled to a second bit line, a second terminal coupled to the voltage source, and a control terminal. The sensing control circuit is coupled to the first bit line and the second bit line, and outputs a random bit data according to currents generated through the first transistor and the second transistor during an enroll operation of the bit data cell.

A random number generating circuit includes: an oscillation circuit including a plurality of first delay elements connected to each other in series to generate an oscillation signal; a sampling circuit including a plurality of second delay elements connected to each other in series to generate a plurality of sampling signals by sampling the oscillation signal at a plurality of sampling points in time based on the plurality of second delay elements; and a random number determining circuit configured to generate a random number based on a target sampling point in time associated with a target sampling signal in which a first logic level transition occurs from among the plurality of sampling signals, wherein the plurality of sampling points includes the target sampling point.

A method for electro-depositing a radioactive material onto a metal substrate is disclosed. This is particularly well-suited for true random number generators. The method includes (a) at least partially masking the metal substrate to expose a metallic surface on the metal substrate; (b) connecting the metal substrate to a cathode of a current source; (c) submersing the exposed metallic surface into a solution containing radioactive metal ions, wherein the solution is connected to an anode of the current source; (d) removing the exposed metallic surface from the solution; (e) removing the solution from the exposed metallic surface; (f) measuring the amount of radioactivity emitted from the exposed metallic surface; and (g) repeating steps (c) through (f) until the amount of radioactivity measured in step (f) stabilizes relative to a previous measurement.

A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The tunnel device is selected based on an attribute, such as IP Geolocation. A tunnel bank server stores a list of available tunnels that may be used, associated with values of various attribute types. The tunnel devices initiate communication with the tunnel bank server, and stays connected to it, for allowing a communication session initiated by the tunnel bank server. Upon receiving a request from a client to a content and for specific attribute types and values, a tunnel is selected by the tunnel bank server, and is used as a tunnel for retrieving the required content from the web server, using standard protocol such as SOCKS, WebSocket or HTTP Proxy. The client only communicates with a super proxy server that manages the content fetching scheme.